List of Dissertation Abstract (Department of Information Environment)
Name
Chen Jiayun

Supervisor

Title

Abstract

Okajima

Study on visual texture of foodTo determine what visual information influences the

Katsunoriwith image processing

visual texture perception of food, the effects ofpresentation time, color attributes, and spatial
frequency were tested based on psychophysicalexperiments. The results showed that material
perception characteristics associated withpresentation time, the three color attributes ofbrightness, saturation, and hue, and spatial frequency
influenced texture perception. It was also found that
there were large individual differences in texture
evaluation values among the experimental
participants, which were attributed to differences inindividual interpretations of food images and imagesof food.

WANG JIA

Katsunari

Detecting and Analyzing

Yoshioka

Malicious Ethereum Accounts
Using Multiple Data Sources

Arai Kazuhiro

Junji Shikata

A Study on Construction of
Public Key Encryption with
Keyword Search

Misconfigured Ethereum clients with application
programming interface (API) enabled, JSON-RPC in
particular, are targeted by cyberattacks. In this study,
we propose a new framework to detect malicious
Ethereum accounts using 3 different data sources(honeypot, Internet-wide scanner and blockchain
explorer). Through the observation of 6 weeks, weobserved 538 hosts trying to call JSON-RPC of ourhoneypots with 41 types of methods, including 2 types
of attacks unreported in the wild. We detected 16
malicious accounts from the honeypot and 64
suspicious accounts from Shodan. To an end, thisstudy provides a brighter view of malicious activities
on Ethereum.
Recently, the need of cloud service increases
opportunity for users to encrypt and keep various data
in database. However, this situation causes a problem
of difficulty of searching and operating suchencrypted data without decryption. Public key
encryption with keyword search (PEKS) was proposed
to solve this problem.
In this thesis, two kinds of constructions for PEKS are
newly proposed. The first one is constructed frominner product encryption, and the second one isconstructed from homomorphic encryption. In
addition, this thesis analyze and evaluate security andefficiency of those constructions.

Aramaki Kodai

Tomohiro

Eliciting focus-sensitive why-

It has been argued in the literature that reason WH-

Fujii

questions in Japanese

adverbials such as 'why' can be focus-sensitive whileother WH-phrases cannot be and that in Japanese
focus-sensitive 'why'-questions, reason-WH-phrases
like 'naze' must precede their focus associate. The
present study provided experimental support for thisword order restriction. Two elicitation experiments
were conducted and revealed that the word order
restriction in question indeed exits. We successfully
tested the relevant theoretical prediction without
appealing to the standard acceptability judgement
methodology, where context and prosody, two factorsthat play a crucial role in the construction underinvestigation, might be hard to control for.

Iida Junko

Tomii Takashi Design and Implementation of aIn this study, we propose a framework that can

Load Leveling Simulation

simulate power load leveling in a smart grid that

Framework Capable of Evaluating

consists of renewable energy and EVs. The framework

Disadvantages of Vehicle-Gridconsists of three components: a database schema, aIntegrationload-leveling simulation algorithm, and a method forquantifying the advantages and disadvantages ofload-leveling. This framework has made it possible tostudy the feasibility of load leveling in the smart grid.

iida seiya

okajima

Effects of ipRGCs and rods on

katunoricolor perception in dichromats

Ichinose

Tsutomu

A Study on Instrumentation

RyuuyaMatsumoto

Security for Automated Driving
Systems

In consideration of the individual differences in the
spectral sensitivities of the three types of cones,
ipRGC and rod among observers, I experimentallyinvestigated the effects of ipRGC and rod on color
perception in dichromats. In Experiment 1, individual
spectral sensitivities were measured using a flicker
method. In Experiment 2, color discrimination
experiment was performed where only stimulus
response of ipRGCs or rods was modulated while
keeping the responses of L,M,S cones which were
calculated using individual spectral sensitivities. The
results of Experiment 2 showed that ipRGCs and rods
contribute to color perception in dichromats.
In recent years, the development of fully automatedvehicles that do not require human control has beenpromoted throughout the automotive industry. In
order to guarantee the safety of vehicles equippedwith automated driving systems, it is important toanalyze the risk of attacks that threaten theInstrumentation Security of on-board sensors and to
take necessary countermeasures. In this study, weconstruct two types of simulators that can be used as
evaluation tools for the Instrumentation Security of
automated driving systems, and evaluate the attacks
as practical examples.

