Course Name（科目名）

Algorithm Expression

Instructor Name(担当教員名）

Teigo Nakamura

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Understanding the representation of control structures, procedures, and data structures required by algorithms
for realizing intelligent information processing, and learning various game tree search methods and methods toimprove search efficiency using game programming as the target area of artificial intelligence.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

It is assumed that students have acquired basic concepts related to programming and data structures andalgorithms.

Theme(テーマ）

Contents（内容）1. Classification of thinking games
2. State space search method
3. Game tree search mechanism
4. Date structure of game positions
Alpha-beta search and its
5.
efficiency
6. Iterative deepening
Course Calendar/Class Topic（授業計画）

7. Game tree expansion
8. Transposition table
9. Window search
10. Control of search space
11. Proof number search
12. Depth-first proof number search
13. Monte Carlo tree search (1)14. Monte Carlo tree search (2)General Course Policies（授業の進め方）
CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15. Final report
At first, the teacher gives lectures, and then each student gives a presentation on the tasks assigned tohim/her. At the end of the semester, report assignments will be given.
Acquiring "basic scholastic ability required in information science / engineering and various fields" listed in the
Common Learning Educational Objective (B) of the Graduate School of Computer Science and Systems
Engineering.
1. Understanding the characteristics of various data structures for game positions.
2. Understanding the basic concept of game tree search and describing search algorithms.
3. Understanding the methods to improve search efficiency and their characteristics.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

For each objective above, the degree of achievement is evaluated based on the results of assignment
presentation status (60%) and final report (40%).

Assignment Instructions（授業外学習（予習・復習）の指示）

As a preparatory, study four hours a week. In the presentation of the assignment, make sure to review therelevant literature and make preparations.

Keywords（キーワード）
Required Textbooks（教科書）Game Computation Mechanism , Yoshiyuki Kotani, Corona Publishing CO., LTD.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

teigo@ai.kyutech.ac.jp

Course Name（科目名）

Advanced modern control theory

Instructor Name(担当教員名）

Noboru Sebe

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective and required course
Credits（単位数）2
Modern control theory concerns the analysis and design of control systems based on the state space
representation. This course focuses on robust control methodologies for linear systems. Topics include:
Quantitative analysis of controllability and observability, model reduction based on the balanced realization,
disturbance observer, discretization, non-minimum phase systems, servo control.
The students should have enough knowledge about the control theory based on the state space
representation.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Contents（内容）1. Quantitative analysis ofcontrollability and observability (1)2. Quantitative analysis ofcontrollability and observability (2)3. Balanced realization and model
reduction
4. State estimation
5. Disturbance observer
6. Servo control (1)Course Calendar/Class Topic（授業計画）

7. Servo control (2)8. Two dgrees of freedom control
systems
9. Non-minimum phase systems (1)10. Non-minimum phase systems (2)11. Discretization
12. Discrete-time control systems
13. Sampled-data control systems (1)14. Sampled-data control systems (2)General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

15. Kalman filter
LectureThis class introduce advance topics of modern control theory.
1. The students should be able to apply model deduction based on the balanced realization.
2. The students should be able to analyse and synthesise sampled-data control systems.
3. The students should be able to synthesise servo control systems.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

100% - Homework/Assignments

Assignment Instructions（授業外学習（予習・復習）の指示）

The students are expected to prepare for this class more than 4 hours a week.

Keywords（キーワード）

Modern control theory, controllability and observability gramians, banaced realization, servo control, nonminimum phase systems, smapled-data control

Required Textbooks（教科書）

None

References/Recommended Reading（参考書）

None

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced Corporate Information System

Instructor Name(担当教員名）

Koji Murata, Masaki Yamamoto

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The goal of this course is the understanding of "the role of information systems" and "approaches to designing
information systems" in business companies. Today's information systems should support business activities
and enhance enterprise value. The course consists of two halves: The first half discusses changes in businessenvironment, required human resources for the changes, and analyzes entire corporate business issues bycollaborative team activities. The second half outlines the roles of business departments and the need forbusiness transformation, followed by business assessment workshop.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is designed to lead students to understand the role and design of information systems in the realworld. Students are encouraged to take other courses in ICT and cloud computing.
Theme(テーマ）

Contents（内容）Changes in business environment and recent success factors
1.
in Japanese business
2.

Required human resources for the changes in businessenvironment

3. Corporate basic activities, philosophy, vision, and strategy
Course Calendar/Class Topic（授業計画）

4.

Introduction to corporate analysis methodology - marketing
analysis, financial statements analysis, issue analysis

5. Groupwork and presentation of issue list of a real company
6. Roles of departments in a company
7. Approach to business transformation
8. Business assessment for the adoption of ICT
General Course Policies（授業の進め方）
Introduction to Couse
Objectives（授業の達成目標の解説）
CourseObjectives（授業の達成目
Couse objectives
標）(具体的な授業の達成目標）

9. Business assessment workshop for the adoption of ICT
The course includes lecture, discussion, group work, and presentation.
Students are expected to:Master the approaches to corporate analysis and corporate strategy planning, as well as the principles
1. of thinking.
Develop skills in analyzing real companies, listing their issues, and presenting the solution proposals from
2. a wide perspective
Understand approaches to business transformation and master the principles of business assessment
3. for the adoption of ICT

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

In the above objectives, the first item is evaluated with (a) and (b) below, the second item is with (c), and thethird is with (a) and (d).
(a) Participation in discussion and groupwork (20%)(b) Mid-term report of realization, awareness of personal issues ("KI-ZU-KI") (10%)(c) Mid-term groupwork and presentation of issues list of a company (30%)(d) Presentation at the final business assessment workshop (40%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Following directions in the class, students should prepare reports and presentations in time. The course will
require 4 hours of preparation work per week.

Keywords（キーワード）

changes in business, principles of thinking, mind change, principles of corporate activities, corporate philosophy,
corporate vision, corporate strategy, information systems planning, business process, logical thinking, businessassessment, financial statements analysis

Required Textbooks（教科書）Lecture slides are distributed.

References/Recommended Reading（参考書）

Reference materials are recommended as required.

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced Linear Algebra

Instructor Name(担当教員名）

Noboru Sebe

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1Linear algebra is a branch of mathematics that studies systems of linear equations and the properties ofmatrices.This course covers matrix theory and norms of vectors, matrices and signals.

Course Description（授業の概要）

The students should have enough knowledge about the basic linear algebra, such as matries and vectors.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Eigenvalues and eigenvectors
Positive and negative definiteness2.
of matrices
3. Singular varlue decomposition
Rank reduction and approximation
4.
of matrices
5. Kronecker products
6. Norms of vectors and matrices
Course Calendar/Class Topic（授業計画）

7. Norms of signals
8. Additional explanation
9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目
Couse objectives
標）(具体的な授業の達成目標）

15.
LectureThis course introduces the some concepts of matrices, such as singular values, positive and negative
definiteness. Also the norms of vectors, matrices and signals are introduced in this course.
1. The students should be able to understand the notions of singular values and definiteness of matrices.
2. The students should be able to understand the norms of vectors, matrices and signals.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

100% - Homework/Assignments

Assignment Instructions（授業外学習（予習・復習）の指示）

The students are expected to prepare for this class more than 4 hours a week.

Keywords（キーワード）

Positive definiteness, Singular values, Kronecker product, norms of vectors, matrices, and signals

Required Textbooks（教科書）

None

References/Recommended Reading（参考書）

None

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Compressed Data Processing

Instructor Name(担当教員名）

Tomohiro I

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Data compression aims at removing the redundancy of data. Although data compression has been developed tostore and/or transmit data efficiently, it tends to prevent us from using the data as we usually have to pay thecost of expanding the compressed data. Recently this problem becomes much more apparent since large scaledata are ubiquitous. To solve this problem, lots of work have been dedicated to "compressed data processing",
The aim of this course is to learn the theory of compressed data processing. Students who take the course
ought to have basic knowledge on how to evaluate algorithms and data structures.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Course Calendar/Class Topic（授業計画）

Contents（内容）1. Introduction
Succinct Data Structure: rank,
2.
selectSuccinct Data Structure: rank,
3.
select for sparse bit vectors
Succinct Data Structure: Wavelet
4.
Tree
Succinct Data Structure: Range
5.
Minimum Query
Succinct Data Structure: Succinct
6.
Tree
7. Grammar Compression
Fundamental Operations on
8.
Grammar Compression
9. SLP-index
Longest Common Extensions on
10.
Grammar Compression
11. LZ-index
12. BWT
13. FM-index
14. r-index

General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

15. Conclusions
Lectures are given with slides that will be available online. When needed, there will be some exercises to help
understanding.
Someshort reports
will beassigned.data processing methods, which have been developedThis
course aims
at learning
the theoryof alsocompressed
recently. More concretely, the objectives are
1. to recognize redundancies in data and to understand that data compression plays an important role indata processing,
2. to understand how to evaluate the data compression methods,
3. to learn how to choose an appropriate compression method in accordance with requirements.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

The final report (70%) and short reports (30%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Students ought to spend at least 4 hours a week to keep up with the class for looking over slides before
lectures or consulting slides and references for reports.

Keywords（キーワード）

Data Compression, Data Processing, Pattern Matching, Indexing, Algorithms and Data Structures

Required Textbooks（教科書）

定兼 邦彦, 簡潔データ構造, 共立出版
岡野原 大輔, 高速文字列解析の世界――データ圧縮・全文検索・テキストマイニング, 岩波書店
Gonzalo Navarro, Compact Data Structures: A Practical Approach, Cambridge University Press

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

tomohiro@ai.kyutech.ac.jp

Course Name（科目名）

Introduction to Robust Control Theory

Instructor Name(担当教員名）

Noboru Sebe

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Robust control concerns the analysis and design of control systems that take into account the presence of
uncertainties, i.e., the unmodelled dynamics and/or unknown parameters. This course focuses on robust control
methodologies for linear
systems. Topics include: Signal and system norms and performance measures, robust stability and performance,
uncertainty modeling, structured uncertainty analysis and synthesis, and gain-scheduled control.
The purpose of thie course is to provide the students with the principles and tools of robust control theory:robustness, uncertainty, H-infinity norm, Linear matrix inequatlity, gain-scheduled control, descriptor systems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The students should have enough knowledge about the control theory based on the state space representation.
This class is a part of robust control modules.

Theme(テーマ）

Contents（内容）1. Introduction to robust control
2. Review of linear systems
3. Inportance of robust control
4. Descripton of uncertainties
5. H-infinity norm of systems
6. H-infinity control
7. Generalized plant
Course Calendar/Class Topic（授業計画）

8. Linear matrix inequality
9. Structured singular value
10. Robust performance
11. Gain-scheduled control
12. Parametric uncertaines
13. Descriptor representation

General Course Policies（授業の進め方）
CourseObjectives（授業の達成目標）

14. Analysis of descriptor systems
Controller design of descriptor
15.
systems
LectureIntroduction to Couse Objectives This class introduces concepts in optimal and robust control theory.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. The students should be able to characterize robustness and optimality of H-infinity control.
2. The students should be able to emply linear matrix inequality methos to analyze nad synthesize therobust control systems.
3. The students should be able to synthesize gain-scheduled control systems.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

100% - Homework/Assignments

Assignment Instructions（授業外学習（予習・復習）の指示）

The students are expected to prepare for this class more than 4 hours a week.

Keywords（キーワード）

Robust control, Uncertainty, H-infinity norm, Linear matrix inequality, Descriptor systems, Gain-scheduled
controlRequired Textbooks（教科書）

None

References/Recommended Reading（参考書）

K. Zhou, J. C. Doyle, and K. Glover, Robust and optimal control, Rentice Hall.
G.-R. Duan, LMIs in Control Systems: Analysis, Design and Applications, CRC Press.

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced Multimedia Representation

Instructor Name(担当教員名）

Tsukasa Noma

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course introduces representations and processing of multimedia data, e.g. images and sounds, with anemphasis on graphics, and then discusses their state-of-the-art techniques with students' presentation onlatest researches in multimedia.

Course Description（授業の概要）
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The prerequisite of the course is undergraduate-level knowledge of computer science. No expert knowledge of
media processing is required.
Theme(テーマ）

Contents（内容）1. Multimedia and its history
2. Multimedia data processing (4 classes)
3. Computer animation
Course Calendar/Class Topic（授業計画）

4. Virtual reality
5. Virtual human agent
6. Multimedia data translation and integration
7. Evaluation of multimedia systems

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

8. Paper presentation and critique (5 classes)
The course consists of two parts: The first part sketches principles of multimedia data processing. In thesecond part, students are responsible for presenting a recently published paper on multimedia and leading its
discussion.
The goal of this course is the understanding of basic representations and processing of multimedia. Students
are expected to:
1. Understand the features and basic processing techniques on multimedia
2. Master how to apply basic processing techniques to various types of multimedia data
3. Understand the outline of multimedia techniques in state-of-the-art applications

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

In the above objectives, all the items are evaluated with participation and attitude (40%) and paper presentationand discussion (60%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Following directions in the class, students should prepare paper presentation. It needs (and is worth) taking
sufficient time. The course will require 4 hours of prepraration work per week.

Keywords（キーワード）

multimedia, computer graphics, animation, virtual reality, virtual human agent

Required Textbooks（教科書）Lecture slides and additional materials are distributed.

References/Recommended Reading（参考書）

Reference materials are recommended as required.

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced Multimedia Engineering

Instructor Name(担当教員名）

Tsukasa Noma

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course introduces representations and processing of multimedia data, e.g. images and sounds, with anemphasis on graphics, and then discusses their state-of-the-art techniques with students' presentation onlatest researches in multimedia.

Course Description（授業の概要）
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The prerequisite of the course is undergraduate-level knowledge of computer science. No expert knowledge of
media processing is required.
Theme(テーマ）

Contents（内容）1. Multimedia and its history
2. Multimedia data processing (4 classes)
3. Computer animation
Course Calendar/Class Topic（授業計画）

4. Virtual reality
5. Virtual human agent
6. Multimedia data translation and integration
7. Evaluation of multimedia systems

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

8. Paper presentation and critique (5 classes)
The course consists of two parts: The first part sketches principles of multimedia data processing. In thesecond part, students are responsible for presenting a recently published paper on multimedia and leading its
discussion.
The goal of this course is the understanding of basic representations and processing of multimedia. Students
are expected to:
1. Understand the features and basic processing techniques on multimedia
2. Master how to apply basic processing techniques to various types of multimedia data
3. Understand the outline of multimedia techniques in state-of-the-art applications

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

In the above objectives, all the items are evaluated with participation and attitude (40%) and paper presentationand discussion (60%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Following directions in the class, students should prepare paper presentation. It needs (and is worth) taking
sufficient time. The course will require 4 hours of prepraration work per week.

Keywords（キーワード）

multimedia, computer graphics, animation, virtual reality, virtual human agent

Required Textbooks（教科書）Lecture slides and additional materials are distributed.

References/Recommended Reading（参考書）

Reference materials are recommended as required.

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Programming Languages and Systems I

Instructor Name(担当教員名）

Masahiro Yasugi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The course covers programming language topics such as syntax and semantics, the object-oriented paradigm,
and type systems. In addition, the course covers topics for programming language systems such as garbage
collection techniques, structures of language systems and compilers, and implementation techniques for parallellanguage systems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Students are expected to have some prior knowledge of the C programming language, compilers, parallel
computers. In addition, some prior knowledge of the Java programming language is helpful.

Theme(テーマ）

Contents（内容）Programming languages and virtual
machines
The object-oriented paradigm and2.
type systems
Garbage collection and weak3.
references
4. Garbage collection techniques
Structures of language systems and5.
compilers
Implementation techniques for6.
parallel language systems
7.
1.

Course Calendar/Class Topic（授業計画）

8.
9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15.
1 to 5 lectures on each topic are given. Remote lectures for fifteen times lectures are given in a combination ofasynchronous and synchronous styles. Live Zoom is used for answering questions. Moolde is used for providing
on-demand videos. Attendance checks are based on Moodle submissions. Students are required to submit

Introduction to Couse Objectives（授業の達成目標の解説）
1. To acquire the ability to understand and think the design of language specifications such as the objectoriented paradigm and type systems
2. To master the structure and implementation of programming language systems such as garbage
collection techniques and parallel language systems
3.

Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The evaluation is based on submitted reports (50%) and an examination (50%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Students are required to read course materials before every class. Students are required to write and submit
reports on some subjects. Students are required to reserve four hours a week for preparing classes.

Keywords（キーワード）

programming languages, the Java language, type systems, language systems, garbage collection, parallellanguage

Required Textbooks（教科書）

Course materials will be indicated during lectures.

References/Recommended Reading（参考書）

N/A

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced Course in Computer Vision I

Instructor Name(担当教員名）

Takahiro Okabe

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The aim of computer vision is to realize human visual system through computation. In this course, we study
computer vision, in particular 2D image processing, image pattern recognition, and 3D image processing fromtheir basic theories to applications.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This advanced course is related to the following ones: Advanced Course in Computer Vision II, Advanced Topics
in Image Processing, Advanced Course of Digital Image Processing, Video Image Processing, Advanced Course
in Pattern Understanding, Advanced Computer Graphics I, and Advanced Computer Graphics II.
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

Contents（内容）1. Digital image
2D image processing: color space2.
and tone curve
2D image processing: spatial
3.
filtering
2D image processing: frequency
4.
filtering
2D image processing: 2D geometric5.
transformation
2D image processing: segmentation
6.
and matching
7. Video image processing
Image pattern recognition: basic
8.
approaches
Image pattern recognition:
9.
supervised/unsupervised learning
3D image processing: geometric
10.
approaches
11. 3D image processing: stereo vision
3D image processing: photometric12.
approaches
3D image processing: inverse
13.
rendering
14. Computational photography
15. Summary
In addition to a term-end examination, some short tests are conducted. The slides for the classes are
distributed
Moodle.
The goals ofviathis
advanced course are as follows.
1. Understand the basic technical terms on computer vision
2. Understand 2D image processing
3. Understand image pattern recognition
4. Understand 3D image processing

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The achievement of the above goals is evaluated through the short tests (30%) and the term-end examination(70%).

Assignment Instructions（授業外学習（予習・復習）の指示）

The preparation for the classes, at least 4 hours per week, is required.

Keywords（キーワード）

2D image processing, image pattern recognition, stereo vision, inverse rendering

Required Textbooks（教科書）奥富 正敏 編「ディジタル画像処理[改訂第二版]」（CG-ARTS協会）

References/Recommended Reading（参考書）

石井 健一郎 他著「わかりやすいパターン認識」（オーム社）
徐 剛 他著「3次元ビジョン」（共立出版）
八木 康史 他著「コンピュータビジョン最先端ガイド1-6」（アドコム・メディア）

Notes（備考）
Email（電子メールアドレス）

okabe@ai.kyutech.ac.jp

Course Name（科目名）

Advanced Course in Computer Vision II

Instructor Name(担当教員名）

Takahiro Okabe

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The aim of computer vision is to realize human visual system through computation. The methodologies incomputer vision are classified into geometric approaches and photometric approaches; the former studies therelationship between the coordinates of 2D images and 3D scenes, and the latter studies the relationshipbetween the 2D images and the scenes description such as shape, reflectance, and illumination. In thisadvanced course, we study the photometric approaches in computer vision from their basic theories,
applications, and recent research trends with programming exercises.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This advanced course is related to the following ones: Advanced Course in Computer Vision I, Advanced Topics
in Image Processing, Advanced Course of Digital Image Processing, Video Image Processing, Advanced Course
in Pattern Understanding, Advanced Computer Graphics I, and Advanced Computer Graphics II.
Theme(テーマ）

Contents（内容）1. Measurement of light and color
2. Representation of light and color
3. Exercise 1
4. Image formation process
5. Image noise

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）
CourseObjectives（授業の達成目
標）Introduction to Couse Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

6. Exercise 2
Measurement and modeling of
7.
reflection
Measurement and modeling of
8.
scattering
Measurement and estimation of
9.
illumination
Shape recovery: shape from10.
shading
11. Shape recovery: photometric stereo
12. Exercise 3
Computational photography: light
13.
field
Computational photography: coded
14.
aperture/exposure
Computational photography: active
15.
illumination
Some reports are assigned. The slides for the classes are distributed via Moodle.
The goals of this advanced course are as follows.

1. Understand the basic photometric approaches in computer vision.
2. Understand the recent research trends in computer vision
3. Implement the basic algorithms in computer vision

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The achievement of the above goals is evaluated through the reports (100%).

Assignment Instructions（授業外学習（予習・復習）の指示）

The preparation for the classes, at least 4 hours per week, is required.

Keywords（キーワード）

Image formation process, image noise, reflection, scattering, illumination estimation, shape recovery,
computational photography, image quality improvement

Required Textbooks（教科書）The textbooks in References/Recommended Reading are recommended if necessary.

References/Recommended Reading（参考書）

コンピュータビジョン最先端ガイド4 八木康史，斎藤英雄 編（アドコム・メディア）
コンピュータビジョン最先端ガイド5 八木康史，斉藤英雄 編（アドコム・メディア）
ディジタル画像処理 奥富正敏 他編（CG-ARTS協会）

Notes（備考）
Email（電子メールアドレス）

okabe@ai.kyutech.ac.jp

Course Name（科目名）

Advanced Computer Graphics I

Instructor Name(担当教員名）

Tsukasa Noma

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）
Course Description（授業の概要）

Elective course
Credits（単位数）2This course introduces fundamental concepts and basic techniques of computer graphics. Graphics API
programming as well as the theoretical foundations of graphics are discussed.

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The prerequisite of the couse is mastery of elementary mathematical analysis, linear algebra, and programmingin C/C++.
Theme(テーマ）

Contents（内容）1. History and raster graphics
2. 2D graphics with OpenGL
3. 2D and 3D geometric transformations
4. Projection
5. Viewing pipeline
6. 3D graphics with OpenGL
7. Input and interaction
Course Calendar/Class Topic（授業計画）

8. Hidden surface removal
9. Shading
10. Shading in OpenGL
11. Shadowing and mapping
12. Global illumination and modeling
13. Curves and surfaces
14. Recent trends in graphics
15. Final exam

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

16. Final exam explanation
In addition to lecture, paper exercises are given in the class, and programming in OpenGL is assigned foroutside-class learning.
The goal of this couse is the understanding of the basics of computer graphics. Students are expected to:

1. Understand fundamental concepts of computer graphics
2. Understand mathematical foundations of computer grahpics and master their caluculation (by hand)
Develop graphics programs with OpenGL and understand the relationship between graphics concepts
3. and API specs

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

In the above objectives, all the items are evaluated with programming assignments (100%). As per request fromstudents, the first and second items may be evaluated with final exam (50%), and the third item with
programming assignments (50%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Paper exercises in the class are helpful to review. Programming assignments are worth for taking sufficient
time outside of class. The course will require 4 hours of preparation work per week.

Keywords（キーワード）

computer graphics, geometric transformation, projection, rendering, hidden surface removal, shading, modeling,
curves and surfaces, OpenGL

Required Textbooks（教科書）* Compute Graphics Editorial Committee(ed): Computer Graphics (new revised ed), CG-Arts Society (inJapanese)
Additional materials are distributed as required.

