crack

Fig.1 Spectrum Sharing

Fig. 2 Wireless Multi-hop Network for M2M/IoT Services

The number of wireless network users has remarkably
grown by recent advances in wireless communication
technologies such as Wi-Fi and 5G. This has led to alack of spectrum resources, which has therefore become
an important issue. To overcome this problem, spectrum
sharing technology, whereby a Wi-Fi system temporarily
uses a spectrum band of a WiMAX system, is receivingmuch attention. We propose a dynamic spectrum sharing
method for ultimate utilization of wireless communication
resources.
In addition, new services based on M2M (Machine-toMachine) and/or IoT (Internet of Things) communications
are also attractive. In such a network, tremendous
number of terminals including sensors, actuators, etc.
are connected, so that traditional networking
technologies does NOT work well. We propose a new
network platform to support M2M/IoT services in a
unified manner.
Specifically, we research on the following topics.
- Efficient spectrum sharing- Dynamic cell area optimization- Routing, buffer control, and channel assignment
method in heterogeneous wireless multi-hop networks

Keywords：wireless network, spectrum sharing
E-mail: kazuhiko@is.tokushima-u.ac.jp
Tel.: +81-88-656-7495
Fax: +81-88-656-7495

Image Retrieval Systems
Registration Phase
Feature DB

Content Analysis

Image Dtabase

Color Feature

Mulit-dimensional
Feature Data

Shape Feature

Color FeatureDB

Mulit-dimensional
Feature Data

Shape Feature
DB

Retrieval Phase
Input Image

Content
Analysis

Euclidean
Distance

Mulit-dimensional
Feature Data

Retrieval
Results
Fig.1 An example
ofRobust
content-based
imageSystem
retrieval systems
NoiseMusic Retrieval
J-pop
Classic
etcMusic DB
with noise
Recording Device

Audio Source
No noiseMusic Feature(Pitch, Chord)Music Feature(Pitch, Chord)

Similarity Calculation by
Time-Series Active SearchMusic FeatureDB

without noiseMusic!

Fig.2 Noise robust music
retrievalsystemNoise
Robust Music
Retrieval System

Noise Robust Music Retrieval System• White Noise!"#$%&
2%"&'
8#&&*
;&1

'：()*+&*,)*-%'.&/0)1''：(0#).-'3&4/)#'5'()1&6))7''：(0#).-'3&4/)#'5'90#&:0)%1''：(0#).-'3&4/)#'5';-*7<*='3>'• Speech Noise!"#$%&
2%"&'
8#&&*
;&1

'：()*+&*,)*-%'.&/0)1''：(0#).-'3&4/)#'5'()1&6))7''：(0#).-'3&4/)#'5'90#&:0)%1''：(0#).-'3&4/)#'5';-*7<*='3>'

The number of successes

The number of successes

SN ratio [dB]
Only 1st place of the search result

SN ratio [dB]Within 5th place of the search result

SN ratio [dB]
Only 1st place of the search result

SN ratio [dB]Within 5th place of the search result

Fig.3 Experimental results on music retrieval systems

Content:
Multimedia Information Retrieval (MMIR) is one ofactive research fields of the computer science. An
example of Content-based Image Retrieval systems(CBIR) is shown in Fig.1. CBIR can be organized in two
important modules: Content analysis module extracts
semantic features from images and affects the search
accuracy. Feature indexing module classifies the similarfeatures into the same category and affects the retrieval
speed. Our research group developed the fast searchengine as the feature indexing module.
As for video data, our group has participated the TREC
Video Retrieval Evaluation (TRECVID) since 2005. Some
content-based video retrieval systems were developed
for the Instance Search task of the TRECVID.
As for music data, conventional systems use text dataas the query, such as song titles, singer names, and soon. Our systems can search the similar music tohumming and noisy data. On the noise robust music
retrieval system (Fig.2, Fig.3), the user inputs the part ofmusic data with white and speech noise, and then thissystem can search the similar music without the noise.
Keywordssearch engine, intelligent systems
E-mail: bori@is.tokushima-u.ac.jp
Tel. +81-88-656-7508
Fax: +81-88-656-7508
HP : http://pub2.db.tokushima-u.ac.jp/
ERD/person/10762/profile-en.html

■Fire Detection■ITS■Quality of Skill■Environmental Preservation
crack■Agriculture Application■Human Behavior Observation