Iwakami

Nagao

Analysis of Marine Biofouling inTomoyaTomoharu

Underwater Ship Bottom Video
ImagesUEDA SHINSEIMATSUMOTO A Study on Instrumentation
TSUTOMU

Security of On-Board Sensors

Ships need to be brought ashore for cleaning whenmarine biofouling increases. In order to determine thenecessity of such cleaning, experts analyze the video
images taken underwater, but manual analysis takes
a long time. Therefore, there is a need for a method toautomatically analyze the marine biofouling. In thispaper, we propose a method that uses deep learning
to create pseudo-supervised data from a small
amount of supervised data, and segment theunderwater ship bottom video images with respect tomarine biofouling.
Automatic driving technology is supported byinformation on the surrounding environment obtained
from onboard sensors. Therefore, any inadequacy inthe measurement results may lead to a serious
accident. Therefore, there is a need to improve theinstrumentation security of in-vehicle sensors. In thispaper, (1) we constructed a simulator for ultrasonicsensors to simulate an attack experiment. （2）We
proposed an attack method for the on-board cameraand evaluated it through experiments. (3) We
constructed an automatic driving simulator forevaluation of instrumentation security and evaluatedthe effect of attacks on the on-board camera on
automatic emergency braking.

Uchida Hiroto

UMEKI Hiroshi

Mori

Elaboration of Curation Map

Tatsunori

based on topic extraction

Shinichi

Bézier Simplex Adaptation for

SHIRAKAWA

Black-Box Multi-Objective
Optimization

The document collection, obtained by a generalsearch engine, is not ranked as a score for content
comprehensiveness of the document. Thus, if the
documents are referred to in order from the top, it
may take a great deal of effort for the user to reachthe necessary information. To address this problem,
research has been done to automate the detection of
documents with multiple contents at the top of the
ranking and the presentation of “Curation Map”
about those documents. “Curation Map” is the graph,
which is obtained by dividing a document by its
contents and generating links based on the content
relevance to other documents with more detailed
content. In this research, we attempted to improve its
accuracy.
A Pareto set analysis method using the Bézier simplex
fitting has been proposed based on the observationthat the Pareto set of real-world continuous multiobjective optimization problems is often
homeomorphic to simplex. This method requires
running a multi-objective optimization algorithm inadvance, and the analysis results heavily depend on
the optimization algorithm. This study proposes a
black-box multi-objective optimization method toefficiently obtain the Bézier simplex describing thePareto set through the optimization process byleveraging the Bézier simplex fitting for solution
generation. The numerical experiment on benchmark
problems whose Pareto set is homeomorphic tosimplex shows the efficiency of the proposed method.

Umemoto

ShirakawaTransfer Learning Method forHaruki

ShinichiRegression Problems and Its
Application to Industrial Data

otsuka fuga

Kenta Ozeki(p,q)-Knight's tours and the total
number of knight's tours on arectangular chessboard

When modeling industrial processes and simulators
using machine learning, existing models cannot
predict output well if their input-output responses
change between training and test stages. We proposea transfer learning method that introduces two
regularizations to the loss function for regression
tasks with little training data after the change. The
first is regularization for the parameters of the modeland the second is regularization for the intermediate
representation of the model. We use two datasets forvalidation: power plant and wing performance
prediction. We show that the proposed method
improves the prediction accuracy of the output after
the change on the wing performance prediction
dataset.
A knight's tour on a chessboard with m rows and ncolumns is a knight's route such that the knight visits
every square exactly once and returns to the firstsquare.
We show a new lower bound of the total number ofknight's tours on a chessboard in the case of m=n.
(p,q)-Knight, also known as (p,q)-leaper, is an
expanded knight that can move from (x,y) square to (x±p,y±q) or (x±q,y±p) square.
We show new conditions of p, q, m and n such that a(p,q)-knight's tour exists on a m×n chessboard.