References/Recommended Reading（参考書）* Hughes, et al: Computer Graphics, Addison-Wesley* Rogers: Procedural Elements for Computer Graphics, McGraw-Hill* Shreiner, et al: OpenGL Programming Guide, Addison-Wesley

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Advanced electronic material engineering

Instructor Name(担当教員名）

Yoshikazu TERAI

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
In the current IoT society, various devices using electronic and optical materials are used. These devices aredeveloped by effectively utilizing the physical properties of electronic materials. The physical properties of eachelectronic material are mainly derived from its electronic structure. The electronic structure can be obtainedby first-priciple calculation. In this course, you learn the basics of first-principles calculation and thecalculation method using the code to understand the electronic structure of various electronic materials.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）In this course, students learn the basic physical properties of electronic materials and the methods of firstprinciple calculations. Basic knowledge such as quantum physics, solid state physics and semiconducting
physics is desirable, but explanations will be given as necessary.
Theme(テーマ）

Contents（内容）Introduction (What is MateriApps,
Quantum Espresso?)
Band calculation of Si (scf.in,2.
nscf̲band.in, band.in)
How to determine the calculation3.
conditions
4. Band calculation of Si, Ge, C
Band calculation of GaAs, GaN,
5.
ZnSe
Calculation of Charge density, Total
6. DOS and Partial
DOS of Si
Calculation of Phonon band and7. Raman, IR peak
positions of Si
Band structure, Fermi surface of Al,
8. Cu, and Spinpolarization of Fe
Calculation code using cif file using
9.
TiO2 as an example
Scf calculation with VC-relax and
10.
relax of latticeCalculation of band structure in11.
selected material
Calculation of TDOS and PDOS in
12.
selected material
Presentation of obtained results in13.
selected material
Presentation of the latest topics on
14. electronicmaterials (1): Electronic device
Presentation of the latest topics on
15. electronicmaterials (2): Optical device
This course will be taught in Japanese. The course materials are mainly given in English.
On-demand lectures (8 times) and face-to-face lectures (7 times) will be given according to the description of
the Moodle course. On-demand class attendance is confirmed by the submitting a report.
This lecture is aimed at learning in the field of physical and information engineering (C) Basic science ininformation science, electronic physics, and biotechnology. The goal is to acquire the basics of electronicmaterial engineering to achieve "having professional ability to use".
1.

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

1. Understand the basic properties and physical properties of semiconductors, dielectrics, magnetic
materials, and metals.
2. Understand the basics of first-principles calculation.
3. Make a first-principles calculation code and calculate the electronic structure of various electronicmaterials.
The report (50%) and presentation (50%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Before the class, the students should a preparatory study for 4 hours a week.

Keywords（キーワード）

Semiconductor, dielectric, magnetic material, metal, device, first-principles calculation

Required Textbooks（教科書）

Nothing special. We distribute necessary materials as needed.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

terai@cse.kyutech.ac.jp

Course Name（科目名）

Advanced Course on Microelectronic Systems

Instructor Name(担当教員名）

BABA Akiyoshi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This class will provide education on both a semiconductor microfabrication technology and a fabrication of
three-dimensional intelligent microsystems that fuse micromachines and microelectronics.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The purpose of this lecture is to introduce specialized education to train engineers related to intelligent
sensors that integrate micromachines and microelectronics. The main purpose of this lecture is to deepen theunderstanding of the expertise in micromachining technology required for these engineers. It is desirable, but
not required, to take the following undergraduate courses or have equivalent knowledge.
Contents（内容）Theme(テーマ）1.

Position of micromachining in theentire productLecture on positioning of microfabrication from the perspective of
microdevice products such as LSI and MEMS

2.

Processing technology(classification by size)

Lectures on size effects of physical quantities and the relationshipbetween size effects and processing methods.

3. Substance and Energy

Lectures on the concept of matter and energy to understand theions and radicals used in microfabrication.

4.

LSI processing technology (planar
technology)

5. Film growth / deposition

Course Calendar/Class Topic（授業計画）

6. Photolithography

Lecture on photolithography techniques used in planar technology

7. Etching

Lecture on the types and characteristics of etching and etching
methods in specific situations

8. Doping and substrate cleaning

Lecture on the outline of doping technology and substrate cleaning
technology, equipment principle, and process

9. MEMS technology

Lecture while comparing the features of MEMS technology with LSI
technology (planer technology)

10. Specific MEMS technology
11. Process integration
12. Process margein
13.

Fusion technology of LIS andMEMS

14. 3D LSI
15. Explanation of report issues

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Lecture on planar technology used in LSI fabrication, a
representative of microfabrication
Lectures on CVD method, sputtering method, and spin coating
method, which are important film deposition methods in LSI
manufacturing.

Lecture on MEMS-specific technologies, application methods, andapplicable devices
Lecture on the outline of integration technology, which is acombination of elemental technologies, and the integration
technology of specific microdevices.
Lectures on process margins in LSI and MEMS technologies foreach major process, and lectures on the impact on final yield.
Lecture on how to integrate MEMS technology and LSI technology(planar technique)
Lecture on 3D LSI fabrication technology as an example of a fusion
device of MEMS technology and LSIM technology (planer
technology)
Explain the reporting issues related to process integration

14 lectures + 1 explanation of report assignment. Since the lecture materials will be distributed in advance, it isnecessary to prepare for the lecture contents and consider the questions. Also, take revenge because you will
be asked questions about points you did not understand in the previous lecture.
This lecture aims to achieve the following points.
1. Understand semiconductor microfabrication technology.
2. Understand MEMS technology.
3. Understand the fusion technology of MEMS technology and semiconductor fine processing technology.

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

Evaluate grades on the following two tasks
・ Assignments given after each lecture: 2 points x 15 times (30 points in total)
・ Report assignment on process integration after the lecture: 70 points

Assignment Instructions（授業外学習（予習・復習）の指示）

At the end of the lecture, we will inform you of the next lecture schedule. Read and prepare for the materials
corresponding to the schedule. Also, review the content of the lecture and be prepared to ask questions before
the next week's lecture or by email. As a preparatory study (preparation), secure at least 4 hours a week.

Keywords（キーワード）

Semiconductor microfabrication, micromachining, microsensor, microsystem

Required Textbooks（教科書）Prepare PDF files as materials for lectures. It will be distributed before the lecture starts.

References/Recommended Reading（参考書）

・ Semiconductor Device 2nd Edition Basic Theory and Process Technology, S.M.G.
・ Basic of latest VLSI, written by Yuan Taur et al., Translated by Takeuchi Kiyoshi et al., Maruzen
・ Physics of Semiconductor Devices 3rd ed., S.M.Sze and K.W.Ng, Willey
・ ULSI Technology, C.Y.Chang and S.M.Sze, McGraw-Hill

Notes（備考）

MoodleコースURL
https://ict-i.el.kyutech.ac.jp/course/view.php?id=2884

Email（電子メールアドレス）

baba@cms.kyutech.ac.jp

Course Name（科目名）

Advanced Science for Nanodevices

Instructor Name(担当教員名）

Professor Yoshihito Maeda

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
In this course, we will give lectures on typical device applications from the foundation about new physicalphenomena coming from the quantum mechanical behavior of electrons, spins, phonons and photons playing apart in advanced nanodevices.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This subject is closely related to the subjects as follows; "Advanced Semiconductor Engineering", "Advanced
Materials for Functional Materials", Graduate School of Advanced Information Science and Technology, and it is
the content which developed them. It is desirable that you have acquired basic physics such as "Modern
physics I", "modern physics II", "electromagnetism", "electronic physics", "solid physics / solid physicalproperties", "quantum mechanics" Explain of them will be given as necessary.
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

Contents（内容）1. Outline

What happens in mesoscopic region?

2. Physics in mesoscopic region

Basics on Electrical conduction, Ballistic conduction and diffusion ofelectron

3. Physics in mesoscopic region

Landauer's conduction law and Buettker foumulas.

4. Physics in mesoscopic region

Magnetoresistance effect, Quantum Hall effecct

5. Electronic properties

Electronic states in solids, Bloch states

6. Electronic properties

Physical processes involving electron waves, Band structure in solids

7. Single Electronic phenomena

Coulomb brokade, tunneling effect

8. Single Electronic phenomena

Single electron transitor and its opreration

9. Semiconductor nanostructures

Qunatum structures, and quantum states of electron

10. Semiconductor nanostructures

Two dimensional electron gases, High electron mobility transistor (HEMT)

11. Semiconductor nanostructures

Quantum confimement effects, optical properties and their applications

12. Practical study

Practical study using related manuscripts in English

13. Practical study

Practical study using related manuscripts in English

14. Practical study

Practical study using related manuscripts in English

Practical study using related manuscripts in English
15. Practical study
Online Lecture by zoom meeting is carried out in a typical seminar style. We will impose a report task tomeasure its comprehension level. In the lecture, they are mainly conducted in English, and are advanced inconsideration of students acquiring English technical terms. We will promote students' understanding byquestion-and-answer / discussion and let them understand essential concepts and research cases on
nanodevice science. In addition, let us learn the current state and future of nano world by related video viewing.
Make reading and summarize specialized English academic journals, and acquire technical terms and syntax. We
welcome foreign students who have a strong interest in nano-scale devices and their science.
In this lecture, deepen the basic knowledge of the knowledge and technology of electronic engineering,

CourseObjectives（授業の達成目
標）Introduction to Couse Objectives information engineering, computer network (information communication) which is a common learning educationalgoal, and acquire expertise on application. (C-1) Achieve the following matters concerning deepening of（授業の達成目標の解説）
knowledge on electronics and nurturing of applied academic ability.
Students can understand and explain the characteristic physical phenomena and conduction in the
1. mesoscopic system.
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Students can understand and explain the physical phenomenon expressed in semiconductor
2. nanostructures and the principle of device operation using it.
3. Students can comprehend the relevant English scientific papers by reading, and can summarize thecontents, and also acquire technical terms.
Comprehensive evaluation of the results by grading the report (60%) on items (1) (2) and the reading summary(40%) of English academic papers on item(3).

Prestudies each for 1-2 hours are recommended.

Keywords（キーワード）
Required Textbooks（教科書）

Mesoscopic system, nanotechnology, devices, nanoscaled materials science, nanomaterials, semiconductor
quantum structures
Nothing in particular about a text book. During the lecture, materials and prints necessary for preparation /review will be distributed as appropriate. Corresponding moodel course offers professional slides necessary forstudy and articles for execise.

References/Recommended Reading（参考書）

J. H. Davies: The Physics of Low-Dimensional Semiconductors (Cambridge Univeristy Press, Cambridge, 1998)

Notes（備考）This course will be given in online zoom meeting, not a face-to face lecture.
Professors academic backgroud may be known from Google Scholar:
https://scholar.google.com/citations?user=WJCqqz8AAAAJ&hl=en&oi=ao

Email（電子メールアドレス）

maeda@cse.kyutech.ac.jp

Course Name（科目名）

Advnaced Applied Superconductivity

Instructor Name(担当教員名）

Edmund Soji OTABE

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The superconductivity phenomenon has the ideal property with no electrical resistance, while it is a nonlinear
giant quantum phenomenon such as the Josephson effect. Taking advantage of such specialty, it is applied to
power application equipments suitable for energy saving, medical equipment such as MRI, analog devices forcommunication, SQUID (superconducting quantum interferometer), and quantum computing. In this course, wewill study physics such as diamagnetism, condensation energy, quantum effect, and Josephson effect, which are
the basis of the superconductivity phenomenon.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Superconductivity is a phenomenon related to thermodynamic phase transition, but it is basically a giant
quantum phenomenon. Hence, it is requred the basic skills of "thermodynamics", "quantum mechanics","electromagnetism". In addition, it is preferable to have knowledge of physical properties such as free electron
theory, because the difference from ordinary metals is discussed. Therefore, in order to take this course,
students must take courses in the following faculties (keywords in parentheses). ̀̀ Modern physics I '' (wave
equation, uncertainty principle, eigenvalue, expected value) ̀̀ Basic physics IIE '' (thermodynamic law) ̀̀Electromagnetics I ・ Seminar '' Study II (Superconductors, Magnetic Energy, Electromagnetic Induction) By
completing this course, you will be able to acquire the basic knowledge of superconductivity phenomena
necessary to complete the Special Course in Applied Superconductivity .
Theme(テーマ）

Contents（内容）Basics of superconductivity
1. (perfect conductivity, perfectdiamagnetizm)
Types of superconductors (Type 1
2.
and Type 2)
3. Energy gap
4. Superconducting electronic state
5. London theory
6. Ginzburg-Landau theory
Course Calendar/Class Topic（授業計画）

7. Quantization of magnetic flux
Type 2 superconductor and upper
8.
critical magnetic field
9. Josephson effect (DC, AC)
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15.
Lectures on the above items will be given mainly in textbooks, and necessary lectures on analytical mechanics,
quantummechanics,
electromagnetics,
and thermodynamics
be given separately.
This
lecturebelongs to
the Electronic Properties
Module, andwill
is expected
to be applied to a wide range of fields

Introduction to Couse Objectives such as electronics in order to achieve one of the learning and educational goals in the electronics field (1)"Development of advanced technologies in the electronics field". The goal is to learn the basics of（授業の達成目標の解説）
superconductivity engineering. In particular,
Couse objectives(具体的な授業の達成目標）

1. 1. Understand the analysis and quantum mechanics, electromagnetism, and thermodynamics that are thefoundations of modern physics, and understand Ginzburg-Landau theory describing superconducting
2. 2. Understand the essence of various unusual physical phenomena exhibited by the superconducting
state, such as the magnetic flux quantization and Josephson effect.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Since the purpose is not to absorb fragmentary knowledge, a test that gives answers in a short period of time
does not fit in grade evaluation. Here, some tasks are assigned within the scope of the lecture, and the results
are submitted as a report within the deadline and evaluated.

Assignment Instructions（授業外学習（予習・復習）の指示）

Report will be giving assignments in a lecture, it is necessary to prepare materials for the next lecture.
4 hours a week is required as a preparatory study.

Keywords（キーワード）

Superconductivity, perfect diamagnetism, energy gap, Ginzburg-Landau equation, quantized magnetic flux, type
2 superconductor, Josephson effectRequired Textbooks（教科書）

Teruo Matsushita, Flux Pinning in Superconductors (Springer Series in Solid-State Sciences) 2014

References/Recommended Reading（参考書）

Notes（備考）
Email（電子メールアドレス）

otabe@cse.kyutech.ac.jp

Course Name（科目名）

Advanced Computer Systems Ⅱ

Instructor Name(担当教員名）

Akihiro FUJIWARA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The course consists of a series of sessions on the followings.
1. Theoretical evaluation of the algorithms.
2. An overview, basic techniques and evaluations of algorithms for parallel and distributed processing.
3. Recent topics for parallel and distributed processing.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is designed to provide an introduction on the theory of parallel and distributed processing.
Basic knowledge for the algorithm is needed.

Theme(テーマ）

Contents（内容）1. An introduction on algorithms and complexity
2. An overview of parallel processing
3. Complexity of a parallel algorithm
4.

Basic techniques for parallel algorithms 1 (divide-and-conquer anddata parallel processing)

5. Basic techniques for parallel algorithms 2 (work-pool approach)6.

Recent topics for parallel and distributed processing 1 (Quantum
computing)

7. Middle exercise
Course Calendar/Class Topic（授業計画）

8. An overview of distributed processing
9. Basic distributed algorithms 1 (leader election)
10. Basic distributed algorithms 2 (logical and vector clocks)
Recent topics for parallel and distributed processing 2 (DNAcomputing)
Recent topics for parallel and distributed processing 3 (Membrane
12.
computing)
Recent topics for parallel and distributed processing 4
13.
(Blockchain)
11.

14. Final exercise

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15. Exam
The lecture is a hybrid of in-person classes and remote classes.
For the in-person class, materials for the lecture are distributed electrically.
For the remote class, videos and exercises are prepared in advance, and attendance of the lecture is recorded by solving the exercise.
The final exam is a written examination.
The basic objectives of the lecture are understanding and acquiring knowledges for algorithms in parallel and distributed processing.
1. Understanding for models and basic algorithms in parallel processing
2. Understanding for models and basic algorithms in distributed processing
3. Acquiring deep knowledges for recent topics in parallel and distributed processing

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Score is evaluated according to two report assignments (20%) and the final exam (80%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Materials is distributed using Moodle.
Preparation for 4 hours per week is needed.

Keywords（キーワード）

parallel and distributed processing, algorithms

Required Textbooks（教科書）

none

References/Recommended Reading（参考書）

none

Notes（備考）
Email（電子メールアドレス）

fujiwara@cse.kyutech.ac.jp

Course Name（科目名）

Vacuum technology on semiconductor

Instructor Name(担当教員名）

SHINKAI Satoko

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This class will be given on the fabrication of next-generation semiconductor devices that apply new materials
and new process technologies to device manufacturing process. In particular, it will explain in detail the handlingof vacuum tools that is indispensable for semiconductor manufacturing.

Course Description（授業の概要）

The vacuum technology will be explain in the field of semiconductor manufacturing technology.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）Contents（内容）1. characteristics of gas

characteristics of gas

2. chsracteristics of gas

characteristics of gas

3. chsracteristics of gas

vacuum technology

4. chsracteristics of gas

Maxwell-Boltzmann

5. chsracteristics of gas

Adsorption equilibrium

6. chsracteristics of gas

Adsorption equilibrium

7. vacuum tools

vacuum pump

8. vacuum tools

vacuum pump

9. vacuum tools

conductance

10. vacuum tools

vacuum materials

11. vacuum tools

leak detection

12. vacuum tools

vacuum gauge

13. vacuum tools

vacuum gauge

14. vacuum tools

How to measure vacuum

summary
15.
This class will be used video. You have to downroad PDF document from moodle. The number of lectures will be
15 times. In this class, you will be evaluated by your reports.

Introduction to Couse Objectives This class aims to understand the principles of vacuum technology. You have to work on your studies 4 hours aweek.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）"Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）"

1. Understand the relationship between vacuum and gas.
2. Understand the relationship between vacuum pumps and gauges
3. Understand the desigh of vacuum tools.
Evaluate in the report. (100%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Understand the content of the vacuum technology well and review it thoroughly.

Keywords（キーワード）

vacuum, semiconductor, process, manufacturing, gas

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Notes（備考）
Email（電子メールアドレス）shinkai@cms.kyutech.ac.jp

Course Name（科目名）

Advanced Lecture on Wireless Mobile Networks

Instructor Name(担当教員名）

TSUKAMOTO Kazuya

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2With the recent development of various user terminals such as smartphones, sensors, and vechicles, a variety
of wireless moible networks including ad-hoc network is built, thereby providing diverse wireless services.
In this course, Instructor explains the design policy and behavior of system and communication protocol working
on these networks. Also, recent ternds of wireless communication technologies including cognitive radio isinvestigated to understand the desing policy for the next wireless communication systems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course assumes that the studensts take courses of "Network communication basic" and "Networkarchitecture" (subjects of Department of Computer Science and Electronics) and their related subjects.
Furthermore, to deeply understand the information communication network, taking of "advanced network
management" and "Advanced lecture on network design" is recommended in addition to this courese.
Theme(テーマ）

Contents（内容）1.

Introduction of wireless mobile
network

Introduce the latest trend of wireless mobile network

2.

Introduction and explanation of
allocated tasks and papers

Introduce the duties for each students and explain the allocated paper

3.

Changes in wireless mobile network(mobility, wireless, multi-home)4.

Overview of wireless mobile
network

5.

Mobility management protocol (e.g.,
Mobile IP)

6. Trends of sensor networks
7. Trends of cognitive radios
Course Calendar/Class Topic（授業計画）

8.

Edge network platform for crossdomain data fusion

9.

Preperation for presentation anddiscussion (I)10.

Preperation for presentation anddiscussion (II)11. Presentation (I)12. Presentation (II)13.

Presentation (III)-backup andpreperation for final report

14. Submission of final report
15. Wrap-up meeting

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

Until 10th class, the instuctor explain in the lecture style. After that, the students need to hand in reports andhave a presentation. In this cource, the expers from other organization including universties and companies areinvited as the external instructor.

In this course, to understand the concrete realising way of the advanced mobile network (one of the course
Introduction to Couse Objectives objectives of computer science), the goal is to acquire basic knowledge about the current status of wireless（授業の達成目標の解説）
mobile networks and their future trends.
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

1. Understanding the history and status of wireless mobile network
2. Understanding the system architecture and communiation protocol of wireless mobile network
3. Understanding the world trends of research and development of wireless mobile network
Evaluates grades with reports by individual submittion and group presentations. About reports andpresentations, materials submitted before the deadline will be evaluated. Regarding presentations, presentationmaterials and Q & A sessions will also be evaluated. After the presentation, reports will be evaluated, finally.

Assignment Instructions（授業外学習（予習・復習）の指示）

Lecture materials will be uploaded to moodle in advance, so download and print them before the lecture andbring them to the lecture. You can download it to your laptop or tablet device and listen to the lecture, or
prepare to take notes for necessary items. Be sure to read the materials before the lecture (preparation) andtake notes as needed during the lecture. After the lecture, review the content, and then examine the English
papers related to the lecture content for each group determined in advance, summarize the content, and report
it in a report and presentation.
Finally, consider the relationship between the textbooks and the contents that you have individually understood,
and then report them. In doing so, review the contents of the lecture and consider future directions from a
broad perspective based on the information obtained from the textbooks.

Keywords（キーワード）

Wireless mobile network, cellular network, WiMAX, mobility management, Wi-Fi Direct, sensor network, vehicular
network, cognitive radio

Required Textbooks（教科書）

Tsukamoto Kazuya, http://www.kyoritsu-pub.co.jp/bookdetail/9784320009158

References/Recommended Reading（参考書）
Notes（備考）This lecture is a remote learning course using Zoom and Moodle.

Email（電子メールアドレス）

tsukamoto@cse.kyutech.ac.jp

Course Name（科目名）

Advanced Organic Electronics

Instructor Name(担当教員名）

Shuichi NAGAMATSU

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
In this lecture, students will learn the basics of optoelectronic properties of organic semiconductor moleculesand conductive polymers and device physics based on knowledge of inorganic semiconductors. Students will
also read relevant English academic papers and discuss the background of organic electronics and future
developments.
This lecture belongs to the Electronic Materials Module and deals with basic physical properties and device
physics of organic semiconductor materials, which is one of the next generation semiconductor materials.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Contents（内容）1. Basis of Semiconductor Devices
2. Organic Semiconductor Materials
3. Conjugated Polymers
4. Organic Light-emitting Diodes
5. Organic Photovoltaics
6. Organic Transistors
Course Calendar/Class Topic（授業計画）

7.
8.
9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15.
a seminar format
This lecture aims to achieve the learning / educational goals in the field of electronics and informationengineering (1) Development of advanced technologies in the field of electronics in order to achieve the next
generation electronics technology with features such as printed flexible wearables. The goal is to learn thebasics of electronics.
1. understandings for optoelectronics properties of organic semiconductor molecules
2. understandings for basics of device physics of organic semiconductor
3. understandings for English papars in field of Organic Electronics

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

attendance and reports

Assignment Instructions（授業外学習（予習・復習）の指示）

4 hours a week for a preparatory study.

Keywords（キーワード）

organic semiconductor, conjugated polymers, device physics

Required Textbooks（教科書）

none

References/Recommended Reading（参考書）

Organic Semiconductor Devices

Notes（備考）
Email（電子メールアドレス）

nagamatu@cse.kyutech.ac.jp

Course Name（科目名）

System Design

Instructor Name(担当教員名）

Jun Kobayashi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deals with a method for devising a system by design thinking, idea sketching, and prototyping. It
enhances the development of students' skill in system design and digital fabrication.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

By taking this course, you can acquire the ability to design systems on the basis of your knowledge about"electrical and electronic circuits" and "control theory" that you have learned in your undergraduate school. It
is desirable that you have completed subjects related to "Electrical and Electronic Circuits" and "Control
Theory ; however, the required minimum knowledge will be taught in this class.
Theme(テーマ）

Contents（内容）1. Guidance
2. Drawing for creation
3. Physical Computing 1
4. Physical Computing 2
5. Physical Computing 3
6. Idea Sketching
Course Calendar/Class Topic（授業計画）

7. Design Thinking 1 (quick review)
8. Design Thinking 2 (quick review)
9. Design Thinking 3
10. Prototyping 1
11. Design Thinking 4
12. Prototyping 2
13. Design Thinking 5
14. Prototyping 3

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15. Test & Presentation
This class will be conducted both remotely and face-to-face using Moodle and Zoom. Students will devise asystem, make a prototype, and give a presentation about their system. Attendance will be checked using Zoom
and Moodle. In the last class, an exam will be given remotely using Zoom. This course will be taught in English.
Students are required to discuss in English.
By the end of the course, students should be able to do the following:
1. Describe and explain process of design thinking and idea sketching
2. Describe the mechanism of digital machine tools and use them
3. Make a prototype of a system they devised
4. Exchange constructive opinions and idea with team members

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Your final grade will be calculated according to the following process: Presentation (60%), Evaluation by teammembers (20%), and test (20%).

Assignment Instructions（授業外学習（予習・復習）の指示）

You must spent 4 hours a week for preparatory learning.