Content:
Image Sensing of Indistinct Shape Objects
Image Sensing of Complicated Motion Objects■Fire Detection
e.g. Detection of smoke and fire frame by image processing■ITS(Intelligent Transport Systems)
e.g. Crosswalk observation by image processing■Environmental Preservation
e.g. Dust counter system by image processing■Evaluation of Quality of Skille.g. Evaluation of quality of AWA dancing skill byimage processing■Agriculture Application
e.g. Insect counter system by image processing■Human Behavior Observation
e.g. Observation of computer room by image processing

Keywords：Computer Vision, Image Processing,Image Sensing, Image Recognition
E-mail: <terada@is.tokushima-u.ac.jp>
Tel. +81-88-656-7499
Fax: +81-88-656-7499
HP : http://www-b1.is.tokushima-u.ac.jp/

Content:

A best-known solution of thewell-known Mona-Liza TSP
benchmark（n=100,000) foundby our genetic algorithm.

crack

A best-known solution of oneof the well-known benchmarksof the VRP found by ourmemetic algorithm.

A best-known solution of
one of the well-known
benchmarks of the JSP
found by the proposed
algorithm.

Metaheuristics are approximate methods used for solving
hard combinatorial optimization problems. The field of
metaheuristics for the application to combinatorial
optimization problems is a rapidly growing field of
research. This is due to the importance of combinatorial
optimization problems for the scientific as well as theindustrial world. In our research, we develop very
powerful approximate methods for many combinatorial
optimization problems.
1. The traveling salesman problem (TSP) is one of themost cited NP-hard combinatorial optimization problems.
We have developed a very powerful genetic algorithm(GA) for the TSP, finding very high-quality solutions on
instances with up to 200,000 cities. A similar approachalso shows a very good performance for solving vehicle
routing problems.
2. Job shop scheduling problem (JSP) is one of the moststudied scheduling problems in the OR community. We
have developed a very powerful approximation algorithm
for the JSP. The proposed algorithm is base on a newmetaheuristic framework, which incorporates constraint
propagation techniques into a local search framework.
Keywords：metaheuristics，combinatorial optimization
E-mail: nagata@is.tokushima-u.ac.jp
Tel. +81-88-656-7505
Fax: +81-88-656-7505
HP :Sensor1

crack

Sensor2

Sensor4

Sensor3

AMP(a) Wrist EMG measurement(b) On-line recognition of rock-paper-scissors

Content:
In this research, finger motions are recognized by EMG(electromyography) signals measured using dry-type
electrodes attached to wrist. Target behaviors to berecognized are four finger motions that the Janken,“rock”, “paper”, “scissors” and when not doing anything“neutral”. EMG signal measured in wrist is unstable andnoisy compared to forearm and upper arm. However
wrist EMG can be applicable to control of wearable
devices.
On the one hand, we developed the Simple-FLDA(approximated version of Fisher linear discriminant
analysis), which resolved three drawbacks in matrix-type
FLDA. This algorithm allows a statistical on-line learningof approximated eigenvectors for the high-dimensional
EMG signals. We can obtain a high recognition accuracy
for hand motions using these eigenvectors.
In the next step, we try to recognize every wrist andfinger motion and develop a total control system for
wearable devices using wrist EMG, including the use ofdeep learning.
Keywords：EMG, Simple-FLDA, Statistical learning
E-mail: fukumi@is.tokushima-u.ac.jp
Tel. +81-88-656-7510
Fax: +81-88-656-7510
HP : http://titan.is.tokushima-u.ac.jp/~fukumi/

crackFigure 1 Example of a trie

Figure 2 Example of a double array structure

Content:
Retrieving strings is used in many applications and avery important technology. Retrieval speed and saving
memory are required for string retrieval. A trie (Figure 1)
is one of data structures to retrieve strings, and a double
array (Figure 2) is one of retrieval methods by using thetrie. As large string sets are frequently used due todevelopment of Internet, compact data structures suchas LOUDS are used. The speed of the compact data
structure is very slow compared with the double array.
Hence, my research is to save memory withmaintaining the high speed of the double array. By
constructing the double array for each depth of trie,
values of BASE and CODE are determined for each
depth, and then reduction of number of bits representing
BASE values and saving memory of double array areachievable. Moreover, a method to reduce number ofbits representing CHECK values is under investigation.
Furthermore, this research applies to similar string
retrieval and DNA sequence retrieval.