Ohashi

Tomii Takashi Utilization of EV Internal Data for

Hironoridifferent purposes to produce the
EV Energy Map

Ogawa Kota

Katsunari

A study on feature extraction of

Yoshioka

IoT malware by dynamic analysis

This study shows how to utilize internal data fromelectric vehicles (EVs) to create EV-specific energy
consumption maps.
For mapping purposes, various data including power
consumption data flowing on CAN bus (CAN:
Controller Area Network) inside the EV are
accumulated as a “lifelog” and utilized.
The lifelog of the EV on constant speed condition wasused as the minimum road-specific energy
consumption.
The coverage of the map was improved by selecting
logs from daily driving logs that were temporarily
driven at a constant speed, as opposed to using logs
that were driven at a constant speed using Adaptive
Cruise Control.
In this study, we first investigate the network statechanges caused by IoT malware infection by
executing malware samples, collected by IoT
honeypots, in a virtual machine. As a result, we foundthat about 33% of the samples change the network
state of infected devices and there are many patterns
in the changes of the network state. Next, based on
the results of the dynamic analysis in the virtualenvironment, we extracted samples that made uniquechanges in the network state and conducted the
dynamic analysis using bare-metal IoT devices. As aresult of the analysis, we found that changes in the
network state were also observed in the actual
devices, which can be confirmed by external portscanning. The change of the port listening state in thevirtual environment did not always match that in theactual device. Finally, we discuss the possibility of
remotely detecting infected devices by checking theirport listening status.

Ozaki Yu

Nagao

Transformation from Real Images

Tomoharu

to Illustrations Depending on the
Style of a Few Illustration
ExamplesOTOGAWANAGAO

A Parts-Based Detection Method

Yuma

Tomoharu

for Construction Machinery

Recently, image transformation based on Generative
Adversarial Networks has been widely used. However,
one of the problems in transforming a photograph to adifferent domain, such as an illustration, is that alarge number of examples of the target image are
required. In this paper, we propose a method thatextracts the features of a style from a few illustrationor painting examples to be transformed and reflects
the style to a photograph. Experiments show that the
proposed method can make a photograph closer tothe target illustration or painting.
In the construction industry, image recognition is
being used for the automatic operation of
construction machinery and for improving work
efficiency. In particular, it is necessary
to be able to accurately recognize obstacles andpeople around construction machinery byobject detection. It is also important to be able toexplain why the recognition was correct
or wrong. In this paper, we propose a new methodthat is more accurate and can explain
the basis of recognition by using parts of construction
machinery. In experiments, we confirmed how theresults changed compared to the conventional
method.

KimuraOzeki Kenta

Masahiro

Kono Taro

Nagao
Tomoharu

Since a Hamiltonian path, which is one passing
through all vertices of the graph, is a spanning tree
degree sum of independent vertex
with the smallest number of leaves, the minimum leaf
set and the minimum leaf number number problem(the problem of finding a spanning
tree with the smallest number of leaves) can bein a K1,p-free graphconsidered as an extension.
In this thesis, we consider the relationship between
the degree sum of independent vertex set and theminimum leaf number in a K1,p-free graph.
This problem was previously shown only when p ≤ 4
and when p = 5 and the minimum leaf number is 4
and 6.
In this thesis, by introducing a new method, thecondition is obtained for the case of the generalminimum leaf number at p = 5.
In CG-based real scene adaptation of semantic
Real Scene Adaptation ofsegmentation, real-style transfer from CG has been
Semantic Segmentation Modelused. However, it is difficult to transfer CG into real
Using CG-Style Transfer fromimages in blurry and colorless environments such ascivil engineering worksites. In this study, we consider
Real Images
real scene adaptation by transferring real images into
CG. The proposed methods are (1) adversarial
learning, in which the output distributions of CGstyled real images and of CG images are made close,and (2) spatio-temporal constraints, in which the pixel
values on same positions of neighboring frames are
made equal. The accuracy of the proposed method isimproved by more than 10% on the data of civilengineering worksites.
The relationship between the