Keywords（キーワード）

Design Thinking, Idea Sketching, Prototyping, Digital Machine Tools

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Notes（備考）You need to bring your own laptop every time. You also need to buy and bring an ESP32 development board.
We will organize teams at the first session. Therefore, it is not acceptable to join the class from the second andsubsequent sessions. If you can not attend the first session, please contact with me in advance. The maximum
number of students is 12 due to the limited classroom space. If there are applicants more than 12, we will
select the students by negotiation or in a lottery.

Email（電子メールアドレス）

jkoba@ces.kyutech.ac.jp

Course Name（科目名）

Robustness and stability of dynamical systems

Instructor Name(担当教員名）

Hiroshi Ito

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The concepts of stability and robustness are two major tools for dealing with dynamical systems . This course
focuses on them in view of both internal and external behavior. The emphasis is on mathematical concepts andformulations which are applicable to both nonlinear and linear systems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course covers materials which are based on fundamental concepts in classic and modern control theory.
Knowledge on them will greatly help learners. Differential equations, linear algebra, Fourier series and Laplacetransform are the mathematical basis of this course. .
Theme(テーマ）

Contents（内容）1. Dynamical systems
Linearity and nonlinearity of2.
dynamics
Solutions to system equations and3.
their characteristics
4. Estimation of system solutions

Course Calendar/Class Topic（授業計画）

5. General formulation of contraction
Equilibria, invariant sets and limit
6.
cycles
7. Internal stability
8. Dissipativity
9. Input-output characterization
10. Lyapunov functions
11. Stabilizability and detectability
12. Stability of interconnected systems
13. Robust stability
14. Robust performance

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15. Stabilization and robustification
This course will be given in the lecture format. Communication with students through exercise assignments
during classes will bridge the gap between theory and real word phenomena , and it helps the students
understand abstract and mathematical formulations of dynamics . Students are asked to take notes including
their own thought they go through during the exercises. The notebooks will be submitted along with the final
assignment.
Learning tools for characterization and analysis of dynamical systems is the major objective. It allows one toacquire basic knowledge's needed for designing dynamical systems supporting and developing modern societies
and technologies.
1. Understanding the concept of stability and being able to apply it appropriately
2. Analyzing and compensating dynamical systems through appropriate characterization
3. Understanding robustness concepts and using them to analyze and design dynamics

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Grading is based on performance of homework assignments (100 per cent).

Assignment Instructions（授業外学習（予習・復習）の指示）

Note-taking is essential. Students are advised to read handouts before lectures and review them and theirnotebooks carefully. The minimum of four hour study at home is necessary each week.

Keywords（キーワード）

Linear systems, Nonlinear systems, Dynamics, Stability, Robustness, Equilibria, Feedback control, Control
theoryRequired Textbooks（教科書）

Handouts will be distributed.

References/Recommended Reading（参考書）

Information will be given in class.

Notes（備考）
Email（電子メールアドレス）

Course Name（科目名）

Stochastic Numerics

Instructor Name(担当教員名）

Yoshio Komori

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deals with numerical methods for stochastic differential equations (SDEs). SDEs can describe
physical phenomenon, in which we have to consider random effects, such as in bio-chemical reactions.
However, in many cases we cannot solve them analytically. Thus, we need numerical methods for them, and infact, such methods have been studied and have been developed in the recent thirty years. In this course, westart from the introduction to SDEs, and have numerical methods for SDEs. In the end, students will be
required to write program codes for the methods and carry out simulation.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Students who want to take this course, will be expected to have fundamental knowledge about probability,
stochastic processes, differential equations, and numerical analysis. However, they do not need to haveadvanced knowledge about all of them. Corresponding to a situation, supplemental explanations will be given to
the students.
Contents（内容）Theme(テーマ）1.

Introduction, probability and random (Contents are clearly indicated by the title in each theme)
variables

2.

limit theorems, stochastic
processes

3.

Stochastic integrals and Ito
Theorem

4. Stochastic differential equations
5. Numerical methods for SDEs
Course Calendar/Class Topic（授業計画）
6.

Applications of SDEs, stochastic
stability

7.
8.
9.
10.
11.
12.
13.
14.
15.
In addition to lectures about the subjects, exercises or reports can be required.
General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

We aim at a level in which students can numerically solve SDEs for applications. For this, our course objectives
are as follows:
1. Students understand basic theories related to SDEs.
2. Students can write program codes to implement numerical methods for SDEs.
3. Students can carry out numerical simulations related to SDEs.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Students are required to submit reports. In the reports, the following are checked mainly: 1) description about
subjects, 2) investigation about subjects, 3) understanding about subjects, 4) how well organized reports as awhole.

Assignment Instructions（授業外学習（予習・復習）の指示）

After each lecture, it would be better for students to check their understanding of the lecture by reading theirnote and the materials handed out. It might takes approximately one hour, but it depends on students.

Keywords（キーワード）

Stochastic differential equation, numerical method, approximation, numerical stability, stochastic Runge--Kutta
method.

Required Textbooks（教科書）Students do not need to buy a text. Prints will be handed out.

References/Recommended Reading（参考書）

Gard, T.C. (1988), Introduction to Stochastic Differential Equations, Marcel Dekker.
Kanekiyo, Y. (2017), Stochastic Differential Equations and its applications, Morikita (in Japanese).

Notes（備考）
Email（電子メールアドレス）

komori@ces.kyutech.ac.jp

Course Name（科目名）

Advanced Optical Systems and Applications

Instructor Name(担当教員名）

Masanori Takabayashi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Lectures on expert knowledges and hot topics about optical systems and applications which are widely used in
our life are given. Especially, we provide explanations to understand the relationships between expert
knowledges on optics and how to apply them in our life by focusing on familiar applications such as optical
recording, optical communication and optical imaging systems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course belongs to Applied Optics Module. Having the knowledge on optics and electromagnetics is
encouraged, but it is not strictly required.

Theme(テーマ）

Contents（内容）1. Overview

Course Calendar/Class Topic（授業計画）

2. Wave optics (1)Wave equation, Plane wave, Spherical wave

3. Wave optics (2)Diffraction, Wave propagation, Fourier transformation by lens

4. Holography (1)Fundamental of holography, Volume holography

5. Holography (2)Digital holography, Computer generated holography

6. Optical information processing (1)Imaging optics

7. Optical information processing (2)Optical filtering

8. Optical memory (1)History and principle of conventinal optical memory

9. Optical memory (2)Recent progress of optical memory

10. Optical communication (1)History and principle of conventinal optical fiber communication

11. Optical communication (2)Recent progress of optical fiber communication

12. Optical imaging (1)History and principle of conventional optical microscope

13. Optical imaging (2)Recent progress of optical microscope: nonlinear optical
microscope

14. Optical imaging (3)Recent progress of optical microscope: quantitative phase imaging

15. Summary

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

If a face-to-face class is available, it will be conducted in a face-to-face lecture format.
If a face-to-face class is not possible, the class will be conducted in an on-demand format (asynchronous).
In this case, lecture materials and videos will be uploaded before the lecture date, and attendance will be
confirmed by a mini-quiz.
To understand fundamental of optics and how optics is applied for optical applications used today.
1. To understand fundamental of wave optics.
2. To understand history and principle of conventinal optical memory and recent progress.
3. To understand history and principle of conventinal optical communication and recent progress.
4. To understand history and principle of conventinal optical imaging and recent progress.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

20%: Homework, 80%: Final report

Assignment Instructions（授業外学習（予習・復習）の指示）

Download and read lecture materials in Moodle, and look up words in references. 4 hours/week should be
set for preparation.

Keywords（キーワード）

Wave optics, Fourier optics, Holography, Optical memory, Optical communication, Optical imaging

Required Textbooks（教科書）

Not specified.

References/Recommended Reading（参考書）

Yoshimasa Kawata, "Beginner's Guide to OPTICS," Kodansha (2014). (in Japanese)
J. W. Goodman, "Introduction to Fourier Optics, Third Edition," Roberts & Co. Publishers (2005)

Notes（備考）
Email（電子メールアドレス）

takabayashi@ces.kyutech.ac.jp

Course Name（科目名）

Advanced Optical Physics

Instructor Name(担当教員名）

OKAMOTO Takashi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This lecture provides the basis of high-speed, high-precision optical wave sensing technology, which occupies
an important position in various measurement technologies. The mechanism of the laser, the operation methodof light, and various interference measurement methods are described in an orderly manner. Some application
examples will be presented to deepen understanding of the methods.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course belongs to the optical application module and relates to the measurement application of laser
technology. Therefore, it is desirable that there is basic knowledge about light and electromagnetic waves, but
not necessarily essential. The subjects related to this lecture include physical subjects such as
electromagnetics and optics.
Theme(テーマ）

Contents（内容）1. Orientation
2. Basics of lasers
3. Interaction of light and atoms
4. Optical resonators
5. Coherence of light
6. Basic properties of light
Course Calendar/Class Topic（授業計画）

7. Manipulation of light
8. Fundamentals of interferometry
9. Methods for improving accuracy
10. Holographic measurement
11. Laser speckle measurement
12. Laser Doppler measurement
13. Scattering of light
14. Biological measurement

General Course Policies（授業の進め方）
CourseObjectives（授業の達成目標）

15. Summary
Lecture-based teaching

Introduction to Couse Objectives This lecture aims to understand the basic properties of laser light and the principles of various measurement
methods using lasers.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. To understand the mechanism of laser systems
2. To understand the principles of interferometry and interferometric measurements
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Evaluate the final report submitted at the end of the course

Assignment Instructions（授業外学習（予習・復習）の指示）

Give an assignment for each class.

Keywords（キーワード）

laser, interferometry, holography, speckle, Doppler effectRequired Textbooks（教科書）
References/Recommended Reading（参考書）

Yariv, Optical Electronics, Oxford University Press

Notes（備考）
Email（電子メールアドレス）

okamoto@ces.kyutech.ac.jp

Course Name（科目名）

Optimization Algorithms

Instructor Name(担当教員名）

Eiji Miyano

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Many optimization problems in Computer Engineering, Computer Science and System Engineering has the discrete
structures and thus they often are formalized as "combinatorial" optimization problems. Recently, the size of data
and/or information is increasing. Thus, to processing and/or deal with the large amount of information, it is important toacquire the knowledge of the standard algorithm design paradigms and efficient data structures. This course develops
standard techniques use in the design and analysis of algorithms, with an emphasis of problems in combinatorial
optimization problems arising in computing applications. Example applications are drawn from graph/network problems,
artificial intelligence, combinatorial geometry, computational biology and so on.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course belongs to "Algorithm design" and "Optimization" modules. This course is concerned with issues that arisein the design for solving combinatorial optimization problems. The prerequisite include courses in discrete mathematics,
discrete structures, the design of simple algorithms, basic data structures, and computational complexity.
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）Contents（内容）1. Introduction
Asymptotic notation and analyzing time2.
complexity
Review on designing and analyzing3.
algorithms
4. Review on data structures

Course guidance

5. Review on computational complexity
Combinatorial optimization problems and6.
approximation
7. Designing approximation algorithms (1)polynomial time solvability, NP-completeness, NP-hardness

8. Designing approximation algorithms (2)dynamic programming

9. Designing approximation algorithms (3)LP-base algorithms, LP-relaxation

10. Designing approximation algorithms (4)primal-dual algorithms

11. Online computation model
Competitive ratio and designing online
12.
algorithms
13. Designing randomized algorithms

online computational model

14. Designing parallel algorithms

parallel algorithms

Big O, big Omega, small o, small omega, Theta-notations
simple algorithm design techniques
basic data structures

Combinatorial optimization problems and approximation
greedy algorithms, local search algorithms

competitive ratio, online algorithms
randomized algorithms

15. Conclusion
Online video/slide classes (mostly), face-to-face classes (several times), and zoom classes (several times)

Upon completion of this course, students will be able to do the following: (1) Analyze the asymptotic performance ofIntroduction to Couse Objectives algorithms and demonstrate a familiarity with major algorithms and data structures. (2) Apply important algorithmic
design paradigms and methods of analysis. More concretely, students who complete the course will have demonstrated（授業の達成目標の解説）
the ability to do the following:
Couse objectives(具体的な授業の達成目標）

1. Formalize engineering applications as combinatorial optimization problems
2. Describe the approximation, online, randomized, and parallel algorithm paradigms.
3. Design and analyze efficient algorithms for combinatorial optimization problems.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Class attendance, discussion and quizzes (20 - 30%). Mid and final reports (70 - 80%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Students have to find at least four hours for preparation/review of classes in a week.

Keywords（キーワード）

combinatorial optimization problems, algorithm design, data structures

Required Textbooks（教科書）We will not follow a single textbook as is fairly common with graduate-level courses. The lecture slides will bemain resources.

References/Recommended Reading（参考書）(1) T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein. Introduction to Algorithms, 2nd Ed., MIT Press.
(2) J. Kleinberg and E. Tardos. Algorithm Design, Addison Wesley.
(3) M.R. Garey and D.S. Johnson. Computers and Intractability, W.H. Reeeman and Company.
(4) V.V.Vazirani. Approximation Algorithms, Springer.
(5) D.P. Williamson and D.B. Shmoys. The Design of Approximation Algorithms, Cambridge University Press.
(6) M. Mitzenmacher and E. Upfal. Probability and Computing: Randomized Algorithms and Probabilistic
Analysis, Cambridge University Press.
(7) A. Borodin and R. El-Yaniv. Online Computation and Competitive Analysis, Cambridge University Press.
(8) Proceedings of STOC, FOCS, SODA, ESA and etc.

Notes（備考）
Email（電子メールアドレス）

miyano@ces.kyutech.ac.jp

Course Name（科目名）

Advanced Optimization Theory

Instructor Name(担当教員名）

Eitaku Nobuyama

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deals with the fundamental optimization theory and the optimization methods for continuousvariable problems. It starts with the optimality conditions for non-linear optimization problems, then explores
some fundamental optimization methods for optimization problems without or with constraints.

Course Description（授業の概要）

This course belongs to Module "Optimization Module."
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）
CourseObjectives（授業の達成目標）Contents（内容）1. Introduction

What is Optimization Theory?

2. Mathematical preliminary

Mathematical preliminary and problem formulation

3. Optimality condition 1

Optimization problems with equality constraints

4. Optimality condition 2

Optimization problems with inequality constraints

5. Optimization method 1

Golden section method

6. Mid-term exam

Midterm exam and its review

7. Optimization method 2

Convergence rate, Steepest descent method, Newton's method

8. Optimization method 3

Trust region method etc.

9. Optimization method 4

Penalty function method, Barrier functin method etc.

10. Convex programming

Convex set, Convex function, Convex programming problem

11. Duality

Dual problem, Duality theorem

12. Support vector machine 1

Problem formulation, SVM with soft margin

13. Support vector machine 2

Variety of SVMs

14. Neural network optimizaiton 1

Problem formulation, NN as an optimization problem

Variety of optimization methods for NNs
15. Neural network optimizaiton 2This course will be taught in a didactic manner in Japanese.

Introduction to Couse Objectives At the end of the course, participants are expected to understand optimality conditions and explain fundamental
optimization methods for non-linear optimization problems.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. Describe optimality condtions for non-linear optimization problems.
2. Explain optimization methods for optimizaiton problems without constraints.
3. Explain optimization methods for optimizaiton problems with constraints.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Grading will be decided based on mid-term exam and term-end report.

Assignment Instructions（授業外学習（予習・復習）の指示）

Participants are expected to study in advance for the next class and review what was learned in class. They are
expected to take more than 4 hours in a week for preparation.

Keywords（キーワード）

optimization, optimality condition, non-linear programming, convex programming, duality

Required Textbooks（教科書）Will be introdued in the class.

References/Recommended Reading（参考書）

Will be introdued in the class.

Notes（備考）
Email（電子メールアドレス）

nobuyama@ces.kyutech.ac.jp

Course Name（科目名）

Advanced Topics in Image Processing

Instructor Name(担当教員名）

Takeshi Saitoh

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Lectures on basic and advanced algorithms related to image processing.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

It is desirable to have knowledge on image processing and pattern recognition, such as "Statistics and Data
Analysis", "Image Information Processing", and "Multimedia Engineering" at undergraduate schools.

Theme(テーマ）

Contents（内容）1. Introduction of machine learning
2. Machine learning exercises
3. Multilayer perceptron
4. Database for image recognition
5. Convolutional neural network (1)6. Convolutional neural network (2)Course Calendar/Class Topic（授業計画）

7. Convolutional neural network (3)8. Image data collection
9. Style transfer
10. Recurrent neural network
11. Explainable AI
12. Presentation (1)13. Presentation (2)14. Presentation (3)General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

15. Summary
This class is conducted in a lecture style. Basic image processing algorithms in each field and papers publishedin journals and international conferences are explained. Read a selected paper presented at journals andinternational conferences on image processing, summarize it as slide, and give presentations once per student.
Exersice using Google Colab.
In this lecture, the common learning and education goals of the Faculty of Information Technology are (B)"Basic academic ability required in information science and engineering and each field", and the learning andeducation goals of System Design and Informatics (1) "Advanced". In order to acquire the ability to "solve
problems as an advanced information engineer based on conventional information technology", through thelatest research on image processing presented at international conferences in recent years, in recent years inthis field Understand trends.
1. Learn the research field of image recognition.
2. Understand the latest research trends in image recognition.
3. Implement image recognition task using a convolutional neural network.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Comprehensive evaluation based on the contents of the quizzes (10%), exercises (50%), reports (30%), andpresentation (10%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Lecture materials will be released in advance in Moodle. Read and prepare for the materials. In addition, areport will be imposed as a review.
4 hours a week as a preparatory study.

Keywords（キーワード）

Image processing, pattern recognition

Required Textbooks（教科書）Distribute materials in the class.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

saitoh [at] ces.kyutech.ac.jp

Course Name（科目名）

Advanced Algebra II

Instructor Name(担当教員名）

Makoto Tagami

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
As a foundation of algebraic systems, the notions of a ring and a filed are introduced and the basis is lectured. We
lecture the notions of ideals and redisue rings and introduce the fundamental theorem of homomorphisms of rings.
Furthermore we introduce the total quotient ring which is a generalization of the construction of rings of rational
numbers from the ring of integers, unique factorization domain which is an abstraction of the property offactorization of integers, the theory of elementary divisors which is the theory of finitely generated module overpricipal ideal domains, and we lecture linear algebra over fileds. Finally we lecture the notion of extension of fields,
algebraic closure, the construction of finite fileds and the property of finite fields.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Under the contents of Advanced Algebra I, ring theory which is the most fundamental notion in algebra islectured.

Theme(テーマ）

Contents（内容）1. Rings and fields
2. Ideals and residue rings
3. The fundamental theorem of homomorphisms
4. Prime ideals and maximal ideals
5. Direct sums of rings
6. Total quotient rings
Course Calendar/Class Topic（授業計画）

7. Unique factorization domain
8. R-modules
9. Modules over principal ideal domains
10. Linear algebra over fields
Jordan normal forms and the theory of elementary11.
divisors
12. Characteristic
13. The notion of extensions
14. The existence and the uniqueness of algebraic closure

General Course Policies（授業の進め方）

15. Constructions of finite fields and its property
We are planning the following(March 1st 2021). The lectures are given asynchronously. The lecture materials
corresponding to the above class contents, movies or slides, are given on the Moodle course. The students
access to the materials and studies the above contents. Reports will be imposed every time and submitting thereports will be understood as the attendance at the lecture. Questions from students will be accepted with
Moodle message or email suitably, and the answers will be explained to the whole of students with Moodle. If
necessary, we take the quetsion time with zoom suitably.

The objective of the class is to acquire 'fundamental knowledge required in information science, information
Introduction to Couse Objectives engineering and other areas' presented in the common course objective (B) of Graduate School of Computer（授業の達成目標の解説）
Science and Systems Engineering.
CourseObjectives（授業の達成目標）

1. To understand the notion of rings and to judege whether an algebraic structure has a ring structure.
2. To understand the notions of ideals and basic calculations on ideals
Couse objectives(具体的な授業の達成目標）

3. To understand the fundamental theorem of homomorphisms and basic calculations of homomorphisms.
To understand the notions of prime ideals and maximal ideals and to judge whether an ideal is a prime
4.
ideal or a maximal ideal.
5. To reconstruct the theory of linear algebra Under the notion of R-modules .

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

It is comprehensively evaluated by reports.

Assignment Instructions（授業外学習（予習・復習）の指示）

In this class, the calculation and property of finite fields play an important role. It is important to review helectures properly and understand the contents steadily. Participants is required to spend at least 4 hours per a
week for a preparation of class.

Keywords（キーワード）

ring theory, number theory, finite fields

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Algebra, Hiroshi Nagao, Asakura shoten, in Japanese

Notes（備考）
Email（電子メールアドレス）

tagami@ces.kyutech.ac.jp

Course Name（科目名）

Algebraic Combinatorics

Instructor Name(担当教員名）

Makoto Tagami

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
In this class, we introduce coding theory from the viewpoint of algebraic combinatorics. We start with a basis ofnumber theory and construct interesting combinatorial structures as an application of number theory.
Furthermore we give a construction of a code fixed a code length and having the maximal error correcting
ability by using the combinatorial structures. We introduce how mathematics can be applied to coding theory ininfomation science.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The class is an information subject (Elective course) in Master's program. We lecture from a basis of discrete
mathematics to applications to information science. As a background knowledge for the class, it is disirable thatparticipants are familiar with linear algebra, but more advanced linear algebra such as linear spaces over finite
fields is lectued in the class at any time if necessary.
Theme(テーマ）1.

Contents（内容）Sets, equivalent classes,
classification

2. functions and algebraic systems
3. Introduction to number theory, I
4. Introduction to number theory, II
5. Introduction to number theory, III
6. GCD of polyomials
7.
Course Calendar/Class Topic（授業計画）A construction of finite fields andits property

8. Finite geometry and designs, I
9. Finite geometry and designs, II
10. A basis of coding theory
11. Linear codes
Encoding and decoding of linear
codes
The Hamming bound and perfect
13.
codes
12.

14. Cyclic codes, I
15. Cyclic codes, IIGeneral Course Policies（授業の進め方）

We are planning the following(March 1st 2021). The lectures are given asynchronously. The lecture materials
corresponding to the above class contents, movies or slides, are given on the Moodle course. The students
access to the materials and studies the above contents. Reports will be imposed every time and submitting thereports will be understood as the attendance at the lecture. Questions from students will be accepted with
Moodle message or email suitably, and the answers will be explained to the whole of students with Moodle. If
necessary, we take the quetsion time with Zoom suitably.

Introduction to Couse
Objectives（授業の達成目標の解説）
CourseObjectives（授業の達成目標）

Couse objectives(具体的な授業の達成目標）

The objective of the class is to acquire 'fundamental knowledge required in information science,
information engineering and other areas' presented in the common course objective (B) of Graduate
1. School of Computer Science and Systems Engineering.
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

It is comprehensively evaluated by reports.

Assignment Instructions（授業外学習（予習・復習）の指示）

In this class, the calculation and property of finite fields play an important role. It is important to review helectures properly and understand the contents steadily. Participants is required to spend at least 4 hours per a
week for a preparation of class.

Keywords（キーワード）

number theory, finite fields, coding theory

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Mathematics of codes and cryptograpy, Ryo Fujiwara and M.Jinbo, Kyoritsu shuppan, in Japanese

Notes（備考）
Email（電子メールアドレス）

tagami@ces.kyutech.ac.jp

Course Name（科目名）

Advanced statistical data analysis

Instructor Name(担当教員名）

Aoi HONDA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Probability and Statistics grows in importance as a foundation of analyses of experimental data, patternrecognition, machine learning, data mining, image processing, etc. In the course, students first learn thefoundation of probability theory, such as the law of large number and the central limit theorem. In the second
half, students learn the way of some statistical arguments, such as statistical inference and hypotheses testing.
I also explain advanced topics and applications.
This is one of the basic subjects (elective) for students in the Master's Course. The purpose of this course isto develop the ability to explain logically in papers and oral presentations. The goal is to develop the ability not
only to analyze the subject but also to design analytical methods by oneself.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Course Calendar/Class Topic（授業計画）

Contents（内容）1. What is Data Science?