Keywords：trie, data compression, dababase
E-mail: fuketa@is.tokushima-u.ac.jp
Tel. +81-88-656-7564
Fax: +81-88-655-4424

VR/AR-based Evacuation Training Systems
Enhancing interactivity and reality of evacuation training

Evacuation Training System using LBG
Mainly training school students to be survivors

LBG-based System forDisaster Management

Learning

Local

Applying Pokémon
GO’s idea to disastereducation

AR-based System for Visualizing Disaster
Situations
Superimposing
virtual disastersituations (CG) onto
the real-time vision

Content:(1) Background and Motivation
Anyone can encounter disasters. People should learn how
to survive disasters and recognize that disasters are notsomeone else’s problem. However, traditional disastereducation has not yet been established. For example, intraditional evacuation training, participants simply follow a
fixed route in a normal situation. Disaster education shouldbe improved by ICT to be more interactive and realistic.
(2) Overview
My research team aims to develop new disaster education
systems using ICT (e.g., VR/AR, digital game, and mobile
systems) and practice the systems mainly in schools.
Projects:• VR/AR-based Evacuation Training Systems• Evacuation Training System using LBG (Location-based Game)• LBG-based System for Learning Local Disaster
Management• AR-based System for Visualizing Disaster Situations
Keywords：VR/AR, digital game, and mobile systems
E-mail: mituhara@is.tokushima-u.ac.jp
Tel. +81-88-656-7497
Fax: N/A
HP: http://pub2.db.tokushima-u.ac.jp/
ERD/person/73176/profile-en.html

<図表>

N=2048

N=1024crack
コンタクト不良

N=4096

N=16384

N=8192

N=32768

Content:
Control engineering is a highly developed fundamental
discipline of the engineering, in which systematic design
methods of control systems are developed based on the
optimization by using mathematical models of the plant.
System identification is one of fields in the control engineering
which estimates the plant model systematically from
input/output data of the plant. Subspace identification is acomparatively new method and has attracted attention fromthe middle of the 1990s. However, we have to say its analysis
on the mathematical characteristics such as the variance ofthe estimate are not sufficient.
We have proposed a variance analysis method based on the
gap between the singular subspaces spanned by some data
matrix which enables us to compare several subspacemethods and determine optimal design parameters, etc.
We are now proposing consistent estimates of Kalman gain
and the covariance matrix of the innovations process. Only
asymptotically consistent estimates of them are proposed in
the conventional methods. So, more accurate variance of theestimates will be evaluated.

Keywords：System Identification, Subspace identification,
Variance analysis
E-mail: <ikeda@is.tokushima-u.ac.jp>
Tel. +81-88-656-7504
Fax: +81-88-656-7504

Content:

Human-Friendly Kansei Robot
Understand human emotions,personalities and relations

Intimacy

crack

コンタクト不良

Emotion

Personality

EmotionEstimation

Empathy

Reputation
Analysis

Conversion of Slang
to Standard Word

Personality
Analysis
Intimacy
Estimation

Analysis of Non-verbal Expression on Web

Application to nursing and caring

In order to construct human-friendly kansei robots, my researchmainly focuses on kansei estimation from language ​and reputation
analysis. Individual messages on Social Networking Sites (SNS) are
effective to find out latest trends or public opinions. However, wemight miss important information in the analysis due to the words
that are not included in the existing dictionaries. Considering thatsuch newly-coined words are often representing personal emotionsor the trends of the times, it would be important to construct a
dynamic and effective dictionary for reputation/opinion mining
analysis. The meanings or frequency of use of the newly-coined
words also change depending on the communities in which they areused, and their meanings or tendency of usage receive a lot of
influence from the times. Therefore, it would be necessary to adjust
the information regarding their sensitivity, usage, degree ofimportance, etc. properly according to the environments in which
they are used. My study deals with how to effectively extract
knowledge to automatically construct an effective dictionary thatcan be updated automatically according to analysis purposes. If the
proposed method is realized, more accurate analysis of reputation
or flame based on SNS would be possible.