KOSAKAIOZEKI KENTA Relation between girth and

MASATO

minimum leaf number of cubic
graphsKobayashi
Hirokazu

Shikata Junji

Optimal Construction ofAnonymous Broadcast Encryption
and Authentication

Minimum number of leaves in any spanning tree iscalled the minimum leaf number of the graph. It is
known that a connected, n-vertex, cubic graph has aminimum leave number less than n/6+1/3, and it isalso known that this is the best. In this study, I predictthat a cubic graph on n-vertices with girth greaterthan or equal to 4 and connected has a minimum leaf
number less than or equal to n/8+1/4, and we show apartial solution that the minimum number of leaves isless than or equal to n/7 if the girth is greater than orequal to 6.
Broadcast Encryption (BE) is a cryptosystem thatallows a sender to specify recipients so that only the
specified recipients can perform decryption.
Anonymity, which is one of additional but important
security requirements of BE, guarantees that no
information of the designated recipients is leaked
from ciphertexts, and several BE schemes withanonymity (ANO-BE) have been proposed so far. In
this thesis, in ANO-BE, the tight lower bound on the
ciphertext-size is derived and an optimal construction
is proposed. Similarly, in anonymous broadcast
authentication, the lower bound on the authenticatorsize is derived and an optimal construction isprovided.

Shimizu Ryota

YamadaVERIFICATION OF AN

Takahiro

IDENTIFICATION METHOD FOR
AHYPERELASTIC BODY BASEDON STRESS ANALYSIS

Suzuki Mana

OkajimaMultisensory Feedback Interface

Katsunoriand Multiperson Empathy System
Using Mixed-Reality Devices

Usually, when identifying hyperelastic, the main focus
is on obtaining comprehensive parameters. However,in the case of mechanical products, it is more useful
to obtain parameters that are sufficiently accurate
under the design conditions of the product. Therefore,a property identification method focusing on thefrequency of occurrence of deformation states ofstructures has been proposed. In this study, the bestproperty parameters for the structure were calculated
in an inverse manner, and sample points that areimportant for property identification were extracted.
This verifies the assumptions made by the methodand demonstrates its usefulness.
I constructed an experimental environment of virtual
keyboard using Hololens2 and verified the effects ofvarious types of feedback on operation performance.
As a result, I showed that the tactile feedback
generated by the user's touch to his/her own skinduring input has a positive influence on theimpression evaluation. In addition, a mixed reality
system that augmented the rhythm of others wasconstructed and tested. As a result, it was shown thatthe visualized rhythm synchronized with theaudience's nasal movements contributes to theformation of a sense of togetherness.

Suzuki Ryotaro

SONG ZIHAOProfessor

Similar document search from a

Tatsunori

set of past defect/inquiryMoridocuments by text analysis

Tsutomu

A Study on Pairing Based

Matsumoto

Cryptography and Aggregate
Signature

There is a great demand for searching past defectcases for inquiries that occur in manufacturing sites.
However, it is difficult to apply existing machinelearning methods to such case because of their small
amount of data and lack of labeling. In this study, we
attempted to create a document vector generation
model suitable for accident and failure casedocuments by combining predicate term structure
analysis and passages segmentation by window
width, based on SWEM, a simple document vector
generation method that takes the average value ofvectors. In the search experiments, we were able toobtain an accuracy that exceeded that of BERT, amachine learning method.
High-performance cryptography is a new type of
cryptography that can provide not only encryption anddecryption but also more convenient functions, and is
expected to be implemented in society with higher
speed and security proofs. In this study, three newparameters of the core technology of highperformance cryptography, which have not yet been
implemented and evaluated, are implemented andevaluated, and their superiority, inferiority, andcharacteristics are clarified for the first time. We also
proposed the first cloud-based large-scale
cryptographic simulator and evaluation platform,
which is indispensable for the social implementationof high-performance cryptography, and implemented
a prototype of the platform.

Takasu

Tatsunori

MegumiMori

Takeuchi Yuta

Nakamoto
Atsuhiro

In recent years, deep learning techniques have maderemarkable progress, improving the accuracy of
Question-Answering System forprediction and estimation. On the other hand, systems
World History Essay Typeare becoming more and more black-boxed, andexplainability, which adds transparency andQuestionsinterpretability to the results of AI decisions, isattracting researchers’ attention. Although somemethods to explain the result of Factoid-type
question answering systems are proposed, it is still
difficult to apply them to Non-Factoid-type question
answering systems (Non-Factoid QA systems). In thisstudy, we discuss the explainability in Non-Factoid
QA systems. We first consider how to make NonFactoid QA systems explainable, and proposed amethod to give explanations from external knowledge
sources to sentence using proper nouns as keys. As aresult, the method achieved 34.4% in recall.
The generating theorem of non-q- It is known as the Hajós theorem that all non-qcolorable graphs are obtained from a certain graph bycolorable signed graphs.
three operations.
It is also known that all non-q-colorable signed
graphs are obtained by five operations, where
signed graphs are ones with each edge assigned asignature ＋ or －.
In this thesis, under a certain condition when q iseven, we improve this theorem by decreasing thenumber of the operations into four.
Study on the Explainability inNatsumeda