Guidance and descriptive statistics of data

2. Multivariate data

Descriptive statistics and visual representation of multivariate data

3. Handling of multivariate dataxercises on multivariate data

4.

Random variables and distributions
Distributions of multivariate random variables
1

5.

Random variables and distributions
Various multidimensional probability distribution functions
2

6.

Basic theory of normal distribution
Multidimensional normal distribution and statistical Inference
and statistical Inference

7.

Distributions of multidimensionalrandom variables

8.

Statistical inference of quantitative Point estimation and Interval estimation for a single population
based on normal distribution
data for a single population 1

9.

Statistical inference of quantitative Hypothesis testing for a single population Bbased on a normal
distribution
data for a single population 2

10.

Statistical inference of quantitative Hypothesis testing for a single population based on the poisson
distribution
data for a single population 3

11.

Regression analysis and deeplearning

Inference and deep learning based on regression models

12.

Prediction and control in deeplearning

Prediction and control theory for deep learning

13.

Statistical inference of quantitative Statistical inference for multiple populations based on normal
distribution
data on multiple populations 1

14.

Statistical inference for multiple
populations 2

15. Nonparametric tests

Multidimensional conditional probability distributions and descriptive
statistics

Tests based on contingency tables
Signed and rank sum tests

General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

Lectures and exercises

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

A small exercise will be assigned each time. A final exam will be given.The final exam will be held at the end of
the course, and the grade will be calculated in the ratio of 40% for the exercise and 60% for the exam.

Assignment Instructions（授業外学習（予習・復習）の指示）

Two hours of preparation per week.

Keywords（キーワード）

Mathematical Statistics, AI, Machine Learning, Statistical Data Analysis

Required Textbooks（教科書）

Basics of Statistical Data Analysis, Shu Yamada, Shun Matsuura, Science Inc.(in Japanese)

References/Recommended Reading（参考書）

Introduce them in class.

Notes（備考）None in particular

Email（電子メールアドレス）

aoi@ces.kyutech.ac.jp

Obtain an understanding and practical skills in statistical data science
1. Understand the handling of random variables and the structure of statistics
2. apply basic methods of estimation and testing to real-world problems
3. Understand the relationship between statistical data analysis and artificial intelligenceCourse Name（科目名）

Advanced Statistical Machine Learning

Instructor Name(担当教員名）

TOKUNAGA Terumasa

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deal with the basics of data science for estimating an essential and latent structure behind hugedatasets
in terms of Bayesian inferences and statistical machine learning. At the end of the course, participants are
expectedto acquire skills to apply basic machine learning techniques including regrression, classification and clustering
for real-world problems. In addition, some advanced application studies using deep leraninng, ensemble learningand sequencial estimation based on Bayesian finters will be introduced.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is intended for master course students to acquire skills and sences in data science for modeling anlatent structure behind huge and complex data.

Theme(テーマ）
1. Introduction
2. Least Squares Method
3. Maximum Likelihood Estimation
4. Perceptron Algorithm
5. Logistic Regression Analysis

Contents（内容）Introduction to machine learning
Understand regression analysis concepts and technique, leastsquares methods.
Understand regression analysis concepts and technique, maximum
likelihood estimation.
Learn the perceptron algorithm which is the most basic method oflearning classifier.
Understand logistic regression analysis.

Practice: Perceptron Algorithm and Run the codes for Perceptron algorithm and Logistic regression
and get the results.
Logistic Regression Analysis
Understanding data clustering concepts and techniques (K-means
7. K-means
and Hierarchical clustering).
Running clustering in Python with Silhouette distance measure for
8. Practice: K-meanscluster validity
Understand EM algorithm as one of familiar computational schemes
9. EM Algorithm
based on the maximum likelihood estimation
6.

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

10. Bayesian Statistics

Understand of the basics of Bayesian statistics.

11. Bayesian Regression

Understand Bayesian linear regressions and model averaging.

12. Deep Learning with Keras 1

Introduction to Deep Learning & Neural Networks with Keras.

13. Deep Learning with Keras 2

Learn the foundations of Deep Learning, understand how to build
neural networks.

14. Deep Learning with Keras 3

Run the codes for Deep Learning and get the results.

15. Deep Learning with Keras 4

Learn the advanced computer vision applications with CNN.

Evaluation is performed comprehensively based on results of exercises or one-minute papers (40%) andsubmitted reports (60%).
Electronically-made lecture materials, such as PowerPoint presentations, will be used.
1. Regression: Minimum square error estimation, Maximum likelihood estimation
2. Classification: Perceptron, Logistic regression, Clustering
3. Validation: Cross-validation, Training error, Generalization error

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Class attendance, discussion and quizzes (40%). Mid and final reports (60%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Details will be instructed in class

Keywords（キーワード）

Bayeisan inference, statistical machine leanrning

Required Textbooks（教科書）

Details will be instructed in class

References/Recommended Reading（参考書）

・Pattern Recognition and Machine Learning/C.M. Bishop
・ITエンジニアのための機械学習理論入門/中居悦司
・統計的機械学数理論/金森敬文
・kerasによるディープラーニング/F. Chollet

Notes（備考）
Email（電子メールアドレス）

saita@kct.ac.jp

Course Name（科目名）

Advanced Discrete Algorithms

Instructor Name(担当教員名）

Toshiki Saitoh

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Many actual problems on computers are modeled as discrete structures, for example graphs, strings, and so on,
and we treat the problems with discrete optimization problems. However, if we use naive algorithms for these
problems, we cannot solve them realistically by the huge amount of combinations. Therefore, it is important todesign efficient algorithms for them. In this course, we study advanced algorithm design and analyze mtehod tosolve the optimization problems.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course belongs to algoirthm design and optimization modules and we study advanced discrete algorithm
design and analyzing methods. We require basic knowledge of graphs and algorithm design before taking thiscourse.
Theme(テーマ）

Contents（内容）1. Introduction of this course

Course Calendar/Class Topic（授業計画）

2. Branching (1)Algorithm design and correctness

3. Branching (2)Complexity analysis

4. Branching (3)Advanced algorithms: Measure & Conquer

5. Branching (4)Exercises

6. Dynamic programming (1)Algorithm design

7. Dynamic programming (2)Advanced algorithms: Inclusions and exclusions

8. Dynamic programming (3)Complexity analysis

9. Dynamic programming (4)Exercises

Treewidth and Frontier-based
10.
search (1)Treewidth and Frontier-based
11.
search (2)Treewidth and Frontier-based
12.
search (3)Treewidth and Frontier-based
13.
search (4)Treewidth and Frontier-based
14.
search (5)Definintion of treewidth and dynamic programming
Computing tree decompositions
ZDD and frontier-based search
Applications of frontier-based search and implementations
Exercises

15. Conclusions
General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

We take the lectures of this course online. The first class and some of exercises are onsite and they are insynch online. The lecture videos are bloadcasted on Moodle so students watch the videos and solve quiz andexercises.
We study advanced algorithm design and analysing methods. And then we learn how to solve discrete
optimization
problems related to actual and social problems.
We can design algorithms by using each algorithm design methods, branching, dynamic programming, and
1. frontier-based search.
2. We can develop algorithms for discrete optimization problems by selecting suitable algorithm techniques.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

We give some homeworks to design and analyze algorithms for each algorithm technique. We check yourunderstanding by examination and/or making presentations about your algorihtms. Report: 60 - 70%, Examination: 30 - 40%

Assignment Instructions（授業外学習（予習・復習）の指示）

You can see the materials of this courses on Moodle. You take preparations 2 hours and reviews 2 hours byusing them. You have to try to solve exercises to understand the details. We will upload these exercises on
Moodle.

Keywords（キーワード）

Discrete algorithms, data structures, branching, dynamic programming, frontier-based search, complexity theory

Required Textbooks（教科書）

Nothing (we will give you some materials on Moodle.)

References/Recommended Reading（参考書）

・F.V. Fomin, D. Kratsch, Exact Exponential Algorithms, Springer, 2010.
・湊 真一(編)，超高速グラフ列挙アルゴリズム，森北出版，2015.
・Cygan et al., Parametarized Algorithms, Springer, 2015.

Notes（備考）
Email（電子メールアドレス）

toshikis@ces.kyutech.ac.jp

Course Name（科目名）

Exercises on Advanced Robotics Integration I

Instructor Name(担当教員名）

Eiji Hayashi, Yuya Nishida, Masahiro Oya

Course intended for（対象学年）

1ｓｔ , 2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1This is practical exercises for advanced robotics integration in Robotics Synthesis & Management Course .
The practical exercise explores proactively future robots development, the management, the service
engineering, focusing on the RaaS (Robot as a Service) with a team to solve the issues for consumers. It
consists of a series of lectures and meetings, a parallel series of hands-on lab & trainings. The hand-on
trainings will have a plan to lead a robot at factory, hospital, shop, office building and so on with the team baseon the consumer's requests and demands. After taking this class, the edge-cloud, the management for the robot
will be learned and acquired based on RaaS.
The course is helpful intermediate-level programming and software operation skills, management and priorexperience in robotics or artificial intelligence but not required.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）A series of this consists of Exercises on Advanced Robotics Integration I, II and III , and then it needs tocontinuously take all of "Exercise on Advanced Robotics Integration I,II and III" depending on the admission
period is in April or October.
Theme(テーマ）

Contents（内容）1. Understanding robot/AI on RaaS
2. Data analysis on robot behavior
3. Research for location to introduce robot
4. . Plan and Introduction for robot
5. Group discussion(1)Design robot behavior that facilitate
6. visual landmark-based localizationand navigation
Course Calendar/Class Topic（授業計画）

7. Management plan
8. Robot operation plan
9. Group discussion(2)10. Hand-on Training (1)11. Hand-on Training (2)12. Hand-on Training (3)13. Group discussion(3)14. Group discussion(4)General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. Presentation
About 5 students will make up a team, and try to mainly do the monthly meeting with Savioke, San Jose, thehand-on lab & training etc..

Introduction to Couse Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

1. Team s communication for searching and finding a solution
2. Engineering for taking control of the issues.
3. Sharing information and development for regions and global technologies
Peer review by students (20％), homework, report, and presentation(80％)

Assignment Instructions（授業外学習（予習・復習）の指示）
Keywords（キーワード）
Required Textbooks（教科書）
References/Recommended Reading（参考書）

Notes（備考）Japanese, English

Email（電子メールアドレス）

Eiji Hayashi haya@mse.kyutech.ac.jp
Yuya Nishida y-nishida@brain.kyutech.ac.jp
Masahiro Oya oya@cntl.kyutech.ac.jp

Course Name（科目名）

Exercises on Advanced Robotics Integration Ⅱ

Instructor Name(担当教員名）

Eiji Hayashi, Yuya Nishida, Masahiro Oya

Course intended for（対象学年）

1ｓｔ , 2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1This is practical exercises for advanced robotics integration in Robotics Synthesis & Management Course .
The practical exercise explores proactively future robots development, the management, the service
engineering, focusing on the RaaS (Robot as a Service) with a team to solve the issues for consumers. It
consists of a series of lectures and meetings, a parallel series of hands-on lab & trainings. The hand-on
trainings will have a plan to lead a robot at factory, hospital, shop, office building and so on with the team baseon the consumer's requests and demands. After taking this class, the edge-cloud, the management for the
robot will be learned and acquired based on RaaS.
The course is helpful intermediate-level programming and software operation skills, management and priorexperience in robotics or artificial intelligence but not required.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）A series of this consists of Exercises on Advanced Robotics Integration I, II and III , is a prerequisite fortaking Robotics Synthesis & Management Course and earning Exercises on Advanced Robotics IntegrationI". However, if this course's teachers permit to taking this course, this course can be taken without earning"Advanced Robotics Integration I".
Theme(テーマ）

Contents（内容）1. Understanding robot/AI on RaaS
2. Data analysis on robot behavior
Research for location to introduce
3.
robot
4. Plan and Introduction for robot
5. Group discussion(1)Course Calendar/Class Topic（授業計画）

Design robot behavior that facilitate
6. visual landmark-based localizationand navigation
7. Management plan
8. Robot operation plan
9. Group discussion(2)10. Hand-on Training (1)11. Hand-on Training (2)12. Hand-on Training (3)13. Group discussion(3)14. Group discussion(4)General Course Policies（授業の進め方）
CourseObjectives（授業の達成目標）

15. Presentation
About 5 students will make up a team, and try to mainly do the monthly meeting with Savioke, San Jose, thehand-on lab & training etc..

Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

1. Team s communication for searching and finding a solution
2. Engineering for taking control of the issues.
3. Sharing information and development for regions and global technologies
Peer review by students (20％), homework, report, and presentation(80％)

Assignment Instructions（授業外学習（予習・復習）の指示）
Keywords（キーワード）
Required Textbooks（教科書）
References/Recommended Reading（参考書）
Notes（備考）Japanese, English

Email（電子メールアドレス）

Eiji Hayashi haya@mse.kyutech.ac.jp
Yuya Nishida y-nishida@brain.kyutech.ac.jp
Masahiro Oya oya@cntl.kyutech.ac.jp

Course Name（科目名）

Exercises on Advanced Robotics Integration Ⅲ

Instructor Name(担当教員名）

Eiji Hayashi, Yuya Nishida, Masahiro Oya

Course intended for（対象学年）

2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1This is practical exercises for advanced robotics integration in Robotics Synthesis & Management Course .
The practical exercise explores proactively future robots development, the management, the service
engineering, focusing on the RaaS (Robot as a Service) with a team to solve the issues for consumers. It
consists of a series of lectures and meetings, a parallel series of hands-on lab & trainings. The hand-on
trainings will have a plan to lead a robot at factory, hospital, shop, office building and so on with the team baseon the consumer's requests and demands. After taking this class, the edge-cloud, the management for the
robot will be learned and acquired based on RaaS.
The course is helpful intermediate-level programming and software operation skills, management and priorexperience in robotics or artificial intelligence but not required.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）A series of this consists of Exercises on Advanced Robotics Integration I, II and III , is a prerequisite fortaking Robotics Synthesis & Management Course and earning Exercises on Advanced Robotics Integration I
and II ". However, if this course's teachers permit to taking this course, this course can be taken without
earning "Advanced Robotics Integration I or II".
Theme(テーマ）

Contents（内容）1. Understanding robot/AI on RaaS
2. Data analysis on robot behavior
3.

Research for location to introduce
robot

4. Plan and Introduction for robot
5. Group discussion(1)Course Calendar/Class Topic（授業計画）

Design robot behavior that facilitate
6. visual landmark-based localizationand navigation
7. Management plan
8. Robot operation plan
9. Group discussion(2)10. Hand-on Training (1)11. Hand-on Training (2)12. Hand-on Training (3)13. Group discussion(3)14. Group discussion(4)General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

15. Presentation
About 5 students will make up a team, and try to mainly do the monthly meeting with Savioke, San Jose, thehand-onlab & training etc.

1. Team s communication for searching and finding a solution
2. Engineering for taking control of the issues.
3. Sharing information and development for regions and global technologies
Peer review by students (20％), homework, report, and presentation(80％)

Assignment Instructions（授業外学習（予習・復習）の指示）
Keywords（キーワード）
Required Textbooks（教科書）
References/Recommended Reading（参考書）
Notes（備考）Japanese, English

Email（電子メールアドレス）

Eiji Hayashi haya@mse.kyutech.ac.jp
Yuya Nishida y-nishida@brain.kyutech.ac.jp
Masahiro Oya oya@cntl.kyutech.ac.jp

Course Name（科目名）

Advanced Energy Principles and Finite Element Methods

Instructor Name(担当教員名）

Niho, Tomoya

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Credits（単位数）2Finite element analysis method are widely used in design and development of mechanical structure. This course provides theenergy principles and the principles of virtual works that required to understand the fundamental principles for the finite element
analysis methods.
Furthermore, the approximate methods and the finite element methods are also provide.

The aim of this course to help students acquire an understanding of the fundamental principles of the finite element methods. It is
desirable to take the courses “Computer Aided Engineering” and “Computational Mechanics” in the master’s course.
Theme(テーマ）

Contents（内容）1. Displacement theory of elasticity
2. Stress energy and complementary energy

Course Calendar/Class Topic（授業計画）

3. Variational principle

Principle of virtual work

4. Variational principle

Principle of minimum potential energy

5. Variational principle

Principle of complementary virtual work

6. Variational principle

Principle of minimum complementary potential energy

Approximate method based on variational
7.
principle
Approximate method based on variational8.
principle
Approximate method based on variational
9.
principle
Approximate method based on variational
10.
principle

Principle of virtual work
Principle of minimum potential energy
Principle of complementary virtual work
Principle of minimum complementary potential energy

11. Displacement method and force method
12. Finite element analysis method

Principle of virtual work

13. Finite element analysis method

Principle of minimum potential energy

14.
15.
General Course Policies（授業の進め方）
Introduction to Couse
Objectives（授業の達成目標の解説）
CourseObjectives（授業の達成目標）

The above items of textbook are introduced by the presenter, and discussed by all students. This course will be held online.
The aim of this course is to help student acquire an understanding of the fundamental principles and a formulating of the finite
element analysis method. The goals of this course are to
1. Understand the virtual work principle, the approximation methods and the finite element methods based on this principle

Couse objectives(具体的な授業の達成目標）

2. Understand the principle of minimal potential energy, the approximation methods and the finite element methods based on
this principle
3. Understand the complementary virtual work principle and the approximation methods based on this principle
Understand the principle of minimum complementary potential energy and the approximation methods based on this
4. principle

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Grade will be decide based on attendance, understanding, reports, presentation and discussion.

Assignment Instructions（授業外学習（予習・復習）の指示）

Presenter understand your presentation part in the textbook, and prepare presentation material.
All student perform the exercises, and prepare to explain its answer to all students.
4 hours preparation are required before every classes.

Keywords（キーワード）

Variational principle, stationary condition, Gauss ’s divergence theorem, Lagrange multiplier, Conditions of compatibility, Stressstrain relationship

Required Textbooks（教科書）鷲津久一郎，エネルギ原理入門（有限要素法の基礎と応用シリーズ3），培風館

References/Recommended Reading（参考書）
Notes（備考）This course will be taught in Japanese.

Email（電子メールアドレス）

niho@mse.kyutech.ac.jp

Course Name（科目名）

Exercises on Team Management

Instructor Name(担当教員名）

JAHNG Doosub, ISHII Kazuo, HAYASHI Eiji, OYA Masahiro

Course intended for（対象学年）

1ｓｔ , 2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1Management Project is a project course that is related to AI Robotics in the Robotics Synthesis & Management
course. Various perspectives are needed to address issues that are faced by regional Society. In the field of
robotics, when considering further development of robots, it is important to embody the technical approachfrom the viewpoint of utilization and application, service, and management in addition to the acquisition ofadvanced technology. And then, this project cooperates the educational institutions and companies related tothe management, common issues and themes for community benefit are inquired with businessperson,
professor, student and so on related to that. And it promotes abilities that are a fusion of the management &the engineer, and the presence in the society.
In this course, students will take the initiative in service planning, creating proposals, and practicing
management for the coexistence and revitalization of regional societies. In the series of processes. Throughout
their hands-on learning experiences, students will practice and learn about team building, activities, andevaluation in order to work as a team.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Robotics Synthesis & Management course is a prerequisite for this course.
Contents（内容）Theme(テーマ）Team Composition,TMC02Management,

1. TMC03Team・TMC04Self-Analysis(SWOT)
TMC05Leadership, TMC06Diversity,

2. TMC07SoftSkill
3.

TMC08TeamCommunication・

TMC09Planning&HowToSummary
TMC10Presentaion, Informationtransmission, Scheduling management,

4. Evaluation, Marketing, Social
investigation method

Course Calendar/Class Topic（授業計画）

5. League Match

League Match: Proposal & Preparation (1)：Finally Choosing the proposal
which is a high feasibility through the league match

6. League Match

Proposal & Preparation (2)7. League Match

Proposal & Preparation (3)8. League Match

League Match: Proposal & Preparation (4)9. Interim report & Presentation
10. League Match (1)We ll vote on which would be the best proposal

11. League Match (2)12. League Match (3)General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

13. League Match (4)Preparing final report &14.
presentation
15. Final presentation
Group Work: The divided 4 teams will proceed with the stages of creating a proposal, obtaining permission, andimplementing while receiving consultations based on pre-learning.
・Pre-learning : TM s podcast (DJ Tayori Anchor, DJ Tayori - Google Podcasts etc.) and the referencematerials are provided
・Q&A and discussion b Zoom and so on
・Accountability of learning process upload on KWM (Key Words Meeting)
http://www.brain.kyutech.ac.jp/~jahng/wp/?page̲id=242

1. Team s communication for searching and finding a solution
2. Engineering for taking control of the issues.
3. Sharing information and development for regions and global technologies
Interim presentation (20%）、Final presentation (30％）、Investigation reports (10％）、Final report（40％）

Assignment Instructions（授業外学習（予習・復習）の指示）
Keywords（キーワード）
Required Textbooks（教科書）
References/Recommended Reading（参考書）

Notes（備考）International Student
Due to the theme of this course (coexistence and revitalization with regional society), Japanese will be theprimarily language used. Please use this opportunity to practice using Japanese. Having a Japanese tutor may
be helpful if further support is needed.

Email（電子メールアドレス）

JAHNG Doosub
林 英治
石井 和男
大屋 勝敬

jahng@brain.kyutech.ac.jp
haya@mse.kyutech.ac.jp
ishii@ brain.kyutech.ac.jp
oya@cntl.kyutech.ac.jp

Course Name（科目名）

Advanced Tribology

Instructor Name(担当教員名）

Kiyoshi HATAKENAKA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Tribology deals with lubrication, friction and wear. Since tribology deals with academic boundaries, it takes a lot of time tounderstand its contents unless one has basic knowledge in multiple fields, when one enters the industry and encounters
tribology as a practical subject for the first time. In this course one will learn the basics of tribology and apply lubrication
theory as an application to deeply understand sliding bearings.

Course Description（授業の概要）

One is required to take all basic subjects in mechanical engineering.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Guidance
2. Significance of tribology
3. Contact with solid surface
4. Friction
5. Boundary lubrication
6. Tribo test of wear
7. Viscosity
Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）

8. Lubricant
9. Hydrodynamic lubrication theory
10. Lubrication theory of plain bearings
Numerical solution of pressure distribution
11.
in slider bearing
12. Elasto-Hydrodynamic Lubrication
Oral presentation of English article in
13.
Japanese
Oral presentation of English article in
14.
Japanese
Oral presentation of English article in
15.
Japanese
The first half of this course is a lecture style, and the second half is an oral presentation.

This course aims to acquire the goal of learning and education "(B) basic skills required in information
science/engineering and various academic fields" in the Graduate School of Information Engineering, especially "(1)Development of advanced technologies in both machine and information fields" and "(2) Ability to realize design andIntroduction to Couse Objectives production system based on knowledge of digital engineering, CAE, various dynamics simulations and advanced digital（授業の達成目標の解説）
technologies" that are declared by the Department of Mechanical Information Engineering, Department of Information
Systems. Specifically, one aims to achieve the following items.

Couse objectives(具体的な授業の達成目標）

1. One understand the basics of tribology, apply the hydrodynamic lubrication theory as an application and analyze
the performance of plain bearings. In addition, one understand deeply the research papers on the state-of-the art
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The specific goals listed above will be evaluated based on the content of oral presentation.

Assignment Instructions（授業外学習（予習・復習）の指示）

Preparation and review of the class for four hours per week are needed.

Keywords（キーワード）

Tribology, Friction, Wear, Lubrication, Surface, Contact, Viscosity, Lubricant, Boundary lubrication, Hydrodynamic
lubrication theory, Sliding bearing, Elastohydrodynamic lubrication

Required Textbooks（教科書）

Masayoshi MURAKI, Tribology - Science of friction and lubrication technology -, Nikkan Kogyo Shimbun

References/Recommended Reading（参考書）

Notes（備考）

Preparation and review of the class for four hours per week are needed.