Keywords ： Affective Computing, Kansei Information
Processing, Kansei Robotics
E-mail: matumoto@is.tokushima-u.ac.jp
Tel. +81-88-656-7654
Fax: +81-88-656-7654

Root
bird

politics
baseball

stork

crane

sportsfootball(a) Example of the usual conceptual knowledge
impression knowledge：
glittercrack
small
mirrormobile phone
light
crane
size
：
phone
large
large
：
：

(b) Example of constructed impression knowledge
Fig. 1 Outline of impression knowledge
1

ph
mo
la

2
6
10

on

3

bi
rg
1

7
11

e

4

le
e

8
12

#

5

#

9

#

13

5

2

9

3

9

5

5

6

link-info：“9-5”

13

7

5

8

link-info：“13-5”

13

4

ilnk-info：“5-9-13”

Fig. 2 Dictionary structure of impression knowledge

Content:
The technology that correctly understands the demandof human is important for the achievement of a manmachine interface with kindness to the person. The
semantic understanding is processed by constructing theknowledge of the concept base, ontology and so on in
the field of natural language processing. For example,"The stork carries" becomes "<bird>+(carry)" byacquiring the semantic concept, however, in this case, itis thought that "{happiness}+(carry)" is correctunderstanding. Thus, an interpretation different from themeaning of the surface is needed to understand themeaning from metaphor, metonymy, onomatopoeia andso on. The sensibility and the impression should be
stored as knowledge.
This research aims to understand the intention by
constructing the impression felt from words as
impression knowledge. The constructed impression
knowledge connects with words and the impression asshown in Fig. 1(b). To store these in the dictionary as theindexes, the dictionary structure shown in Fig. 2 isconstructed.
Keywords： impression knowledge, knowledge dictionary
E-mail: kam@is.tokushima-u.ac.jp
Tel. +81-88-656-7490
Fax: +81-88-655-4424

Medical and habilitation field・To grasp human conditions
・To deliver appropriate
serviceCommon field：
Ambient BCI
crack
コンタクト不良
Industrial field・Human-centered system
・Downsizing of devices

To control
exogenous
stimulususing BCI

Individual Characteristic analysis
Based on EEG analysis
Issues・Intra- and inter- individual characteristic

Noveltyalgorithm

Solutions・To consider human personality
・To propose methods based on gray model【Ambient Brain Computer Interface】
・Concept;
This study constructs novel electroencephalogram (EEG)interface, which is ambient BCI, based on EEG analysis
techniques. Final goal od this study is to create the assist
system for therapy.
・Applications－To detect an inclination, thinking, preference,
uncomfortable feeling－ To control exogenous stimulus【Individual Characteristic Analysis in EEG】
・Concept;
This study analyzes an intra- and inter-individual
characteristic in EEG. One is affected by the influence of
personality. We propose a method to analyze the EEG
considering personality. Also, the proposed method employ atechnique based on gray model.
・Applications－ To make new EEG interface－ To detect the human habit
Keywords：EEG, stimulus, personality
E-mail: sito@tokushima-u.ac.jp
Tel. +81-88-656-9858
Fax: +81-88-656-9858
HP : http://pub2.db.tokushimau.ac.jp/ERD/person/189119/profile-en.html

Driver's Head Posture Categorization

crack(a) Frontal face category(b) Deep head bending category
Head posture classification example..

Content:
This study aims to construct a driver assistance systemthat is able to detect such driver deviations. The system
detects deviation using time-series head motion
information. We analyze driver’s head posture duringsafety verification and propose a method for classifying
head posture using two types of unsupervised neuralnetworks: Self-Organizing Maps (SOMs) and fuzzy
Adaptive Resonance Theory (ART). The proposed
method has a feature based on the hybridization of two
unsupervised neural networks with a seamless mapping
procedure. The proposed method can generate theoptimal number of cluster-generated labels for the target
problem. We experimentally assess the effectiveness ofthe proposed method by adjusting the fuzzy ART network
vigilance parameters. In addition, we indicate thatdriver’s head posture during safety verification can be
categorized according to their individual properties.

Keywords：intelligent transport system, driving behavior
analysis, machine learning
E-mail: momoito@is.tokushima-u.ac.jp
Tel. +81-88-656-7512
Fax: +81-88-656-7512

From the point of view of engineering, my research is
focused on music information processing to searchmusic efficiently, to manage music easily, and to enjoy
music more and more.

crack

入力部

特徴抽出部

接続部

最短経路算出AIST Annotation

曲1 intro 曲2 intro 曲3 intro
曲1 Aメロ 曲2 Aメロ 曲3 Aメロ
曲1 Bメロ 曲2 Bメロ 曲3 Aメロ
曲1 サビ 曲2 サビ 曲3 Bメ
曲1 end 曲2 サビ ロ曲3 サビ曲2 end 曲3 end

ビート構造
リフレイン構造

局所的接続の特徴ベクトル
V = ( クロマベクトル, BPM, 音量,
周波数重心, 音程パワー分散 )