MatsuiSintering Simulation for Ceramics

Chikako

Kazumiin Large Deformation

Noda Yuhei

ShinichiDynamic Neural Architecture

Shirakawa

Search for Convolutional Neural
Network with Categorical
Distribution and Structure
Regularization

In this paper, the simple simulation strategy forsintering ceramics in the large deformation framework
is proposed. The total deformation gradient ismultiplicatively decomposed into thermal andmechanical components, and they are also
decomposed into reversible and irreversible
components. For the thermal irreversible component(sintering deformation), Master Sintering Curve is
employed, and Peric's viscoplasticity model is used
for the mechanical irreversible component torepresent the creep deformation in sintering ceramics
under stress. The model is introduced into ANSYS,
thermal-structural analysis with User Programmable
Feature (UPF). The simulation is validated bycomparing with sintering experiment under external
axial compression loads.
Neural Architecture Search (NAS) is a field ofautomatically designing deep neural networkarchitectures. In this study, we focus on NAS thattakes into account the architecture complexity andpropose a method that obtains multiple architectureswith different complexity in a single search by using
importance sampling. We experimentally show thatthe proposed method can obtain multiple
architectures with the same or better performancewith less search cost than the comparison method.

hayashi shungo Prof. Tsutomu A Study on Evaluation andMatsumotoFault injection attacks cause faults in operating

Countermeasures of Laser

embedded systems, resulting in the leakage ofInduced Instruction Manipulation

confidential information. In particular, instruction
manipulation attacks cause faults in instructions
executed by a processor and change the instruction toanother one. This study shows that existing
countermeasure is vulnerable to instruction
manipulation attacks using laser irradiation, andproposes a coding method to improve resistance tosuch attacks. This study also proposes a method toanalyze and evaluates the effects of instruction
manipulation attacks on programs.

Hirose Masaya

Mori

Detection of facial emojis that

The growth of SNS makes sentiment analysis more

Tatsunoriaffect the estimation of utterance

crucial. In recent years, the method of using emoji for

intention

sentiment analysis has become a hot topic. Sinceemojis are widely used in text communication andtheir usage is diverse, emojis with rhetorical usage
such as sarcasm and self-mockery 😊, for example,
are expected to affect the results of sentimentestimation using existing methods. In this paper, we
proposed a method to detect such emojis using emoji
classifiers and showed its effectiveness.

Hirobe Akira

Kenta Ozeki

Characterization of graphs

A rectangle divided into rectangles is called a

representing rectangular

rectangular dissection of the rectangle. Felsner gave a

dissections of the cylindernecessary and sufficient condition for plane graphs torepresent rectangular dissections of a rectangle. We
can similarly define a rectangular dissection of thecylinder. However, we need more discussion that do
not occur for the rectangle case, due to a property of
the cylinder. In this thesis we first give another proofof the Felsner’s result and then give a necessary andsufficient condition for cylindrical graphs to represent
rectangular dissections of a cylinder.

Fujita Tomoko

Nagao

Construction of Pedestrian

In recent years, simulating and analyzing pedestrian

Tomoharu

Behavior Model Using ADG;

flow has attracted much attention to improve safety

Automatically Defined Groups

and revitalize areas where people gather, such as
train stations and urban areas. However, it is difficult
to analyze the pedestrian flow in public spaces undernormal conditions using a single pedestrian behavior
model, because individuals act for various purposes.
In this paper, we propose a method to construct apedestrian behavioral model by using ADG. The
results of the experiments show that by using our
method, behavioral models with multiple objectives
are acquired.