Email（電子メールアドレス）

hatakenaka.kiyoshi218@mail.kyutech.jp

Course Name（科目名）

Micro Devices/Microsystems

Instructor Name(担当教員名）

Sunao MURAKAMI

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course introduces the fundamentals of the microdevices and microsystems including MEMS, which containmechanical and electrical micro-elements as the functional components of them. In particular, the fundamentalsof the design and the microfabrication techniques are introduced, and some practical examples and topics ofMEMS are also explained.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）In terms of the course and curriculum linkage in the learnig education goal of Graduate School of Computer
Science and Systems Engineering, this course is positioned as part of lectures to obtain the basic academic
skills which are required in various areas including informartion science and engineering.
Theme(テーマ）1.

Contents（内容）Overview of microdevices andmicrosystems

2. Materials used for Microdevices (1)3. Materials used for Microdevices (2)4. Microfabrication processes (1)5. Microfabrication processes (2)6. Micromachinig technique for MEMS
Fundamentals of operation
principles of MEMS (1)Fundamentals of operation
8.
principles of MEMS (2)7.
Course Calendar/Class Topic（授業計画）

9. Examples of MEMS
10. Topics on MEMS devices
11. Physical microsensors
12. Micro actuators
13. Chemiical microsensors
14. Micro chemical systems
15. Summury
General Course Policies（授業の進め方）
CourseObjectives（授業の達成目
標）This course will be taught with explainations (PPTs) and handouts for the lecture.

Introduction to Couse Objectives Main aims of this course are review and deepen knowledge and understanding of the fundamentals of
microdevice, microsystems including MEMS.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

1. Students are expected to explain the summary of microdevices, microsystems and MEMS
2. Students are expected to obtain the basic knowledge about the microfabrication techniques
3. Students are expected to explain the technology relating to microdevices and microsystems with some
practical examples
Final grade will be decided based on some homeworks (short reports) relating to the selected topics of thelecture (40%), and a final report (60%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Student are required 4-hours preparations for the topics of the class before each class.

Keywords（キーワード）

Microdevices, Microsystems, Microelectromechanical systems (MEMS), Microfabrication, Micromaching

Required Textbooks（教科書）

Text books are not used. Refferences are introduced in the class. Some materials are provided in each class.

References/Recommended Reading（参考書）

Some references are introduced in the class and the handouts.

Notes（備考）

Basically, this course will be taught in Japanese.

Email（電子メールアドレス）

murakami[at]mse.kyutech.ac.jp (Please change "[at]" to "@" in the mail address written in the left.)Course Name（科目名）

Micro Fludics

Instructor Name(担当教員名）

Katsuya Nagayama

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Knowledge of microfluidics is becoming essential in the expanding and expanding MEMS industry. Here, topics
covering micro flow dynamics and various fields of application to MEMS are widely covered, and students will
understand the basics and outline of micro fluid engineering. Specifically, it deals with microfluidics, flow inside
micromachines, processing technology, and measurement technology such as microscopes. Divide a wide rangeof fields and conduct research and analysis in specific fields to deepen understanding.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Learning objectives of the Graduate School of Information Engineering (B) Learn the basic scholastic skills
required in each field of information science and engineering from the viewpoint of micro-physical phenomena.
Based on knowledge of basic physics and fluid dynamics in undergraduate education, develop into physics inmicro systems. He is not limited to fluid mechanics, but deals with a wide range of micro-systems, such as
micro-measurement and micro-machining, and gains much knowledge.
Theme(テーマ）

Contents（内容）1. Microfluidics Overview
2. Molecular / nano thermal fluid
3. Micro thermal fluid
4. Interface and phase change
5. Micro channel
6. Electric field driven flow
Course Calendar/Class Topic（授業計画）

7. Tribology
8. Nano materials
9. Measurement technology
10. Processing technology
11. MEMS packaging technology

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

12. Aapplication

Micro bubbles, micro thrusters

13. Aapplication

Micro fuel cell, heat exchanger

14. Aapplication

Nanotube, laser processing

DNA, micro chemical system
15. Aapplication
Share topics in microfluidics reference books and make remote presentations and discussions. Add the latest
technology findings to the contents of the reference book.

Learning objectives of the Graduate School of Information Engineering (B) To acquire basic academic skills
Introduction to Couse Objectives required in information science and engineering and various fields from the viewpoint of micro-physicalphenomena. Understand general physics including fluid dynamics in micro systems, and acquire the ability to（授業の達成目標の解説）
apply to the field of micro devices.
Couse objectives(具体的な授業の達成目標）

1.
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Approximately 75% of the fields shared by the reference book were announced, including the latest technology,
and approximately 25% were discussed in questions and answers.

Assignment Instructions（授業外学習（予習・復習）の指示）

Presentation materials should be prepared with the latest information.
Review and examine any technical terms that you did not understand in class.
As a preparatory study, prepare 4 hours a week.

Keywords（キーワード）

Micro flow, micro machine, micro machining, microscope

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Micro / Nano Thermal Fluid Handbook (NTS Publishing)Notes（備考）As a preparatory study, prepare 4 hours a week.

Email（電子メールアドレス）

nagayama@mse.kyutech.ac.jp

Course Name（科目名）

Advanced Lecture on Mechatrosystem

Instructor Name(担当教員名）

Hiroyuki Narahara

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Miniaturization and advanced functionality are evolved about the leading-edge mechanical system such as robotics systems.
As the system configuration becomes complicated, extracting a useful parameter out of many parameters, and designing properly is required
more and more.
In such a curcumstances, development frameworks enables us accelerates development process as it makes us focus on the most importantfactors among design parameters.
Lecture is given about the fundamentals of the HCD (human centered design), KA method, Quality Function Deployment (Quality Function
Deployment:QFD) and Robust Quality Engineering: (RQE), which attract attention as an indispensable methods for product development
process.
In addition, the new machinery based on 3D printer technology is produced increasingly one after another. A lecture is also given about theAdditive Manufacturing used as the basis of 3D printer technology. It is given on the history, technology components, the state-of-the-art
development trends, and future challenges.

Course Description（授業の概要）

Lecture and an exercise are conducted about the following four topics.
1. Design, Product Development, and Research Process
2.Summary and Hardware of 3D Printer3. 3D Printer-related Software and Algorithm
4. Basic Knowledge on 3D Printer Material

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

It aims at mainly supporting the basic knowledge of Additive manufacturing, and the research-and-development skill relevant to 3D printerresearch in this lesson.
Since 3D printer is one of the electronic machine control systems represented by the robot etc., to an understanding of the component
engineering, it is desirable to have mastered the knowledge of mechanical drawing, electronic circuit and programming.

Theme(テーマ）

Contents（内容）1. A design, product development, and a research process
2. HCD (human centered design) and the KA process
3. The way of thinking of a function, and the definition of a function
4. An introduction to QFD (quality functional design)
5. Quality engineering and a parameter design
6. The history and the summary of 3D printerCourse Calendar/Class Topic（授業計画）

7. Hardware of 3D printer8. Basic knowledge on 3D printer material
9. The application example of 3D printer10. 3D printer-related software and an algorithm
11. 3D modeling and geometry data processing
12. The geometry processing algorithm relevant to 3D printer13. 3D printer related software
14. Reprap firmware and a temperature control algorithm

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. Reprap firmware and mechanism control algorism
It carries out in a seminar style.
In connection
order to deepen
understanding
in thegoal,intervalsof a lecture,
exercises,
such asdiscussion,
are performed
whererelevant.developments ofInwith aanlearning
performancethe systemevaluation
technology
towarda commonitem (B) andengineering

Introduction to Couse Objectives (1), (2), and (3) of a Major of Interdisciplinary Informatics and a Department of Mechanical Information Science and Technology, and a system（授業の達成目標の解説）
construction is learned.
Couse objectives(具体的な授業の達成目標）

1. Understand design and product development process, and make your own research plan based on the methods learned.
2. Understand the fundamentals of hardware and software of 3D printer.
3.

Understand the basic knowledge of 3D printer materials.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Based on the mid term report (20%) and final report (80%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Prepare homework, such as investigating and summarizing the contents of an exercise specified by lesson by the next time.

Keywords（キーワード）

3D printer, Additive manufacturing, Robust Design, Quality Function Deployment, Robust Quality Engineering

Required Textbooks（教科書）

Hiromichi Onikura ed, "Kikai Seisaku Yoron", yokendo, 2016.

References/Recommended Reading（参考書）

Notes（備考）It requires 4 hours homework per week for preparation and review.

Email（電子メールアドレス）

nara@mse.kyutech.ac.jp

Course Name（科目名）

Intelligent Robot Control

Instructor Name(担当教員名）

Hiroshi Ohtake

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Nowdays, the demand for robots has been growing rapidly in the fields of not only helping automation infactories, but also medical or nursing care, agriculture, entertainment, disaster rescue, and so on.
In this lecture, robot control methods will be explained from basic knowledge to applied techniques.
In addition, our understanding will be deepened by investigating and considering the latest robots and theircontrol methods.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

In order to take this course, basic knowledge of mathematics, mechanics, and control engineering is required.
Therefore, it is assumed that the following subjects have been completed. "Linear Algebra" "Physics""Differential Equation" "Dynamics" "Control Engineering"
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Contents（内容）1. Vector and matrix

review of linear algebra

2. Linear Control I

learn modern control theory (state equation, stability)

3. Linear Control IIlearn modern control theory (controller design, observer design)

4. Sensors

introduce sensors for robot

5. Actuators

introduce actuators for robot

6. Robot Control I

learn robot control (kinematics, inverse kinematics)

learn robot control (dynamics, inverse dynamics)
7. Robot Control IIIntelligent Control (Rule-basedlearn fuzzy control (fuzzy sets, fuzzy inference)
8.
Fuzzy Control I)
Intelligent Control (Rule-basedlearn fuzzy control (fuzzy control)
9.
Fuzzy Control II)
Nonlinear Control I (Model-basedlearn model-based fuzzy control (fuzzy model construction)
10.
Fuzzy Control I)
Nonlinear Control I (Model-basedlearn model-based fuzzy control (fuzzy controller design)
11.
Fuzzy Control II)
Introduction to various Robot
introduce to flying robots and wheel chair control
12.
Controls
Survey, Consideration, Presentation
presentation on robot, control, intelligent control, and so on.
13.
ISurvey, Consideration, Presentation
presentation on robot, control, intelligent control, and so on.
14.
I
Survey, Considering, Presentation presentation on robot, control, intelligent control, and so on.
15.
III
This lecture is held in in a didactic manner (lecture style). Students create reports on the contents of thelecture. In addition, students survey and consider on robot control, and give a presentation. Finally, students
create a report on your and others' survey contents.
This lecture is taught in Japanese. The lecture materials are mainly given in Japanese.
Depending on the infection spread of COVID-19, remote lessons that combines asynchronous and synchronous
types may be given.
The goal is to learn basic robot control methods based on control theory, and to be able to understand thelatest robots and their control methods.
1. Understand how to design control systems based on linear control theory
2. Understand the measurement and drive principles of various sensors and actuators used in robots
3 Understand the control method of multi-link robot
4 Understand how to design control systems using fuzzy control techniques

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Give a few report tasks within the scopes of the lecture. And evaluate the achievement of the goals using thereports (50%). Furthermore, evaluate the presentation (20%) and the final report (30%) on robot control.

Assignment Instructions（授業外学習（予習・復習）の指示）

Please keep 4 hours a week for a preparatory study.
Listen carefully and take notes.
Check literatures on robot control on a routine basis for final presentation.

Keywords（キーワード）

Robot control, linear control, nonlinear control, fuzzy control, mechatronics, robotics

Required Textbooks（教科書）

Necessary materials will be provided as needed.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

hohtake@mse.kyutech.ac.jp

Course Name（科目名）

Advanced Bioinformatics

Instructor Name(担当教員名）

YADA Tetsushi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Bioinformatics is an interdisciplinary field that understand biological phenomena from viewpoints of information
science. In this course, we read a state-of-art paper concerning with bioinformatics.

Course Description（授業の概要）

It is desirable to complete an undergraduate subject 'bioinformatics'.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

Contents（内容）1. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

2. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

3. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

4. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

5. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

6. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

7. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

8. Colloquium

Reading a state-of-art paper concerning with bioinformatics.

9.
10.
11.
12.
13.
14.
General Course Policies（授業の進め方）
CourseObjectives（授業の達成目
標）

15.
Mainly colloquium style, partially lecture style.

The main objective of this course is to get an idea to solve various biological issues by using bioinformatics
Introduction to Couse Objectives approaches.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. Understanding bioinformatics methods for biological data analysis.
2. Understanding recent advances in (molecular) biology brought by bioinfomatics researches.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Evaluated by oral presentation in colloquium.

Assignment Instructions（授業外学習（予習・復習）の指示）

Read the paper carefully in advance. 4 hrs per week for preparation.

Keywords（キーワード）

Bioinformatics, Genome, Gene, RNA, Protein, Evolution

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Notes（備考）

See the moodle course for the detailed information.

Email（電子メールアドレス）ytetsu@bio.kyutech.ac.jp

Course Name（科目名）

Genetic and Cellular Information (GCI)

Instructor Name(担当教員名）

Sakae KITADA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course is based on a lecture format, and aims to connect knowledge and essence of molecular cell biology.
It will be provide to dialogue between students as much as possible, extract scientific logic from researchers'
experiments and examples of consideration, and use it as the basis for the development of biotechnology.
Group discussions on issues, encourage interactive, student communication, and logical scientific expression
will be also done in this course.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

It will be expected to understand a part of the molecular and cellular biology in advance. This course is included
in a module System Biology .

Contents（内容）Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. Introduction
Protein birth, maturation, and2.
related diseases
Evolution of cell, construction of3.
eukaryote, and organelle diseases
4. Protein traffic in cell
Vesicle traffic in cell, and the5.
related infection
Quality control and degradation in
6.
cell, and the related diseases
Summary of lectures from 2nd to
7.
6th
8. Preparation for group discussion

Lecture9. Group discussion, part1

Discussion in groups of 4 or 5 students

10. Group discussion, part2

Discussion in groups of 4 or 5 students

11. Presentation and discussion, part1

Presentation on a theme by students, and discussions

12. Presentation and discussion, part2

Presentation on a theme by students, and discussions

13. Presentation and discussion, part3

Presentation on a theme by students, and discussions

14. Presentation and discussion, part4

Presentation on a theme by students, and discussions

LectureLectureLectureLectureLectureLectureOrganization of lecture and picking up several discussion topics

Review and summary of the course so far
15. Overall summary
Promote basic understanding and problem raising based on the lecture format. From this content, then,problems and issues will be discovered through group discussions. Finally, each student will summarize theresearch themes and problems found in the discussion and make a presentation.
Lecture format (excluding the first day) will be remote, using Moodle, and group discussions and presentations
will be held face-to-face.
It will be expected to understand molecular biology in cell, discuss the issues between students, and to improve
presentation in scientific fields.
1. Understanding molecular and cellular biology, especially protein maturation, traffic and Quality control.
2. Understanding diseases and infections related above topics.
3. Improving presentation skills in the biological and life science.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

The grade will be determined based on your active discussion (30%) and presentation (70%).

Assignment Instructions（授業外学習（予習・復習）の指示）

In the subject field studied in the undergraduate school, study the part corresponding to this class.

Keywords（キーワード）

Gene, transcription, translation, central dogma, protein, folding, organelle, evolution, protein transport, vesicletransport, quality control, proteolysis, cell death, infectious disease, folding disease, organelle disease, amyloid

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Molecular Biology of the Cell, 5th edition or later

Notes（備考）

At least four hours should be spent for preparation per week.

Email（電子メールアドレス）

kitada@bio.kyutech.ac.jp

Course Name（科目名）

Chemical & Biomedical Engineering

Instructor Name(担当教員名）

Iori Maeda

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course introduces students taking this course to the basics of the different types of biomaterials that canbe applied to regenerative medicine. Students will develop understandings of the organic compounds andproteins used as components of biomaterials. This class also helps students improve their self-study skills bygiving presentations using materials that they have prepared themselves for presentation. Students should
discuss in detail the assigned theme and the latest scientific papers selected.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This class places to learn basic chemistry knowledge that is essential in the first year of the master's programat the Graduate School of Computer Science and Systems Engineering. This class is also positioned as a course
to learn broad biochemical engineering that leads to the research contents of each student.
Theme(テーマ）
1. Chemical basics for the medicine

the basics of chemistry and biochemistry

2. What are biomaterials?

5. drug delivery systemdefinition of biomaterials used in regenerative medicine
introducing many kinds of biomaterials used in regenerative
medicine
introducing many types of artificial organs used in regenerative
medicine
introducing drug delivery system used in medical field

6. material for the biomaterial

problem to be solved in development of biomaterial

7. the latest biomaterials

introducing the latest biomaterials

3. biomaterial polymer
4. artificial organ

Course Calendar/Class Topic（授業計画）

Contents（内容）

8.
9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15.
The first half of the class is in the form of lectures given by teachers. Quizzes to confirm comprehension will beheld as needed. In addition, for each theme, students present what they have learned.
In the second half, students explain academic papers written in English. In this class, teachers provide guidance
and amendments as needed to encourage lively discussion between students.

This lecture is a bioinformatics subject set up for the purpose of cultivating the basic learning ability required in
Introduction to Couse Objectives the information science and engineering and various fields, which is a common learning education goal of the
Graduate School of Computer Science and Systems Engineering.
（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

1. Understand the chemical structure of materials
2. Understand the environment that a substance undergoes in vivo
3. Understand the properties of various materials and their issues in application

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Your overall grade in the class will be decided based on the following:- Class attendance and attitude (presentation) in class: 70%- Short reports: 30%

Assignment Instructions（授業外学習（予習・復習）の指示）

preparing the presentation, examining tasks

Keywords（キーワード）

Biomaterial, Drug Delivery System, Elastin

Required Textbooks（教科書）『ヴィジュアルでわかるバイオマテリアル』（古薗 勉、岡田正弘著、秀潤社）

References/Recommended Reading（参考書）『ドラッグデリバリーシステムDDS技術の新たな展開とその活用法』（田畑泰彦編集、株式会社メディカルドウ）『DDS最前線』（金尾 義治著、広川書店）

Notes（備考）

4 hr/week

Email（電子メールアドレス）

Course Name（科目名）

Computational and Integrative Biology

Instructor Name(担当教員名）

Kazuhiro Takemoto

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course introduces "Network Science." Network science is a research area in which complex networks arestudied, and it originates from graph theory. Networks describe the relationships among elements, and are, thus,
simple and powerful tools for describing complicated systems. The concept of networks is universal and can beapplied to a wide range of fields (e.g., mathematics, computer science, economy, sociology, chemistry, biology). This
course focuses on the fundamental concepts and applications of network science (especially, in biology). The topic
are as follows.
This course is based on discrete math, linear algebra, statistics, numerical computation, artificial intelligence, andbioinformatics.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）
CourseObjectives（授業の達成目標）Contents（内容）1. Introduction

What is network science

2. Graph theory

Revisiting graph theory

3. Network representation

Network properties and measures

4. Centrality analysis

Finding important nodes from complex networks

5. Random networks

Random network models as null models

6. Small-world networks

The fundamental concepts and applications

7. Network motifs
Generative models for complex
8.
networks
9. Stochastic block models

Finding important subgraphs from complex networks

Application to network clustering

10. Community detection

Detecting communities (groups) from complex networks

11. Network robustness

Measuring network robustness and finding critical nodes

12. Network controllability (1)Maximum matching-based approach

13. Network controllability (2)Minimum dominating set-based approach

14. Random matrix theory

The fundamental concepts and applications

Extended random networks, evolving networks, and more

Estimating networks from high dimensional data
15. Correlation networks
This course is lecture-style, but practice-style partly.

Introduction to Couse Objectives The goal is to acquire the fundamental concepts and applications of network science. The specific objectives are
as follows.
（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. To aquire the fundamental concepts of network science (theories, models, methods, etc.)
2. To design real-world application of network analysis
3. To perform network analysis using scripting languages (e.g., R and Python)

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The evaluation is based on reports and homeworks.

Assignment Instructions（授業外学習（予習・復習）の指示）

Use the online course materials for preparation and review. At least 4 hours per week is required for preparation.

Keywords（キーワード）

networks, graphs, discrete algorithm, bioinformatics, network analysis

Required Textbooks（教科書）

References/Recommended Reading（参考書）「Network Science」http://barabasi.com/networksciencebook/「Lectures on Complex Networks」https://sites.google.com/site/sergeydorogovtsev/lectures̲on̲complex̲networks「Tutorial on R+igraph」https://sites.google.com/site/kztakemoto/resources

Notes（備考）

Remote class (asynchronous)

Email（電子メールアドレス）

takemoto@bio.kyutech.ac.jp

Course Name（科目名）

Cell Signal Transduction

Instructor Name(担当教員名）

Shunsuke Aoki

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Lectures are for learning the latest research results on cell signaling. The teaching materials on academic
papers published in the academic journal "Cell" are used to understand cutting-edge cell biology and to develop
research design skills.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

In order to grasp the whole cell or life as a system, it is necessary to understand the main subsystems, gene
expression system, cell signaling system and energy metabolism system.

Theme(テーマ）

Contents（内容）1. RTK signaling pathway
2. ras-grab signaling molecules
3. p53 and Rb molecules
4. UPS system
5. ubiquitination and cell signals
6. E1-E2-E3 pathway
Course Calendar/Class Topic（授業計画）

7. deubiquitination systems
8. anti-cancer drugs
9. Presentation and discussion 1
10. Presentation and discussion 2
11. Presentation and discussion 3
12. Presentation and discussion 4
13. Presentation and discussion 5
14. Presentation and discussion 6

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. Presentation and discussion 7
Lectures are conducted mainly on reading, presenting, asking questions, and group discussions on English
academic papers.

In order to grasp the whole cell or life as a system, it is necessary to steadily understand the main subsystems.
Introduction to Couse Objectives Therefore, we will concentrate on the characteristics of genetic information expression system, cell signal（授業の達成目標の解説）
transmission system, energy metabolism system, and experimental and theoretical analysis methods.
Couse objectives(具体的な授業の達成目標）

1.
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The evaluation is based on the content of the presentation and reports.

Assignment Instructions（授業外学習（予習・復習）の指示）

You have to prepare your presentations. In addition, you have to submit reports, etc.
4 hours a week as a preparatory study.

Keywords（キーワード）

Cell, information transmission, English academic papers, biotechnology, bioinformatics, molecular biology, cellbiology

Required Textbooks（教科書）reserch papar" Cell"

References/Recommended Reading（参考書）

reserch papar" Cell"

Notes（備考）

4 hours a week as a preparatory study.

Email（電子メールアドレス）

aokis@bio.kyutech.ac.jp

Course Name（科目名）

Neuroethology

Instructor Name(担当教員名）

Hideki Nakagawa

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Powe Point slides are used. In this class, at first, history of ethology is summarized. Then, the fundamentals of
ethology and signal processing in neural systems are explained. Finally, particularly progressed investigation ofneuronal mechanisms underlyaing some kinds of escape behaviors are explained.

Course Description（授業の概要）

This class belongs to systematic biolgy module in life sicence course.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）Review for study of behavior andthe foundamentals of ethology(1)Review for study of behavior and2.
the foundamentals of ethology(2)Review for study of behavior and3.
the foundamentals of ethology(3)Understandig of signal processing in4.
neural systems(1)Understandig of signal processing in
5.
neural systems(2)1.

6. Tail flip escape of the crayfish(1)7. Tail flip escape of the crayfish(2)Course Calendar/Class Topic（授業計画）

8. Tail flip escape of the crayfish(3)9. Bending reflex of the leech(1)10. Bending reflex of the leech(2)Collision avoidance behavior of thepigeon(1)Collision avoidance behavior of the12.
pigeon(2)Collision avoidance behavior of the
13.
locust(1)Collision avoidance behavior of the
14.
locust(2)11.

15. Term examination
General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

This lecture is performed in real time remote lecture by using Zoom system. Powe Point slides are used.
Construction of higher information system based on the knowledge of life science and technology
1. Understandig of the fundamentals of ethology
2. Understanding of signal processing of neuronal systems
3. Understanfing of neuronal mechanisms underlying various escape behaviors

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Evaluations of reports about key wrods in class topics(40%), term examination (60%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Rports about key words in class topics. Preparation and review of 4 hours per week

Keywords（キーワード）

Ethology, Neurophysiology, Neuroethology, Escape behavior

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Foundations of Neurobiology, Fred Delcomyn

Notes（備考）

Preparation and review of 4 hours per week

Email（電子メールアドレス）

naka@bio.kyutech.ac.jp

Course Name（科目名）

Computational molecular biophysics

Instructor Name(担当教員名）

Masayuki Irisa

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Shannon entropy in information theory and Gibbs entropy in non-equilibrium state have the identical equation.
Relation between a measure of information, entropy, and functions of biomolecules is reviewed based on statisticalmechanics. For example, protein has an unique conformation, tertiary structure, in water. A principle ofdetermination of a native conformation from amino-acid sequence, primary structure is explained. Furthermore,static and dynamic characters of a native conformation of protein, molecular motors, and roles of cations and waterin DNA cleavage by restriction enzymes are explained based on recent theoretical and computer simulation studies.
Mainly, theories of protein in aqueous solution based on statistical mechanics, especially theory of molecular liquids.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is addressed in the module of "Information of Biological Structure". Characters of biomolecules, protein
and DNA, are explained in biophysical aspects through computational chemical physics. Basic knowledge of biology isrequired. Biomolecules have functions in aqueous solution. Knowledge of thermodynamics, statistical mechanics, andquantum mechanics are also required. This course has relationship with not only biological courses but also
computer science courses through statistical mechanics, e.g. optimization problem, graph theory, computational
geometry, information entropy, boundary element method, and finite element method. To take this course, it isprerequisite to take courses, Modern Physics, Basic Physics, Chemical Thermodynamics, Biomolecule, andBioinformatics.
Contents（内容）Theme(テーマ）
Introduction: Thermodynamics andstatistical mechanics
Shannon entropy and2. thermodynamic entropy

Relation between thermodynamic equations and statistical mechanics

Derivation of micro-canonical,
3. canonical, grand-canonical, and TP-mu ensembles
Feynman ratchet model formolecular motors
4.

Derivation of the four ensembles by maximizing Gibb entropies withensemble-dependent conditions

Theory of molecular liquids and5. computer simulation

Formulas of calculating solvation free energies by using molecular
dynamics

1.

6.

Course Calendar/Class Topic（授業計画）

Theory of non-ideal liquid

Statistical theory of hard-spheres:
Scaled particle theory, van der7.
Waals EOS, cluster expansion of
grand potential
Protein thermodynamics and8. molecular dynamics

Identical equation for Shannon entropy and Gibbs entropy in
non-equilibrium state

Principles of molecular motors in non-equilibrium state - an exampleof actin-related molecular motor system explained with Feynman
ratchet model

Cluster expansion in grand-canonical ensemble
Virial coefficients, activities, osmotic pressure, head capacity, andpartial molar volume.
Thermodynamic quantity calculation of protein by using molecular
dynamics

Primary, secondary, tertiary, and
9. quaternary structures of protein

Experiments showing differences between protein and polymer

Review of studies on protein byusing molecular dynamics and10. Monte Carlo method - present
studiesProtein structure and hydration of protein

Hydration of protein and11. microscopic surface tension

statistical mechanics method incorporating effects from non-sphericalshape of protein

interpretation of volume entropy in polymer science with statistical
Macromolecular crowding effectmechanics of molecular liquids
and scaled particle theory
Review of studies on mechanics ofpresent studies
13. molecular motors
12.

Integral equation method in
14. statistical mechanics of molecularliquids
15. 1D-RISM and 3D-RISM theory

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

Ornstein-Zernike integral equation and Debye-Huckel theory of electrolyte

Application on Mg2+ and water molecule distribution in active sites of
EcoRV-DNA complex
Oral presentation including computer graphics presentation
In order to achieve an aim of a super course, Bioinformatics Course, "to learn methodologies of computer science,system technology, and biophysics to understand biological systems at the molecular level from diverse biologicalinformation," the objective of this course is "to learn basic knowledge of biophysics and computational chemical
physics of biomolecules in aqueous solution."
The objective is included in the objective of the Graduate School of Computer Science and Systems Engineering,（Ｂ）, "basic knowledge of computer science and technology, and other subjects."
1. To understand thermodynamics based on statistical mechanics
2. To understand the relation between theory of molecular liquids and computer simulation
3. To understand protein with statistical-mechanics and computer-simulation

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

There will be homework each week (40%) and final report (60%).

Assignment Instructions（授業外学習（予習・復習）の指示）

4 hours are required for home-work

Keywords（キーワード）

statistical mechanics, thermodynamics, computer simulation, molecular dynamics, theory of molecular liquids,
protein, water, entropy, information entropy, biophysics, single molecule measurement

Required Textbooks（教科書）

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

・ Yasushi Takahashi, Toukeirikigaku-Nyumon (Koudansha)
・ L.E.Reichl, Modern Course in Statistical Physics (Univ of Texas Pr)・ Kiyoshi Arakawa, Mizu・Suiyoueki no Kouzou to Bussei (Univ. of Hokkaido)
・ Katsuhide Yutani and Haruki Nakamura: Tanpakushitsu Kougaku (Asakura Shyoten)

Course Name（科目名）

Biomolecular Information

Instructor Name(担当教員名）

Junshi Sakamoto

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Biomembranes and membrane proteins play important roles in all living organisms. This lecture describes
physiological functions and molecular structures of ion pumps, ion channels, drug receptors, solute transporters
and respiratory enzymes.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This lecture expect students to have undergrad-level knowledge of biochemistry, biophysics, and molecularbiology.

Theme(テーマ）

Contents（内容）biomembranes and membraneproteins

two lectures

2. how to handle membrane proteinstwo lectures

3. drug receptors

two lectures

4. ion channels

two lectures1.

signal transduction on
biomembranes

two lectures

6. ion pumps and transporters

two lecturesenergy drancduction and7.
chemiosmosis

three lectures

5.

Course Calendar/Class Topic（授業計画）

8.
9.
10.
11.
12.
13.
14.
General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

15.
lectures and casual oral exams
achieve aims (D), (1) and (3)1. basic knowledge on funcitons and structures of membrane proteins
2. understand physiological importance of biomembranes
3. quantitative understanding of the membrane potential and the ion motive force

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

oral exams at every class

Assignment Instructions（授業外学習（予習・復習）の指示）

two hour review after every class

Keywords（キーワード）

fluid mosaic model, neurotransmitter, protein stereostructure, geneme, electrochemical potential

Required Textbooks（教科書）

hand made (free)

References/Recommended Reading（参考書）

Biology, for Physical Sciences and Engineerings (Shokabo, ISBN978-4-7853-5231-8)

Notes（備考）
Email（電子メールアドレス）

sakamoto@bio,kyutech.ac.jp

Course Name（科目名）

Bioanalytical Chemistry

Instructor Name(担当教員名）

Shinji Sueda

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deals with the latest techniques on bioanalysis methods based on the protein tagging system with afocus on fluorescence labeling and imaging techniques in living cells. It also enhances the development ofstudents' skills in scientific presentation.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is included in a module Functional Proteomics Module .
The students are expected to understand the basic chemistry and biochemistry in advance.

Theme(テーマ）

Course Calendar/Class Topic（授業計画）

Contents（内容）Intodcution and Fundamental of1.
spectroscopy
2. Properties of fluorescent proteinsLecture3. Aplications of fluorescent proteins
Properties and applications of
4.
bioluminescent proteins
Fluoresent labeling with tag-probe5.
systems
Obsevation of cells by fluorescent
6.
microscopy
Reading and explanation of
7.
references: part 1
Reading and explanation of
8.
references: part 2
Reading and explanation of
9.
references: part 3
Reading and explanation of
10.
references: part 4
11. Presentation and discussion: part 1

LectureLectureLectureLectureLectureReading and explanation of references
Reading and explanation of references
Reading and explanation of references
Reading and explanation of references
Presentation and discussion by students

12. Presentation and discussion: part 2 Presentation and discussion by students
13. Presentation and discussion: part 3 Presentation and discussion by students

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

14. Presentation and discussion: part 4 Presentation and discussion by students
15. Presentation and discussion: part 5 Presentation and discussion by students
Each topics are provided by the following formats:
Topics 1-6: Lecture
Topics 7-10: Reading and explanation of references
Topics 11-15: Presentation anad discussion by students

Introduction to Couse Objectives The students are expected to understand bioanalytical methods based on fluorescence imaging and to acquire
the basic presentation skills in scientific fields. Specific goals of this course are as follows:（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1. Understand the mechanisms and the principles of fluorescence labeling and imaging
2. Understand the imaging techinques with fluorescence microscopes
3. Acquire the basic presentation skills in a scientific field

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Your final grade wil be determined based on the presentation of a scientific paper (50%), mini-examination (25%),
and the report on the references (25%).

Assignment Instructions（授業外学習（予習・復習）の指示）

The students are expected to read the teaching materials distributed on a Moodle system in advance. The
participants must find an appropriate scientific paper for presentation by themselves and prepare the materials
for presentation. At least four hours should be spent for preparation per week.

Keywords（キーワード）

Bioanalytical chemistry, Protein tagging system, Florescence analysis, Enzyme reaction, Fluorescence imaging

Required Textbooks（教科書）The teaching materials will be provided on a Moodle system.

References/Recommended Reading（参考書）

Molelcular Biology of the Cell, Sixth edition (Garland Science)
Molecular Cloning, Fourth edition (Cold Spring Harbor Laboratory Press)
Short Protocols in Protein Science (Wiley)

Notes（備考）This course will be held online.

Email（電子メールアドレス）

sueda@bio.kyutech.ac.jp

Course Name（科目名）

Electromagnetic Wave Applied Chemistry

Instructor Name(担当教員名）

Shokichi Ohuchi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Irradiation of a chemical reaction with microwaves, which is one of the electromagnetic waves, accelerates thereaction. Compared with conventional heating, the reaction time is shortened to 1/100 at the same
temperature. Such technologies using microwave energy are attracting attention as energy reduction
technologies and low carbon technologies, and play a role in green innovation. In this lecture, in addition toresearch applying microwave heating to chemical processes, we will explain examples of application tobioprocesses such as cell culture and genetic engineering. The first few lectures will review the organic
chemistry and physical chemistry learned in the undergraduate program.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This lecture is based on the premise that you have taken courses such as organic chemistry, physicalchemistry, thermodynamics, physics (electromagnetics), biology, and biotechnology as undergraduate lectures.

1-2.

Theme(テーマ）

Contents（内容）Chemicals and electromagnetic
waves

Various phenomena when irradiating chemical substances withelectromagnetic waves

Organic electron theory,
thermodynamics
Microwave irradiation effect on
7.
organic reaction
Microwave irradiation effect on
8.
enzyme reaction
Application to chemical processes,
9-10.
substance separation technology
Application to bioprocess,11.
sterilization technology
Application to medical technology,
12.
hyperthermia
Other microwave energy applied
13. technologies
3-6.

Course Calendar/Class Topic（授業計画）

14.
15.
General Course Policies（授業の進め方）

Introduction to Couse
Objectives（授業の達成目標の解説）
CourseObjectives（授業の達成目標）

Organic chemistry and thermodynamics under microwave irradiation
cceleration effect of organic chemical reaction under microwave
irradiation
Acceleration effect of enzyme reaction under microwave irradiationand effect on protein structure
Chemical process technology and substance separation technology
by microwave heating
Application of microwave heating to medical technology
Ｅxamples of industrial use of microwave heating technology
Thermodynamic quantity calculation of protein by using molecular
dynamics

Laws and regulations and safety ofusing electromagnetic waves
Summary

Lecture materials will be distributed each time, and lectures will proceed based on it.
This course aims to help students to develop "Basic skills required for informatics, technology and otherrelated fields." The course is involved in the research and development in interdisciplinary area of
bioinformatics, genomics, proteomics, systems biology and so on.

To understand the phenomena that occur at the molecular level when a chemical substance is irradiated1. with electromagnetic waves
Couse objectives(具体的な授業の達成目標）

To understand molecular motion, intermolecular interactions, and thermal energy as the basis of
2. microwave chemistry
To understand that the use of electromagnetic energy can be used in various industries as an
3. application of microwave chemistry

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

This lecture will be evaluated in the final exam.

Assignment Instructions（授業外学習（予習・復習）の指示）

If you cannot understand the content of the lecture within the time of the lecture, you need to try to review it
according to your ability.
It is important to concentrate on each lecture.
Out-of-class learning is left to your own discretion.

Keywords（キーワード）

Microwave Assisted Chemistry, Organic Chemical Reactions, Bioorganic Chemistry, Thermodynamics, Process
Chemistry, Green Technology, Biotechnology, Protein Engineering, Omics Technology, Chemical Evolution

Required Textbooks（教科書）The materials will be handed out.

References/Recommended Reading（参考書）

・ March's Advanced Organic Chemistry: Reactions, Mechanisms, and Structure, 7th ed., Wiley (2013)

Notes（備考）
Email（電子メールアドレス）

ohuchi@bio.kyutech.ac.jp

Course Name（科目名）

Computation Methods for Molecules

Instructor Name(担当教員名）

Matsuyama Akihiko

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2Soft matter, such as polymers, liquid crystals, surfactant molecules, and gels, is important in the fields of food,medicine and material science. It is also the substance that makes up our bodies, and as a result of various
interactions, the most complex phenomena of life occur.. In this lecture, we will learn statistical mechanical theory
and computer simulation methods for phase separation and phase transition in soft matte, mainly, Polymer and Liquid
Crystals.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This lecture belongs to the Biological Structure Module and teaches the physical basis of the soft matter that makeup living organisms. Understanding the physical properties of soft matter requires understanding of a wide range ofphysics, chemistry, and biology. In this lecture, we will learn how soft matter is treated by statistical mechanics andcomputer simulation.
Theme(テーマ）
Contents（内容）1. Soft Matter(1) Introduction of soft matter

2. Statistical physics of single polymer chain (2)-(3) Statistical physics of Single polymer chain
3. Ideal chain
4. Theory of polymer solutions(4)-(7) Physics of Polymer solutions and polymer blends

5. Phase separatiuons of polymer solutions phase separations and dynamics
6. Spinodal decomppositions
Course Calendar/Class Topic（授業計画）

7. Nucleation and growth
8. Physics of Liquid Crystals(8)-(14) Physica of liquid crystals

9. Order parameters
10. Theory of Liquid Crystalline solutions
11. Onsager theory
12. Nematic-isotropic phase transitions
13. Maier-Saupe theory
14. Smectic liquid crystals

General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）(15) Current topics in soft matter
15. Recent topics of soft matter
Lecture (It will be an Online Class COVID19.) See Moodle for more informations.
The objectives is to learn the basics of soft matter substances, which are expected to be applied to a wide range offields such as life sciences and nanomaterials.
1. Polymer
2. Liquid Crystal
3. Soft Matter

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

ReportAssignment Instructions（授業外学習（予習・復習）の指示）

As a preparatory study, prepare 2 hours a week.

Keywords（キーワード）

polymer, liquid crystal, soft matter

Required Textbooks（教科書）

Original text will be prvided.

References/Recommended Reading（参考書）

search Soft Matter Physics

Notes（備考）

See Moodle for more informations.

Email（電子メールアドレス）

Course Name（科目名）

IC Design

Instructor Name(担当教員名）

Yutaka ARIMA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The purpose of this class is to understand the basic structure, functional configuration, design method, etc. ofan IC (Integrated Circuit) through an actual layout design experience. After explaining the basic knowledge(element structure, operating principle, etc.) necessary for IC design, we will proceed with the explanation along
the IC design flow (functional design, circuit design, layout design, verification). On the final day, the verified
layout pattern (final form of IC design data) is completed. Students can select the circuit to be designed bythemselves. After understanding the design method for each step explained in the class, work on designing andverifying each integrated circuit. The design tools (CAD) necessary for design and verification are installed andused on their own notebook PCs, so they can perform design work outside of class hours. In this lesson,
guidance will be given mainly on layout design.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This class teaches the general basic knowledge of ICs (integrated circuits), including the structure and operation
principles of semiconductor devices, manufacturing methods, and design techniques, and has the feature ofdeepening their understanding through actual layout design experiences. . It is desirable, but not required, thatstudents take the following subjects or have equivalent basic knowledge. Electronic circuits, semiconductor
engineering.
Theme(テーマ）

Contents（内容）1. Class guidance
Semiconductor element and CMOS
2.
circuit
IC manufacturing flow, various
3.
manufacturing equipment
4. IC design flow, various design methods
5. Functional design and circuit design
6. Design tools (CAD)
Course Calendar/Class Topic（授業計画）

7. Circuit design (netlist generation)
8. Layout pattern design rules
9. Layout pattern design (element level)
10. Layout pattern design (gate level)
Layout pattern design
11.
(circuit configuration)
Layout pattern design
12.
(IC level configuration)
13. Verification of layout pattern (DRC)
14. Verification of layout pattern (LVS)

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. Test bench (test specification)
Explains the basic knowledge of semiconductor device structure and CMOS circuit which are indispensable fordesigning IC (Integrated Circuit), and explains the flow of IC manufacturing and design. Then, according to thedesign flow, the explanation will proceed in the order of functional design, circuit design, function verification,layout pattern design, layout pattern verification using DRC and LVS. In this lesson, layout design will be taught
in detail. Finally, the test methods required to verify the functional performance of the designed integrated
circuit are described.
This course will be taught in Japanese. The course materials are mainly given in Japanese.

In order to understand the concrete means of realization in connection with one of the goals of learning andeducation in the electronic field (3) ̀̀ Construction of information systems with advanced functions that
Introduction to Couse Objectives evolved the principle of computers, '' The goal is to acquire general knowledge of circuit engineering.
This aims to acquire the basic learning and education goal of the Faculty of Information Engineering (B) "Basic（授業の達成目標の解説）
academic skills required in information science, engineering and various fields".

Couse objectives(具体的な授業の達成目標）

1. Understand the structure and manufacturing method of IC (integrated circuit).
2. Understand IC (integrated circuit) design techniques.
3. Understand the characteristics of semiconductor devices and the configuration of CMOS circuits.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

For the above-mentioned achievement targets (1) and (2), the degree of understanding is evaluated based on
the design data (final layout pattern) of the integrated circuit (70%). In addition, (3) is evaluated in the test
specification for functional performance evaluation of the designed circuit (30%). As described above, the degreeof understanding is evaluated by the design layout pattern of the integrated circuit and the test specification, sothat the term-end test is not performed.

Assignment Instructions（授業外学習（予習・復習）の指示）

The materials used in the lecture will be posted on Moodle, so please download and prepare in advance, andbring them with you on the day of the class. After the class, review the material and organize and reconfirm
what you have learned. If you have any questions, be sure to ask them or do your own research. Students are
expected to set aside 4 hours per week for preparatory study.

Keywords（キーワード）

Semiconductor, integrated circuit, IC, design, electronic circuit

Required Textbooks（教科書）

None.

References/Recommended Reading（参考書）

None. Introduce during the lecture if necessary.

Notes（備考）Distance learning courses (both synchronous and asynchronous). Synchronous type is Zoom lectures. The
maximum number of remote classes is 15 (face-to-face classes will be conducted according to the situation).

Email（電子メールアドレス）

arima@cms.kyutech.ac.jp

Course Name（科目名）

Semiconductor topic seminar

Instructor Name(担当教員名）

Kazuyuki Nakamura

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Semiconductors are the base material of various electronic elements (parts), and many faculty members of thethree campuses of the KIT are engaged in education and research on various related technologies. There arealso many joint research labortories on related themes. In this lecture, these teachers will collaborate andprovide the latest technology and topics in a relay system using a TV lecture system that connects the remote
campuses. Specifically, in addition to semiconductor element processing methods (process fields), electronic
device structures (device fields), large-scale integrated circuits and LSIs (system fields), micro-mechanicaldevices MEMS (Micro Lecture on Electro-Mechanical Systems) (MEMS field).
[Notes] The classes will be held on Thursday classes common to the three campuses for three-campus
cooperative lectures.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Overview
Manufacturing method of 3D
2. (stacked)
LSI
3. Semiconductor surface nanotechnology
4. LSI test and power analysis
Solid material devices and5. numericalanalysis
6. Organic semiconductor devices
Course Calendar/Class Topic（授業計画）

7. Digital integrated circuit
Medical and biological applications
8. ofmicrofluidic devices
9.

Switching power supply integration
technology

Reconfigurable devices andapplications
11. Real-time 3D distance sensor
Medical and bio-application of
12.
MEMS
13. MEMS and thermal engineering
10.

14. Memory LSI and applications

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. High-speed interface design
The three campuses are connected by a TV lecture system and a remote lecture is conducted. Students
should first check how to take the course.
14 professors give lectures on different themes each time. Therefore, even if you do not register, you canlisten to only the topics you are interested in.

Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1.
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

Evaluate at least one report from each field of process, device, system, and MEMS, and one report from any
field, for a total of five reports. (No final exam will be conducted)

Assignment Instructions（授業外学習（予習・復習）の指示）

Two hours a week for lecture preparation and review (making reports) are required.

Keywords（キーワード）
Required Textbooks（教科書）No textbook is used in this lecture. Some materials are supplied in class.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

nakamura@cms.kyutech.ac.jp

Course Name（科目名）

Quantitative Biology

Instructor Name(担当教員名）

Yusuke Morimoto

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Quantitative biology is a general term for methods used to understand life sciences through quantitative
analysis of biological phenomena. In this lecture, we will study the basic theory of quantitative biology andintroduce various measurement and analysis methods. In addition, the latest research results in related fields
will be introduced.
Since this lecture includes data handling, it is assumed that students will have taken laboratory courses inundergraduate school. A general basic knowledge of physics, biology, and chemistry is desirable, but notrequired. Related courses include those related to biophysics, biochemistry, and statistics.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Contents（内容）1. Overview
2. Size
Concentrations and Absolute
3.
Numbers
4. Energies and Forces
5. Rates and Duration

Course Calendar/Class Topic（授業計画）

6. Quantitative Measurement of Cells
Quantitative Measurement of
7.
Multicellular Systems
Quantitative Measurement
8.
Technology
9. Summary
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

15.
Mainly lecture style. Exercises to check understanding and interactive discussions will be included.
The course may be conducted by remote learning.
The goal of this lecture is to understand the quantitative analysis of physical and chemical quantities that playa role in biological phenomena, and to come into contact with the latest research trends in this field.
Specifically, the following items are targeted.
1. Understand the basics of physical and chemical quantities related to biological phenomena
2. Understand measurement methods for quantitative measurement of biological phenomena
3. Understand analytical methods for analyzing measurement data of biological phenomena.
4. Study about the latest research trends in quantitative biology

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Your overall grade in the class will be decided based on exercises and final report.

Assignment Instructions（授業外学習（予習・復習）の指示）

Students are expected to set aside 4 hours per week for preparation. A survey of research trends in the fieldis recommended.

Keywords（キーワード）

Quantitative Biology, Biophysics, Statistics, Optogenetics, Fluorescence Imaging

Required Textbooks（教科書）No specification.

References/Recommended Reading（参考書）

細胞の物理生物学 Rob Phillips, Jane Kondev, Julie Theriot 著（共立出版）
数でとらえる細胞生物学 Ron Milo, Rob Phillups 著（羊土社）
定量生物学 小林徹也 編（化学同人）

Notes（備考）
Email（電子メールアドレス）

yvm001@bio.kyutech.ac.jp

Course Name（科目名）

Knowledge and Thinking Process Modeling

Instructor Name(担当教員名）

Hidenobu KUNICHIKA

Course intended for（対象学年）

1ｓｔ , 2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course provides a methodology for estimating users' thought by a computer. Specifically, methods of
estimating and storing the thought process and the knowledge of a user by using computer is provided.
Moreover, as an example of using the result of user modeling, a method in which a computer constructs a usermodel and adjusts the behavior is also described.

Course Description（授業の概要）

This course relates to both Basis of Artificial Intelligence and AI Programming.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）User modeling and knowledge
engineering
Methods of user modeling and2.
applications
1.