Funawatashi

Ushikoshi

Mathematical analysis of crack

TakashiErika

growth in the elastic body bybending

Furihata

Shirakawa

Construction of Focus

SuguruShinichi

Determination Model for Bhas42
Cell Transformation Assay by
Multiple Instance LearningThis study analyzes a mathematical model of crack
growth by bending a one-dimensional elastic bodywhose shape is a very thin rod. Specifically, we derivea mathematical model of crack growth due to bending
based on the method of Takaishi-Kimura(2009), who
considered the case for mode III. Furthermore, we
analyze the relationship between the parameters of
the stationary problem and a sketch of the graph ofthe solution using numerical analysis. In addition, theresults of numerical calculations are discussed from amathematical view point.
Bhas42 cell transformation assay (Bhas42 CTA) is amethod for testing the carcinogenicity of chemical
substances. In Bhas42 CTA, the experimenter needs
to manually determine whether the abnormal growthof the cell group
exposed to the chemical substance is due to thecancerous cells. Therefore, the automatic judgment
system is required to reduce the burden on theexperimenter. In this study, we use Multiple Instance
Learning to construct a
determination model that captures both global andlocal information in cell group images. The
effectiveness of the proposed model is demonstrated
by comparing existing methods.

Matsuda

ShinichiEnd-to-End Learning of Tabular-

TakuyaShirakawato-Image Converter andConvolutional Neural Network

Matsuyama

Nakamoto

K6-minors in 4-representative

AtsushiAtsuhirographs on the torus

Methods for converting tabular data into images andapplying convolutional neural networks (CNN) thatshow excellent performance on image recognition
have been developed. However, previous studies do
not transform tabular data into images by directly
considering the CNN error. In this study, we propose anovel method that simultaneously trains a tabular-toimage converter and CNN, resulting in obtaining thetabular-to-image converter minimizing the CNN loss.
Further, we introduce an additional loss function tocreate human-interpretable images by the tabular-toimage converter. We confirmed that the proposed
method achieves high accuracy and produces humaninterpretable images on several benchmark datasets.
In graph theory, characterizations of graphs whichcontains the complete graph of specified number ofvertices as a minor are considered important andstudied by many researchers, in relation to a
conjecture on the graph coloring problem. However,no characterization is known for the cases where theorder of the complete graph is at least 6. As a
restriction of this problem, we show that every graphwhich has a 4-representative embedding on the torus
has the complete graph of 6 vertices as a minor,
confirming the result obtained by a computer-aided
experiment.

Murakami

Tomii Takashi Design and Evaluation of Load

Taichiro

This study simulate power load leveling utilize

Leveling Algorithm Utilize

renewable energy and EV batteries.

Renewable Energy and EV

To achieve this load leveling, we formulated andBatteries

designed an algorithm.
Utilizing a database that combines open data andlifelogs for load leveling, when load leveling was
performed, the simulation was conducted undervarious conditions to quantify and visualize the results
under various evaluation indexes.

murakami

KatsunariMeasuring the effectiveness of

The importance of notification activities for users of

hayatoYoshioka

notification to the users ofvulnerable devices is increasing, and as a method, we

insecure IoT devices via

focused on a model that alerts through a dedicateddedicated apps

app installed on the user terminal. In this research,
we conducted a notification experiment using an
actual app for 60 people who have opened vulnerable
ports. As a result, the port opening status was
improved more than three times compared to when no
notification was given. In addition, in thequestionnaire in the notification, information of theuser's network environment and whether or not there
was an intention to open the port was obtained.

Yamaguchi

Shinichi

Improvement of CMA-ES for

TeppeiShirakawa

Optimizing High-Dimensional
Functions with Low Effective
Dimensionality

Wakabayashi

Shinichi

Improving Machine Learning

KentaroShirakawa

Model by Pre-Training Scheme
toward Support of Construction
Equipment Operations

High-dimensional black-box optimization problems
often have a property where only a small part ofdesign variables affects the objective function value
but the others do not. This property is called Low
Effective Dimensionality (LED). In this study, we
introduce a mechanism that estimates and leverages
the low effective design variable into a widely used
continuous black-box optimization algorithm,
Covariance Matrix Adaptation Evolution Strategy(CMA-ES), and realize efficient optimization on
objective functions with LED.
A support system to improve the operator's skill
during the construction work is needed for the smooth
progress of construction work. In this study, we train
machine learning models using sensor data of wheel
loaders and discuss the operation supporting method
using the trained model. In order to improve theaccuracy of the operation supporting method, we
propose a pre-training method for efficiently
exploiting our datasets including different conditionsof data in terms of the construction site and operator.
The experimental result using overseas data anddomestic test site data shows that the proposed pretraining method can improve the operator
classification and operation prediction performances.
We also discuss the potential of the operator support
using the trained model.