3. Intelligent Tutoring Systems
4. Intelligent Tutoring Systems
5. Recommender Systems
6. Midterm report
7. Programming
Course Calendar/Class Topic（授業計画）

8. Programming
9. Programming
10. Programming
11. Programming
12. Programming
13. Writing a report
14. Writing a report
15. Reviewing other reports

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

Lectures and exercises will be done asynchronously (15 lectures in total). Attendance will be counted if you
watch all the videos and report your progress by the deadline. Instead of a final exam, you need to submit areport and questions/comments on other reports.
In order to achieve the goals "Development of a new mechanism of intelligent information processing in whichhumans and computers cooperate" for the Division of Artificial Intelligence and "Utilization of the latest
information technology and business-oriented research and development based on real-world needs" for theDivision of Creative Informatics, the following items are the objectives of this course. These aim to acquirecommon goal (B) "Basic academic ability required in information science and engineering and various fields" forGraduate School of Computer Science and Systems Engineering.
1. Understanding methods of user modeling
2. Understanding methods of using the results of user modeling3.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

The degree of understanding , presentations, the participation in discussion will be assessed.

Assignment Instructions（授業外学習（予習・復習）の指示）

Examine the keywords mentioned in the course before and after by using related books or the Web. Note thatfour hours a week for preparations are necessary.

Keywords（キーワード）

User modeling, Knowledge representation, Thought process, Dialogue systems

Required Textbooks（教科書）
References/Recommended Reading（参考書）
Notes（備考）Any changes will be announced on moodle.

Email（電子メールアドレス）

kunitika@ai.kyutech.ac.jp

Course Name（科目名）

High Reliability Design

Instructor Name(担当教員名）

WEN Xiaoqing

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Test for determining whether a manufactured LSI circuit operates properly is extremely important for the
reliability of the system to which the circuit is applied. Due to the ultra-large scale and ultra-miniaturization of
LSI circuits, low test quality and high test costs are becoming a major problem. This course outlines the role oftest design in the LSI design and the manufacturing process. It also covers the basics of test methods, test
genetation, and design for testability.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This lecture belongs to the LSI module, and covers the test part of LSI design, manufacturing, and test. Since it
is impossible to completely prevent errors from occurring in design and manufacturing, it is necessary toaccurately check whether the manufactured LSI circuit operates properly and prevent defective products fromleaking to the market. In testing, it is required to have the basic knowledge of targeted logic circuits andalgorithms on which test methods are based. It is assumed that undergraduate courses, such as "Computer
Arichitecture", "Logic Design", "Integrated System Design", and "Integrated System Design Exercise" havebeen taken.
Theme(テーマ）

Contents（内容）1. Introduction to LSI Test
2. LSI Test Basics
3. Fault Models
4. Fault Simulation
5. Testability Analysis
6. Basics of Combinational ATPG
Course Calendar/Class Topic（授業計画）

7. Major ATPG Algorithms
8. Mid-Term Eaxm
9. Basics of Design for Testability
10. Built-In Self-Test
11. Test Compression
12. Low-Power Test I
13. Low-Power Test II
14. Summary

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

15. Final Exam
During class hours, lectures will be given according to the above schedule. You will also be required to submit
your homework report several times. In addition, mid-term and final exams will be conducted. This first half ofthe course will be taught in English and the second half of the course will be taught in Japanese. 20% of thecourse materials are given in Japanese and 80% of the course materials are given in English.
In this course, in order to realize the learning and educational objective of the Department of Creative
Informatics, (1) "utilize the latest information technology for practical research and development to meet realworld needs", the goal is to learn the LSI test technology that affects the reliability of semiconductor integrated
circuits that form the foundation of modern industry and society. This course controbuts to the raelization of
the common learning and educational objective of Graduate School of Computer Science and Systems
Engineering, (B) "academic skills required in each field related to information science and engineering".
1. Understand the importance of LSI test in the semiconductor industry
2. Understand the basic technology of LSI test (fault model, test generation, design for testability)
3. Understand advanced technologies in LSI test (test compression, low power test, high quality test)

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

For (1) to (4), grade evaluation will be based on the total score of the mid-term exam (out of 50 points) and thefinal exam (out of 50 points).

Assignment Instructions（授業外学習（予習・復習）の指示）

By the day before taking the class, download the materials for the lecture from the designated site and performthe preparation study (preparation). At least 4 hours need to be spent on preparation every week. If you haveany questions, please send them to lecturers in advance (wen@cse.kyutech.ac.jp, holst@cse.kyutech.ac.jp). In
addition, A4 papers need to be used for homework reports.

Keywords（キーワード）

Test, Fault, Test Pattern, ATPG, Scan Design, BIST

Required Textbooks（教科書）

References/Recommended Reading（参考書）

1. T. Yoneda, S. Kajiwara, and T. Tsuchiya, "Dependable System", Kyoritsu Publishing.
2. L.-T. Wang, C.-W. Wu, and X. Wen, (Editors), "VLSI Test Principles and Architectures: Design for Testability",San
Elsevier.

Notes（備考）

Remote course with Zoom

Email（電子メールアドレス）

Xiaoqing Wen (wen@cse.kyutech.ac.jp), Stefan Holst (holst@cse.kyutech.ac.jp)

Course Name（科目名）

Mechanism and Kinematics

Instructor Name(担当教員名）

Takahiro ITO

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
We will take up a wide range of mechanisms from robots, vehicles to micro electro mechanical systems, andexplain their mechanisms and movements.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Since we are assuming mechanical design, manufacturing, and measurement technology, which are mainly
represented by mechatronics and MEMS technology, students are supposed to have taken specialized courses
related to mechanical and electronic design, manufacturing, and measurement technology. Alternatively,
preparation for basic knowledge equivalent to the above is a prerequisite. Therefore, it is a prerequisite to takethe following undergraduate lectures. "Information and communication network" (computer, semiconductor
manufacturing) "Information and communication network training" (network technology) "Basic control II"(modeling and design of controlled objects),
Theme(テーマ）

Contents（内容）1. Introduction to Mechatronics
2. Introduction to Vibration Studies
Basic knowledge of vehicle
3.
engineering
4. High-speed rail bogie design
5. Car movement and design
6. Railroad and mechatronics
7. Railroad model mechatronics
8. Introduction to micromachines
Course Calendar/Class Topic（授業計画）

9. Mico mechanisms
10. Introduction to MEMS
11. MEMS manufacturing process
12. MEMS design method
13. Optical MEMS
14.

Mechatronics / MEMS Technical
Exercise

Latest trends from international
15. conferences and conference
presentations
General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Perform in a seminar format using a textbook. Exercises such as discussions will be held as appropriate todeepen understanding between lectures.
In relation to learning and education goals, students will acquire the common item (B), the information system
major, the technical development of (1) (2) (3) in the field of mechanical information engineering, and thesystem evaluation technology for system construction. The following items are the goals to be achieved.
1. Understanding mechatronics and micromachines
2. Understand the mechanism and vibration phenomenon.
3. Can make research plans for mechatronics and MEMS.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Attendance and submission of reports are mandatory, and the degree of achievement of the achievement goals
will be evaluated based on the degree of understanding of the part in charge of the seminar, explanation
contents, prepared materials, questions and answers, homework, and reports.

Assignment Instructions（授業外学習（予習・復習）の指示）

We will give instructions as appropriate, so be proactive.

Keywords（キーワード）

Micromechanisms, MEMS

Required Textbooks（教科書）"Mechanism and Kinematics," written by Teru Hayashi and Takahiro Ito, Corona-shya (In Japanese), ISBN9784-339-04596-3

References/Recommended Reading（参考書）"Optical MEMS," written by Renshi Sawada, Kazuhiro Hane, and Eiji Higurashi, Ohm-shya (In Japanese), ISBN
978-4-274-03589-0

Notes（備考）
Email（電子メールアドレス）

ito@mse.kyutech.ac.jp

Course Name（科目名）

Advanced Computer Graphics Ⅱ

Instructor Name(担当教員名）

Masaki Oshita

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This class covers advanced techniques on computer graphics and animation. The students can learn practicaltechniques through lectures and programming exercises.
This class is taught in Japanese. Although some materials have English version, most of materials are Japanese
only. Reports in Japanese or English are acceptable. A foreign student who are not so fluent in Japanese canstill take this class. The students also must have fundamental programming skills of C++. Basic knowledge on
computer graphics and OpenGL programming are not mandatory but desirable.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

The students who do not have basic knowledge on computer graphics and OpenGL programming arerecommended to take Advance Computer Graphis I before this class.

Theme(テーマ）

Contents（内容）1. Fundamentals in Computer Graphics
2. Fundamentals in OpenGL Programming
3. Camera Control
4. Geometry Models
5. Shadow Drawing
6. Keyframe Animation (1): Position
7. Keyframe Animation (2): Orientation
8. Physics Simulation
9. Collision Detection and Picking
Course Calendar/Class Topic（授業計画）

10. Character Animation (1): Human Models
11. Character Animation (2): Forward Kinematics
Character Animation (3): Inverse
12. Kinematics and PostureInterpolation
Character Animation (4): Motion
13. Interpolation, Connection, andTransition
Character Animation (5): Motion
14. Generation, Deformation, andControl
15. Advanced Rendering Techniques

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

The class materials such as lecture videos and exercises will be available before class. During class. The
questions about the lectures and programming exercises will be answered during class. The students will be
required to work on programming exercises and submit reports after class.
The objectives are as follows,
1. To learn advanced techniques on computer graphics and be able to apply them for application softwaredevelopment.
2.
3.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Participation and quizzes during classes (20%) and programming exercises and reports (80%).

Assignment Instructions（授業外学習（予習・復習）の指示）

The students should obtain class materials and read them before class.
The students should do programming exercises and submit reports after class.

Keywords（キーワード）

Compute graphics, OpenGL, computer animation, application software development

Required Textbooks（教科書）

None. Class materials are available on the class webpage.

References/Recommended Reading（参考書）

Refences on each topic will be introduced during class.

Notes（備考）The students must spend at least 4 hours per week for pre-clss and post-class study.

Email（電子メールアドレス）

oshita@ces.kyutech.ac.jp

Course Name（科目名）

System-LSI Design

Instructor Name(担当教員名）

Kazuyuki Nakamura

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
In order to learn the circuit design technology of the system LSI in the analog / digital (A/D) mixture era, PLL(phase synchronization loop :Phase-Locked-Loop) circuit will be taken as a subject of the design target. An
analog circuit design tools (ns-spice) will be employed to design the PLL circuit.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

They learn MOS transistor and CMOS logic gate, the circuit components of PLL (phase frequency detector,
voltage controlled oscillator, etc.) and design and simulate them by using SPICE to understand the operations.

Theme(テーマ）

Contents（内容）1. Basics of Circuit Simulations

2.

Analog / Digital Mixed Circuit
Design using SPICE

3.

Overview of PLL Circuit and its
Appliations

Design of PLL Components I
4. （Phase-Frequency Detector,
Frequency Divider）
Course Calendar/Class Topic（授業計画）

Design of PLL Components II
5. （Low-pass Filter, Charge-pump,
Voltage Controlled Oscillator)
6.

Whole PLL Operation using Nsspice

7.
8.
9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15.
At first, students learn usage of analog digital mixture circuit simulator (ns-spice) working on a PC. Finally they
develop whole phase locked loop (PLL) and perform whole simulation.

Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

1.
2.
3.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）
Assignment Instructions（授業外学習（予習・復習）の指示）

The different specifications for the PLL design will be given to each student as a final report subject.
Confirming stable lock operation of PLL by whole simulation by spice and submitting the report of the result arecondition of the obtaining the unit.
Four hours a week for lecture preparation and review are required. Final PLL Design report will be required.

Keywords（キーワード）

SI, Circuit Design, SPICE, Verilog, VHDL, Circuit Simulator, Phase-Locked Loop, Analog / Digital Mixed Circuits

Required Textbooks（教科書）No textbook is used in this lecture. Some materials are supplied in class.

References/Recommended Reading（参考書）

１．B.Razavi, Design of Analog CMOS Integrated Circuits , McGraw-Hill Companies 2003
２．N.Weste, D.Harris, CMOS VLSI Design: A Circuits and Systems Perspective , Addison Wesley 2010

Notes（備考）
Email（電子メールアドレス）

nakamura@cms.kyutech.ac.jp

Course Name（科目名）

System Architecture

Instructor Name(担当教員名）

YOSHISDA Takaichi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course deals with the basic concepts of software architecture and distributed system architecture as acase examples of system architecture.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）You are required to have learned courses related to software engineering, operating systems, and computer
networks.
Theme(テーマ）

Contents（内容）1. Introduction
2. Overview of Software Architecture
3. Quality Attributes
4. Architectural Pattern
5. Designing the Architecture
6.

Documenting Software
Architectures

7. Analyzing Architectures
Course Calendar/Class Topic（授業計画）

8. Software Product Lines
9. Introduction to Distributed Systems
10. Design Issues
Inter Process Communication andRemote Method Invocation
Distributed File Systems and
12.
Naming11.

13. Concurrency Control
14. Reliability
15. Security

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Lectures will be given according to the materials distributed in advance.
To understand actual examples of software architecture and distributed system architecture, a case study
homework will be assigned.
This course will be taught in Japanese. The course materials are mainly given in English.
The goals of this course are to understand
1. Design, analysis and documentation of software architecture.
2. Architecture of distributed systems.
3. Issues and solutions of distributed computing.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Your overall grade in this course will be decided based on mid-term repot (Case study on software architecture
design: 50%) and final report (Case study on distributed middleware: 50%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Read the course material in detail. If you have any point you cannot understand, study the point before eachlecture. You are required to take four hours a week for preparation.

Keywords（キーワード）

Functionality and Quality Attributes, Design Pattern, Software Life Cycle, Network Transparency, Transaction
Processing

Required Textbooks（教科書）

References/Recommended Reading（参考書）

Software Architecture in Practice, Second Edition, Len Bass, Paul Clements, Rick Kazman, Addison Wesley,
2003.
Engineering Distributed Objects, Wolfgang Emmerich, John Wiley & Sons, 2000.
Distributed Systems, Principles and Paradigms, Second Edition, Andrew S. Tanenbaum, Maarten Van Steen,
Persons Education, 2007.

Notes（備考）This cource will be taught in Japanese. However, all of the course materials are in English.

Email（電子メールアドレス）

takaichi@ai.kyutech.ac.jp

Course Name（科目名）

Advanced Software Engineering

Instructor Name(担当教員名）

Keiichi Katamine

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Software engineering is a discipline or technology for improving productivity, maintainability and reliability
by introducing an engineering approach to the design, development and operation of highly complex
software. This lecture teaches basic knowledge and ideas about software engineering.

Course Description（授業の概要）

As for this course, it is desirable to have learned a software design and an object-oriented methodology.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Overview of Software Engineering
2. Software Development Process
3. Project Management
4. Software Analysis
5. Requirements Analysis
6. Structured Analysis
Course Calendar/Class Topic（授業計画）

7. Object Oriented Analysis
8. Architecture Design
9. Module Design
10. Programming
11. Test and Verification
12. Software Maintenance and Reuse
13. Engineer Education
14. Summary

General Course Policies（授業の進め方）

15. Report Issues and Explanation
This course focuses on lectures. It also involves group works during lectures to understand the contents.
In addition, it gives the exercise appropriately.
Lecture videos and exercises are provided on the moodle. And the questions about lectures and exercises
are replied on line.
This course will be taught in Japanese. The course materials are mainly given in Japanese.

The purpose of this course is to help students understand software requirements analysis, design, andIntroduction to Couse Objectives implementation. In addition, the goal is to acquire the technology to build an information system in order to（授業の達成目標の解説）
solve problems.
CourseObjectives（授業の達成目標）

understand the basic contents of software requirements analysis, design and implementation
development process.
understand the basic contents of modeling technology and re-engineering technology to solve2.
problems by applying information systems.
understand the basic contents of the system structure and project management to develop an
3.
information system.
1.

Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Evaluate the final report (80%) and the small report (20%) that is given during the lecture.

Assignment Instructions（授業外学習（予習・復習）の指示）

Review the previous content at the start of the lecture and review it. At that time, it is desirable toconsider whether it can be used in situations such as the methods and techniques learned during thelecture. As a preparatory study, prepare 4 hours a week.

Keywords（キーワード）

Software Development Process, Requirements Analysis, Modeing, Project Management, PSP/TSP

Required Textbooks（教科書）

References/Recommended Reading（参考書）

N. Takahashi, K. Maruyama, Software Engineering, Morikita-Shuppan
IEEE Computer Society, Guide to the Software Engineering Body of Knowledge(SWEBOK)
Project Management Institute, A Guide to the Project Management Body of Knowledge(PMBOK Guide)

Notes（備考）
Email（電子メールアドレス）

katamine@ci.kyutech.ac.jp

Course Name（科目名）

Advanced Software Engineering

Instructor Name(担当教員名）

Keiichi Katamine

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
Software engineering is a discipline or technology for improving productivity, maintainability and reliability byintroducing an engineering approach to the design, development and operation of highly complex software. This
lecture teaches basic knowledge and ideas about software engineering.

Course Description（授業の概要）

As for this course, it is desirable to have learned a software design and an object-oriented methodology.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Overview of Software Engineering
2. Software Development Process
3. Project Management
4. Software Analysis
5. Requirements Analysis
6. Structured Analysis
Course Calendar/Class Topic（授業計画）

7. Object Oriented Analysis
8. Architecture Design
9. Module Design
10. Programming
11. Test and Verification
12. Software Maintenance and Reuse
13. Engineer Education
14. Summary

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目標）

15. Report Issues and Explanation
This course focuses on lectures. It also involves group works during lectures to understand the contents. In
addition, it gives the exercise appropriately.
Lecture videos and exercises are provided on the moodle. And the questions about lectures and exercises are
replied on line.
This course will be taught in Japanese. The course materials are mainly given in Japanese.

The purpose of this course is to help students understand software requirements analysis, design, andIntroduction to Couse Objectives implementation. In addition, the goal is to acquire the technology to build an information system in order to（授業の達成目標の解説）
solve problems.
understand the basic contents of software requirements analysis, design and implementation
development process.
understand the basic contents of modeling technology and re-engineering technology to solve problems
2.
by applying information systems.
understand the basic contents of the system structure and project management to develop an
3.
information system.
1.
Couse objectives(具体的な授業の達成目標）

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Evaluate the final report (80%) and the small report (20%) that is given during the lecture.

Assignment Instructions（授業外学習（予習・復習）の指示）

Review the previous content at the start of the lecture and review it. At that time, it is desirable to consider
whether it can be used in situations such as the methods and techniques learned during the lecture. As a
preparatory study, prepare 4 hours a week.

Keywords（キーワード）

Software Development Process, Requirements Analysis, Modeing, Project Management, PSP/TSP

Required Textbooks（教科書）

References/Recommended Reading（参考書）

N. Takahashi, K. Maruyama, Software Engineering, Morikita-Shuppan
IEEE Computer Society, Guide to the Software Engineering Body of Knowledge(SWEBOK)
Project Management Institute, A Guide to the Project Management Body of Knowledge(PMBOK Guide)

Notes（備考）
Email（電子メールアドレス）

katamine@ci.kyutech.ac.jp

Course Name（科目名）

Project Managemnet

Instructor Name(担当教員名）

Keiichi Katamine, Masanobu Umeda, Keita Asaine

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course explains the concept of general project management and its basic principles, and lectures on the
project management for software development based on the concept. It also lectures on critical chain project
management.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）In this course, it is desirable to have understood systems engineering, software engineering methodology suchas object oriented analysis and design, software engineering including development process and software
process, and system technology forcus on software engineering.
Theme(テーマ）

Contents（内容）1. Introduction: Requirements Analysis
2. Introduction: Conceptual Design

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

3. Introduction: WBS and Project Plan
Modern Project Management:
4.
Project Plan
Modern Project Management: Time
5.
Management
Modern Project Management:
6.
Communication Management
Modern Project Management:
7.
Integration Management
Modern Project Management:
8.
Measurements and Analysis
Modern Project Management: Risk
9.
Management
Modern Project Management:
10.
Quality Management
Critical Chain Project Management:
11.
Theory of Constraints
Critical Chain Project Management:
12. Synchronization and Resource
Management
Critical Chain Project Management:
13.
Critical Chain
Critical Chain Project Management:
14.
Buffer Management
15. Presentation of Project Exercise
Lectures and assignments. Lecture materials and assignments are provided on the moodle. And it replies
questions about them on line. This course will be taught in Japanese. The course materials are mainly given in
Japanese.
The following items are the targets.
1. understand the meaning of the project management, its features, and the importance of teamwork.
2. understand and implement how to estimate works and how to make a project plan.
3. understand the concepts of the TOC and Critical Chain Project Management.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Evaluate based on the contents of the reports and the exercise products.

Assignment Instructions（授業外学習（予習・復習）の指示）

Borrow books related to lectures and use them for preparation and review. Be sure to paricipate actively
outside of the lecture hours because you perform project exercise as a group work.

Keywords（キーワード）

Project Management, Project Process, Project Plan, Team Building, Risk Management, Quality Management,
TOC, Critical Chain Management

Required Textbooks（教科書）
References/Recommended Reading（参考書）

Project Management Insitute: A Guide to the Project Management Body of Knowledge(PMBOK Guide)
Watts S. Humphrey: TSP Leading a Development Team

Notes（備考）
Email（電子メールアドレス）

katamine@ci.kyutech.ac.jp

Course Name（科目名）

Knowledge and Thinking Process Modeling

Instructor Name(担当教員名）

Hidenobu KUNICHIKA

Course intended for（対象学年）

1ｓｔ , 2nd or 3rd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2This course provides a methodology for estimating users' thought by a computer. Specifically, methods of
estimating and storing the thought process and the knowledge of a user by using computer is provided.
Moreover, as an example of using the result of user modeling, a method in which a computer constructs a usermodel and adjusts the behavior is also described.
This course relates to both Basis of Artificial Intelligence and AI Programming.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. User modeling and knowledge engineering
2.

Methods of user modeling andapplications

3. Intelligent Tutoring Systems
4. Intelligent Tutoring Systems
5. Recommender Systems
6. Midterm report
7. Programming
Course Calendar/Class Topic（授業計画）

8. Programming
9. Programming
10. Programming
11. Programming
12. Programming
13. Writing a report
14. Writing a report
15. Reviewing other reports

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

Lectures and exercises will be done asynchronously (15 lectures in total). Attendance will be counted if you
watch all the videos and report your progress by the deadline. Instead of a final exam, you need to submit areport and questions/comments on other reports.
In order to achieve the goals "Development of a new mechanism of intelligent information processing in whichhumans and computers cooperate" for the Division of Artificial Intelligence and "Utilization of the latest
information technology and business-oriented research and development based on real-world needs" for theDivision of Creative Informatics, the following items are the objectives of this course. These aim to acquirecommon goal (B) "Basic academic ability required in information science and engineering and various fields" forGraduate School of Computer Science and Systems Engineering.
1. Understanding methods of user modeling
2. Understanding methods of using the results of user modeling3.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

The degree of understanding , presentations, the participation in discussion will be assessed.

Assignment Instructions（授業外学習（予習・復習）の指示）

Examine the keywords mentioned in the course before and after by using related books or the Web. Note thatfour hours a week for preparations are necessary.

Keywords（キーワード）

User modeling, Knowledge representation, Thought process, Dialogue systems

Required Textbooks（教科書）
References/Recommended Reading（参考書）
Notes（備考）Any changes will be announced on moodle.

Email（電子メールアドレス）

kunitika@ai.kyutech.ac.jp

Course Name（科目名）

Real Time System

Instructor Name(担当教員名）

Masanobu KOGA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2More efficient production of high-precision and high-quality product is required in the industry. It becomes
more important to design the product based on the high-precision model which represents the physicalphenomena more accurately. Because more complex computation is required for the design, it is essential touse CAD software which helps us from design process to manufacturing process. Although CAD software isused as black-box commonly, this course deals with how CAD software works and how to implement it in orderto deepen understanding and enhance application skills of CAD software. And the data processing for
manufacturing process and real-time process are explained in the couse.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This couse belongs to the software module and deals with how CAD for control systems works, how to
implement CAD for control systems, and real-time process. Students are expected to have learned basic
numerical analysis, basic theory of control systems, and C programming language.
Theme(テーマ）

Contents（内容）1. CAD for control systems
Processor of languages fornumerical computation
Data type and format for numerical
3.
computation
Error evaluation in numerical
4.
computation
2.