HE SONGWEI

Katsunari

A New Web Service to Inspect

In recent years, it becomes important to notify the

Yoshioka

End Users' IoT Devices forowners of IoT devices infected with malware in Japan.

Malware Infection and

The traditional method is that the notification to the

Vulnerabilities

end user who did suspicious communication by ISP.
In this research, we propose a new notification
method to provide check results for the users whowant to know the security status of their IoT devices
in their homes by the web service.

Guo Binnan

YOSHIOKA

A research on analysis ofWith the increase in IOT devices, cyber attacks

Katsunarivulnerability attacks observed intargeting their vulnerabilities are becoming more

honeypots

sophisticated. Honeypots, which are decoy systems,
are widely researched, developed, and operated totake security measures. Insufficient registration ofvulnerabilities in the database and an increase inresearch scans by researchers and operators make it
difficult to observe attacks. In this research, we
analyze the attacks observed in the honeypot, which
is a decoy system, identify the equipment / system to
be attacked, the vulnerabilities being exploited, andinvestigate the characteristics of the attack activity.

Kou

Buntou Katsunori

Study on communication robot

Kou

OKAJIMA

returning appropriate gestures
according to the emotions ofusers

ZHOU LUMING NAGAOTOMOHARU

Facial Expression Recognition of
Sketch Using Facial Landmark

I developed a communication robot with specificcharacter-equipped motion sets that can read theemotions of a face-to-face person with a facial
expression recognition system and return anappropriate gesture. I conducted three evaluation
experiments. The results of Expt.1 showed thathumans can estimate emotions from body
movements, and the results of Expt.2 showed that thenatural feeling and willingness to use virtual robots
are significantly improved by appropriately selecting
characters. Finally, the results of Expt.3 showed that
communication robots have a positive effect onhuman emotions when humans are watching videos.
In recent years, facial expression recognition ofhumans has been actively carried out, but there arefew studies related to facial expression recognition of
sketch such as manga characters. Since the style ofsketch depends on the author, it is more difficult than
the facial expression recognition task of a person. In
this paper, we propose a facial expression recognition
model using landmarks for different styles of sketch.
By inputting landmark into the facial expression
recognition model in addition to the facial image,important parts of the face are emphasized． The
accuracy of the model is improved compared to theconventional research in which only the facial image
is input.

SHEN XINNAN

Chen Kai

Mori

Automatic summarization of

Tatsunori

minutes of the meeting

Katsunori

Adaptation and delay

Okajimacompensation effects ofincoherent visual information in
hand movements

Unlike the ordinary document summary, the minutes
summary is required a special summary format thatconsists of the "question of the members" and thecorresponding "answer of the governor". However,there are difficulties that one statement in theminutes is very long, the question and the answer
wide apart, and maybe there are multiple answers to
one question. To solve these problems, this study
summarizes by considering the structure of the
discussion. We constructed detailed rules from someminutes’ characteristics and determine the positionof questions and answers. Experimental result showsthat the proposed method improves the ROUGE valueof the minutes summary.
In this study, we investigated an adaptation effect anda compensation effect for motion delay by modulating
the gain = (speed of hand movement in virtualenvironment) / (speed of real hand movement) in VR
spaces. The experimental results showed thatparticipants adapted to such inconsistentenvironments where the gain is not 1 in a short time,
and that motion delay can be partially compensatedby setting the gain more than 1. In addition, it was
shown that working efficiency in three-dimensional
spaces with a motion delay can be improved bymodulating the position gain appropriately.

YANG LIU

OkajimaImage processing method and theIn this study, I developed a method to control

katsunorivisual perception mechanism ofraindrops in moving images using image processing

rain strength

technology and clarified the visual mechanism onperception of rain intensity. I conducted experiments
to evaluate the perception of rain intensity bymodulating the number and size distribution ofraindrops and brightness contrast in moving images
Using the proposed method. The results showed thatthe number, size distribution, and brightness contrastof raindrops affect the perception of rain intensity.
Finally, a prediction equation for the perception wasderived by analyzing the experimental data.