5. Matrix computation (1)6. Matrix computation (2)7. Computation for polynomials
Course Calendar/Class Topic（授業計画）

8. Numerical computation for ODE
9. Simulation of control systems
10. Simulation based on block diagrams
11. Introduction to embedded system
Periodic execution of real-time
tasks
Implementation of real-time control
13.
systems
Numerical computation in next14.
generation
12.

15. Explanation of final examination
General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

Mainly lecture-based course with imposing reports assignments
This course has the goal of acquiring the basic knowledge of software for control systems. It aims to achieve
the goal of acquiring the knowledge and skills for research and development based on the requirements in thesociety using the current information technology.
1.
2.
3.

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Report assignments（60%）, term-end exam or final report assignment（40%)

Assignment Instructions（授業外学習（予習・復習）の指示）

Students are expected to take more than four hours for homework every week.

Keywords（キーワード）

Simulation, real-time system, data processing

Required Textbooks（教科書）

None (Instructor will supply prints in class)

References/Recommended Reading（参考書）

Masanobu Koga, MaTX for control and numerical analysis, tokyo denki university press

Notes（備考）

None

Email（電子メールアドレス）

koga@ces.kyutech.ac.jp

Course Name（科目名）

PBL Cloud System

Instructor Name(担当教員名）

Noriyuki Kushiro

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Credits（単位数）2
In this course, basic technologies required for cloud computing and PBL(system analysis and design methods, project management methods etc.)
are lectured at the first sections. After that, students desing and implement a system with cloud computer technologies in mini-PBL sections.

This course is a lecture belonging to practical cloud computing modules. The sutudents, who attend this lecture, are expected to take "Advanced
project learning for cluod computing".

Theme(テーマ）

Contents（内容）1. Guidance for the lecture and overview for cloud computing
2. System Development Process
3. Methods for Requirement Analysis
4. Mehod for System analysis
5. Mehod for System design
6. No SQL
Course Calendar/Class Topic（授業計画）

7. Basic technologies for WEB application 1
8. Basic technologies for WEB application 2
9. Methods for Software testing1
10. Methods for Software testing2
11. Infrustructure for Cloud computing
12. PBL 1
13. PBL 2
14. PBL 3

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

15. Presentation for Results of PBL
The class wiil be adovanced on the above course calender with PBL style, in which each topic is discussed by a small gourp of students andteachers.
The aim of the lecture is that acheving basic skills for "project-based research and development to nourish ability for solving problems andcollaboration".
In the lecture, the students are expected to experience system development in PBL, and to master practical skills for system design and project
management.
1.
2.
3.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The students are evaluated by portfolios for each topic, and final portfolio after the Mini-PBL, and agressiveness to the lecture and PBL,

Assignment Instructions（授業外学習（予習・復習）の指示）

The students are expected 3 hours preparations for each topic. The class provides the students handouts and video teaching materials for their
preparation.

Keywords（キーワード）

System development, Project management, Requirement analysis, System design mehod, Cloud computing

Required Textbooks（教科書）Doug Rosenberg and Kendall Scott: Use Case Driven Object Modeling withUML, A Practical Approach by Doug Rosenberg Kendall Scott, AddisonWesley Professional, 1999

References/Recommended Reading（参考書）

Notes（備考）
Email（電子メールアドレス）

kushiro@ai.kyutech.ac.jp

Course Name（科目名）

Advanced OS and Virtualization

Instructor Name(担当教員名）

Kenichi Kourai

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
The purpose of this course is to provide the overview of cloud computing, its technical background,virtualization, and operating systems. The class deals with actual Linux kernel and hypervisor to understandthe state-of-the-art of these systems software.

Course Description（授業の概要）

It is desirable to have the basic knowledge of operating systems and the C language.
Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Introduction

Introducing this course

2. Overview of cloud computing

Providing the overview of cloud computing

3. Creating a virtual machine

Creating a virtual machine in a cloud computing platform

4. IaaS and cloud computing platforms Providing the overview of IaaS and cloud computing platforms
Providing the internals of system calls in Linux
5. System calls in Linux

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

6. Creating a system call (1)Implementing a system call in Linux (1)7. Creating a system call (2)Implementing a system call in Linux (2)8. Desktop virtualization

Providing the overview of desktop virtualization

9. Linux kernel modules

Providing the internals of Linux kernel modules

10. Creating a kernel module (1)Implementing a Linux kernel module (1)11. Creating a kernel module (2)Implementing a Linux kernel module (2)12. Filesystem and FUSE
13. Creating a filesystem

Providing the internals of filesystems and the FUSE library
Implementing a filesystem using FUSE

14. Virtual machines

Providing the internals of virtual machines

15.
The class will be presented using both theory and hands-on exercises.
The course objectives are as follows:
1. To obtain the basic knowledge of cloud computing
2. To obtain the knowledge of the internals of an actual operating system by writing programs in Linux
3. To understand the structure of virtual machines

Evaluation Methods and Granding Criteria（成績評価の基準および評価方法）

Students will be evaluated by the reports for exercises.

Assignment Instructions（授業外学習（予習・復習）の指示）

The class will give several programming assignments. Students need to work on optional ones as much as
possible. They are required to prepare the class for four hours per week.

Keywords（キーワード）

Cloud computing, virtualization, operating systems, Linux, virtual machines

Required Textbooks（教科書）

Slides are uploaded to moodle.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

kourai@ksl.ci.kyutech.ac.jp

Course Name（科目名）

LSI Design

Instructor Name(担当教員名）

Yutaka ARIMA

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2More than 60 years have passed since the invention of LSI (Large Scale Integrated Circuits), and theminiaturization of LSI devices is reaching its physical and economic limits. What we need to learn about this LSI
technology now is the successful experience of LSI-specific manufacturing and design methods that havecontinued to improve its performance over the past 60 years. It is also important to understand the developmentof LSI and semiconductor device technologies in the new era beyond the limits.
In this class, the trend of LSI device miniaturization for higher performance and lower cost will be explained. Then,the challenges of device miniaturization and the current situation where the limits are being reached will be
introduced. Then, efforts to improve the performance of new LSIs and semiconductor devices will be introduced. In
addition, innovations in LSIs and semiconductor devices will be introduced in order to understand value creation.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This class belongs to the integrated circuit design module, and teaches the key points of technological progress
and future development by looking at the high-performance technology of LSIs (large-scale integrated circuits)
and semiconductor devices. An overview of the progress of LSI technology as one of the successful cases will be
useful as a reference case for those engaged in various R & D other than LSI in the future. This class will provide
an insight into the technological history of LSI and semiconductor devices that have evolved so far, as well as thelimitations of device miniaturization. In addition, knowing new development examples will enable you to learn how tocreate value. In this class, it is desirable, but not essential, to have basic knowledge of electronic circuits andsemiconductor devices.
Theme(テーマ）

Course Calendar/Class Topic（授業計画）

Contents（内容）1. Class guidance, LSI evolution

Outline and aims of the lecture, schedule, grading method, etc.

2. LSI manufacturing technology

Characteristics of LSI structure and manufacturing methods

3. LSI element miniaturization
Limitations of LSI device
4.
miniaturization
5. LSI design technology

Device miniaturization and its effects on LSI value
LSI device miniaturization trend, its limitations and approaches
Overview and key points of LSI design methodology

Development of design tools (CAE) for complex and large-scale LSI design
6. Large-scale LSI design
Deployment example of new typeNew value-added LSI and semiconductor devices
7.
LSI
Development environment for new The technological environment required for new LSIs and devices
8.
technologies
Objectives and outline of theConsideration of latent needs in innovation examples
9.
exercises, Exercise 1
10. Introduction of development case (1) Neural Network LSI with On-Chip Learning Function

11. Introduction of development case (2) Image sensor that mimics the auto-adjustment of local sensitivity in vision
12. Exercise 2

Discovering latent needs and examining the lifestyle changes that result from solving them

13. Introduction of development case (3) Real-time 3D range sensor LSI
14. Introduction of development case (4) Lensless near infrared sensor device

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

15. Summary, otherIn the first half of the class, lectures will be given on LSI-specific manufacturing methods and design methods, aswell as element miniaturization technologies that have achieved high performance. In addition, the trends andissues will be introduced, and the actual situation where the miniaturization of elements is approaching thephysical and economic limits will be explained. In the latter half of the class, we will give a lecture on highperformance that is not based on miniaturization. Introducing several actual LSI development cases and explaining
the concept of developing new-function LSIs and high-performance devices that have never existed before. In
addition, the importance of technological innovation and the necessary abilities will be explained through two
exercises.
This course will be taught in Japanese. The course materials are mainly given in Japanese.
In connection with one of the goals of learning and education in the electronics field, (3) ̀̀ Construction ofadvanced information systems with advanced functions of computers '', LSI and semiconductor The aim is todeepen the understanding of high value-added and development methods, and to acquire specialized basic
knowledge related to information system technology development focusing on new high value-added LSI devices.
This aims to acquire the common learning and education goals of the Graduate School of Information Technology:(B) "Basic academic skills required in information science and engineering and various fields" and (C) "Individual
problem-finding and problem-solving abilities" .
1. Understand the outline and features of LSI design and manufacturing methods.
2. Understand techniques for adding value to LSIs and semiconductor devices.
3. Understand the ability to apply knowledge required for technological innovation.

Evaluation Methods and Grading Criteria（成績評価の基準および評価方法）

The achievement goals (1), (2), and (3) above are evaluated based on exercises 1 and 2 (50 points each). Since theevaluation is based on the total score (100 points) of these two reports, the term-end examination is notconducted.

Assignment Instructions（授業外学習（予習・復習）の指示）

The materials used in the lecture will be posted on Moodle, so please download and prepare in advance, and bringthem with you on the day of the class. After the class, review the material and organize and reconfirm what you
have learned. If you have any questions, be sure to ask them or do your own research. Students are expected to
set aside 4 hours per week for preparatory study.

Keywords（キーワード）

LSI, semiconductor integrated circuit, design, miniaturization, added value, semiconductor device, technologicalinnovation

Required Textbooks（教科書）

None.

References/Recommended Reading（参考書）

None. Introduce during the lecture if necessary.

Notes（備考）Distance learning courses (both synchronous and asynchronous). Synchronous type is Zoom lectures. The
maximum number of remote classes is 15 (face-to-face classes will be conducted according to the situation).

Email（電子メールアドレス）

arima@cms.kyutech.ac.jp

Course Name（科目名）

Advanced Backend Phase of LSI Design

Instructor Name(担当教員名）

Kohei Miyase

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）2
When an LSI is designed, many techniquies are utilized. Even in backend phase of LSI design, logic sysnthesis,
layout design, verification, design for testability, test pattern generation, and power analysis are included. In thislecture, basic techniques are introduced, and then some detail techniques are discussed.

Course Description（授業の概要）

It is desired that undergraduate courses "Computer System I", "Computer System II", "Computer
Course and Curriculum linkage
Architecture", "Programing", "Data base and algorithm" have been taken.
（カリキュラムにおけるこの授業の位置付け）
Theme(テーマ）

Contents（内容）1. Introduction of LSI design
2. Transistor, CMOS
3. LSI design flow
4. Overview of frontend design
5. Verification
6. Logic synthesis
Course Calendar/Class Topic（授業計画）

7. Design for test
8. Layout design
9. Logic simulation
10. Understanding circuit description
11. Power analysis
12. Conclusions
13.
14.

15.
General Course Policies（授業の進め方） This course takes lecture style. (on-demand style)
Introduction to Couse The purpose of this course is to understand the fundamental theory that is used to enhance the reliability ofdigital systems. It is provided to achieves (B) learning the necessary fundamentals of computer science,
Objectives
Course（授業の達成目標の解 engineering and its application . More details are given as follows:
Objectives説）（授業の達成目
1. Basic concept of LSI design
Couseobjectives
標）(具体的な授業の達成
2. How to impliment a new techniques in a programer's point of view目標）
3.
Evaluation Methods and Granding Criteria
Reports as a homework.
（成績評価の基準および評価方法）
Assignment Instructions（授業外学習（予習・復習）の指示）

Spend a time reviewing lessons with distributed course materials. (4 hours)

Keywords（キーワード）

LSI design, backend design, logic synthesis, layout, verification, design for test, test generation, power analysis

Required Textbooks（教科書）「システムLSI設計工学」藤田昌宏 編著、オーム社
References/Recommended Reading（参考「VLSI設計工学 SoCにおける設計からハードウェアまで」藤田昌宏、数理工学社
書）「図解でわかる半導体とシステムLSI」菊池正典 監修、日本実業出版社
Notes（備考）This course takes on-demand style. QandA will be done with Zoom if needed.

Email（電子メールアドレス）k̲miyase@cse.kyutech.ac.jp

Course Name（科目名）

Japanese Ⅰ

Instructor Name(担当教員名）

HIRATA Yuko

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1
Based on Japanese social and cultural topics, students will improve their reading and listening skills, expand
their vocabulary, and develop the ability to express their thoughts and feelings appropriately.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Course Calendar/Class Topic（授業計画）

General Course Policies（授業の進め方）

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）
Couse objectives(具体的な授業の達成目標）

This is a basic course for international students and is designed to establish intermediate level Japanese
language skills for supporting university life.
It is assumed that students have at least beginner/intermediate Japanese language ability (about JLPT test N3
level).
Theme(テーマ）
Contents（内容）1. Lesson 1: The Ichiroku Bank

"tame to express a reason

2. Lesson 1: The Ichiroku Bank

Supporting the partner's decision

3. Lesson 2: Zoo

The result of the operation: "〜ta tokoro"

4. Lesson 2: Zoo

Expressing a result that is contrary to expectations

5. Lesson 3: Virtual Reality

Onomatopoeia and mimetic words

6. Lesson 3: Virtual Reality

Expressing that facts differ from appearances

7. Lesson 4: Body Time

Partial negative expressions

8. Lesson 4: Body Time

Passive affirmation

9. Lesson 5: Nature

Double negative expressions

10. Lesson 5: Nature

Emphasis

11. Lesson 6: Left-handedness

The result of reminiscence: "〜mono da"

12. Lesson 6: Left-handedness

Speaking nostalgically and with emotion

13. Lesson 7: Symbiotic Housing

Evidence: "〜ijo"

14. Lesson 7: Symbiotic Housing

Expressing the speaker's determination and resolve

15. "VOICES FROM JAPAN"

Discussion

16. Summary and examination
While studying each lesson, students will confirm sentence patterns, grammar, vocabulary, and expressions, anddeepen their understanding of the content. After close reading, we will exchange opinions on each topic. In
addition, vocabulary and sentence patterns will be reinforced through assignments.
Mid-term and final exams will be given as appropriate.
Students will develop intermediate level expression skills to support their university life. Students will be able toexpress their knowledge and thoughts on each topic in their own words.
1. To improve reading and listening skills
2. To expand vocabulary on social and cultural topics
3. To express one's thoughts accurately in Japanese

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

Evaluation will be based on class participation (20%), assignments (20%), and mid-term and final examinations(60%).

Assignment Instructions（授業外学習（予習・復習）の指示）

Students are expected to set aside 30 minutes per week for study preparation. Students are required to submit
assignments for each lesson.

Keywords（キーワード）

Japanese society and culture, reading comprehension, vocabulary, expression.

Required Textbooks（教科書）

NobukoMizutani: Modern Japanese Intermediate Cours, Alc Publishing.
Yuriko Nagata: VOICES FROM JAPAN, Kuroshio Publishing Co.

References/Recommended Reading（参考書）
Notes（備考）
Email（電子メールアドレス）

jayjammin.chiro.haru56@gmail.com

Course Name（科目名）

Diversity, Inclusion, and Equity

Instructor Name(担当教員名）

KATO, Reiko

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective course
Credits（単位数）1
In the globalized society, we can find conflicting discourses on Multiculturalism : exclusion and inclusion ofhuman diversities in communities. However, acceptance of different cultures has become a key competence tocontribute to the sustainable development of the global society. In this course, we will examine diversities inour society, and will critically look at issues and initiatives regarding multiculturalism in our daily lives. We willthen make suggestions/proposals to make our society more inclusive and equitable. Through classroom
discussions and group activities, the course will offer opportunities to strengthen critical thinking, problem
solving, and intercultural communication skills.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

This course is part of the Advanced Global Liberal Arts Subject, an elective course for the Global Engineer
Course.

1.

Course Calendar/Class Topic（授業計画）

Theme(テーマ）

Contents（内容）Global Trend of Multiculturalism inthe 21st Century

Introduction to the Course and the concept of Multiculturalism

2. Diversity in local communities

Examining the Effects of Globalization and Diversification in local
communities

3. Diversity in classrooms

Examining the Effects of Globalization and Diversification in
Education Sectors.

4. Diversity in workplaces

Examining the Effects of Globalization and Diversification in
Workplaces

5.

Mechanism of Prejudice andIntervention

Rethinking "prejudice" and "intervention" from cultural perspective

6.

Promoting Multiculturalism:
Proposal to our community 1

Gathering and analyzing current issues on multiculturalism andidentifying a problem to take on as your group project7.

Promoting Multiculturalism:
Proposal to our community 2Group Discussion on Proposal to our Community.

8.

Group Presentations andConclusion

Peer review for classmates proposals

9.
10.
11.
12.
13.
14.

General Course Policies（授業の進め方）

15.
All class meetings will be held online on Zoom. The Zoom access will be announced via Course Moodle. Aftereach class meeting, participants need to submit a reflective memo on Moodle. Reflective memos will be used toconfirm attendance to the class. The Final Project includes a group presentation and an individual report.
In this course, Active Learning Strategies will be implemented. Active Learning Strategies help learners toengage in activities based on ideas about how people learn.
Through experiences: Do it
Through discussions: Talk about it with others
Through rephrasing: Say it in your words
Through investigations: Clarify it
Through reflection: Know what you have learned
Active and informed participation in class results from your preparation and reflection of the course materials.
If you have an unavoidable reason to be absent or tardy (such as sickness, family emergency, religious holidays,
or job interviews), consult with your instructor in advance.
This course will be conducted in Japanese. Slides/Reading materials are available in English.

CourseObjectives（授業の達成目
標）Introduction to Couse
Objectives（授業の達成目標の解説）

Couse objectives(具体的な授業の達成目標）

By scrutinizing Issues and Initiatives regarding Multiculturalism, this course aims to foster Global Competenceof participants. At the end of this course, the participants will be able to gain knowledge/improve their skills in
following aspects.
1. Explain issues of Multiculturalism with concrete examples.
2. Identify initiatives to construct inclusive society with concrete examples.
3. Suggest ideas to make society more inclusive and equitable.
4. Work in a multicultural group using effective intercultural communication skills.

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

In-class contributions （50%）and Group Project（50%）

Assignment Instructions（授業外学習（予習・復習）の指示）

There will be reading assignments on Moodle for each class meeting. Also, participants were expected to havegroup meetings for the project. For preparation and group meetings, participants were expected to spend
around 2 hours/week.

Keywords（キーワード）

Human Rights, Prejudice, Multiculturalism, Reasonable Accommodation, Intercultural Communication
Competence

Required Textbooks（教科書）

There are no required Textbooks, but articles for discussion will be distributed and references will be
introduced in class.

References/Recommended Reading（参考書）

Aramaki, S., Enoi,Y., Ehara, H., Kojima, Y., Shimizu, K., Minamino, N., Miyajima, T., & Yamano, R. (Eds.). (2017).
Gaikokujin no kodomo hakusho [The state of the foreign children]. Tokyo: Akashishoten. ISBN 9784750344959
Koido, A. (Ed.). （ 2017). Imin ukeire no kokusai shakaigaku: senbetsu mekanizumu no hikaku bunseki[International Sociology of Immigration Acceptance: Comparative Analysis of Selection Mechanism]. The
University of Nagoya Press. ISBN 9784815808679
Koizumi, K and Kawamura, C. (Eds.). （2016). Tabunka "kyo so " shakai nyu mon: imin, nanmin to tomo ni kurashi,tagai ni manabu shakai e [Multicultural synergy : conceptual challenges and practical solutions in the age ofglobal migration]. Kei Gijuku Daigaku Shuppankai. ISBN 9784766423716
Menju, T. （2016). Jichitai ga hiraku nihon no imin seisaku: jinko gensho jidai no tabunka kyo sei e no cho sen[Local Governments Lead Japan s Immigration Policy : Challenge for multicultural symbiosis in the era of
population decline]. Akashishoten. ISBN 9784750343655
Kagami, T. (Ed.). （2013) Tabunka kyo sei ron: tayo sei rikai no tame no hinto to ressun [Multicultural existence
theory: Hints and lessons for understanding diversity]. Akashishoten. ISBN 9784750338484
Kagami, T. (Ed.). (2012) Tabunka shakai no henken, sabetsu : keisei no mekanizumu to teigen no tame no kyo
iku [Bias/discrimination in multicultural societies: The formation mechanism and education for prejudice
reduction] Akashishoten. ISBN 9784750335810
References in English will be provided in class

Notes（備考）

Office hours will be announced in the first class meeting.

Email（電子メールアドレス）

kato@lai.kyutech.ac.jp

Course Name（科目名）

Information Society

Instructor Name(担当教員名）

Keiko Yasukochi

Course intended for（対象学年）

1ｓｔ or 2nd year student

Credit Category（単位区分）

Elective and required course
Credits（単位数）1
The rapid development of information technology since 1970 has greatly advanced informatization and globalization all over the world.
Exponential developing information technology has promoted online platform companies (such as GAFAM), changed emoloyments, and may bringsingularity around 2045.
In this course, lectures are given about history of development of information technology, the problems of online platform companies, the futureof employment, and the singularity. Furthermore, we consider the future and issues of information society.
This course is an advanced globa liberal arts subject in the Global Engineering Course.
This course places to learn the current states of information sosiety, and make students think about the future and issues of informationsociety.

Course Description（授業の概要）

Course and Curriculum linkage（カリキュラムにおけるこの授業の位置付け）

Theme(テーマ）

Contents（内容）Introduction: Development of information technology and future of1.
humankind, society
2. Development of information technology and chnges of society
3. Rise and problems of online platform companies
4. Development of information technology and future of employment
5. Singularity and future of humankind
6. Singularity and 2045issue
Course Calendar/Class Topic（授業計画）

7.

Last: Development of information technology and future ofhumankind, society

8. Summary and explanation about final exam (final report)
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10.
11.
12.
13.
14.
General Course Policies（授業の進め方）
Introduction to Couse
Objectives
Course（授業の達成目標の解説）
Objectives（授業の達成目 Couse objectives
標）(具体的な授業の達成目標）

15.
The first harf of this class carries out in lecture style, and the latter harf in seminar style (if possible).
Course objectives are to make students learn the current states of information sosiety, and think about the future and issues of informationsociety.
1. Understand the history of progress of computerization
2. Understand the current situation and issues of information society
3. Understand the problemsn and issues that will arive in the future information society

Evaluation Methods and Ganding Criteria（成績評価の基準および評価方法）

Your overall grade in this class will be decided based on following:-Small reports (50%) (in total)-Final exam (or Final report) (50%)

Assignment Instructions（授業外学習（予習・復習）の指示）

This class requires for 2-4hours per week, and 8-10hours at last time.
(1) On every lesson: preparations / reviews is essencia l: Gathering informations and writing small report (about 2hours)(2) On presentation: Getting ready for presentation (about 4hours)(3) On Final exam (or Final report) : Reviewing all the contents you have learned so far (about 8-10hours)

Keywords（キーワード）

Informatization, Information Society, Online Platform Compnies, GAFAM, Future of Employment, Singularity, 2045issue, Universa Basic Incom,
Dr.Osborne, Dr.Kurtzweil

Required Textbooks（教科書）

None

References/Recommended Reading（参考書）

レイ・カーツワイル 『ポストヒューマン誕生 -コンピュータが人類の知能を超えるとき-』（NHK出版）
レイ・カーツワイル 『シンギュラリティは近い』（NHK出版編集）（NHK出版）

Notes（備考）(1) At first class, I explain overall process of this course.
(2) If you have any questions, please send me an email (email adress is below).

Email（電子メールアドレス）

yasukochi@lai.kyutech.ac.jp