曲1

曲2

曲3

大局的
接続ルール

再生部
曲2 intro 曲2 Aメロ 曲1 Bメロ 曲3 サビ 曲3 end

Figure 1 Medley song genaration system(1) Music information retrieval system based on
audio fingerprint
An audio fingerprint is condensed digital summary,deterministically generated from an audio signal that canbe used to identify and audio sample or quickly locate
similar items in an audio database. We research analgorithm to extract audio fingerprint and to retrieval
music efficiently.
(2) Audio synthesis system for music appreciation
We research audio synthesis techniques to listen music
interactively. For example, medley generation system
and music summarization system.
(3) Structural analysis of music
We research signal processing techniques such as beattracking system, chord recognition system, structuralsegmentation system.
Keywords：Music information processing
Music information retrieval
E-mail: oono@tokushima-u.ac.jp
Tel. +81-88-656-4735>

• Human behavior recognition

Content:• Research Topics• Road signs recognition/ safe driving assist technology• Vehicle recognition and tracking using surveillance cameras• Human Action recognition using wearable sensors

crack• QR code analysis using smart phone• Surveillance camera based human action recognition• Kanji character recognition using smart phone• Intelligent Transportation Systems• Human tracking and recognition suing an Air-drone• Sports skill assisting technology

Keywords：Pattern recognition, Wearable sensors
E-mail: Karungaru@tokushima-u.ac.jp>
Tel. 088-656-7488
顔写真
Fax. 088-656-7488（省略可）
HP : http://www-b1.is.tokushima-u.ac.jp

Early Detection of Depression

crack

Dialogue quality evaluation &Domain-Specific Dialogue Generation

Early detection of psychiatric disorders has become an important
issue for psychological treatment and rehabilitation. In this research
we use semantic and emotion understanding modules for analyzing
message streams of SNS users and propose a model for predicting
their depression probabilities while learning a policy for raising thealert of depression as soon as possible. Alerts can be provided to
SNS users or to the medical and hygiene institutions for further
treatments. In this study, we examine various machine learning
methods in order to resolve the contradiction between two
important targets, that is, the detection accuracy and the alert
raising time.
The rise of voice assistants such as Siri and Alexa is inspiring new
researches for developing human-like dialogue systems. However,as the conversation scenario or purpose varies, uniformly defining“humanity” in the generated dialogues still challenges the academic
society. Without clear constraints such as “humanity” to thelearning target, dialogue systems tend to generate semanticallyconflicting or even ethically violating utterances, which areunacceptable in many real-world use cases. This research focuseson service counter conversation and psychological counselingconversation and experimenting psychological theories with various
machine learning methods for automatically evaluating thehumanity of dialogue systems while improving the quality ofgenerated dialogues.

Keywords：NLP, Early Risk Detection, Dialogue Quality
Evaluation, Dialogue Generation
E-mail: kang-xin@is.tokushima-u.ac.jp
Tel. 088-656-9912
Fax: 088-656-9912
HP : https://researchmap.jp/kang-xin

1) Research backgroundIn recent years, spoken dialog systems such as Apple
Siri have become widespread. However, a smoothconversation like a conversation between humans
cannot be performed. To achieve this, the control ofother elements is indispensable.
Probrem:
Robots can't
interact as naturally
as humans

コンタクト不良

Solution:crack Focus on conversation
tempo and make itsmoother2) Research method
In this study, we focus on the tempo of the dialog(volume, pitch, speed, timing). The purpose of thisresearch is to clarify the elements necessary for the user
to use the spoken dialog system naturally and enjoyably.
3) Application
As a result of this research, it is possible to realize arobot that can have more fun and smooth interaction
by being able to perform conversations with good tempo.
Not only that, this technology is indispensable as ameans for inputting information to a spoken dialoguesystem, robot, and device.

Improve the performanceof each part- Introduction of deep learningØ Response timing control
Ø select response content- Daily conversation voice dataØ large conversation data

Mutual cooperation- Use info from each part
Ø Exchange information
Ø In real timeØ Mutual use of interim results

Keywords： spoken dialog system,
speech recognition, tempo, real-time
E-mail: nishimura@is.tokushima-u.ac.jp
Tel.: +81-88-656-9446
Fax: +81-88-656-9446
HP : http://ryota.nishimura.name/Fig.1: Workflow: Query Suggestion by Text Mining

Fig.2: Our System: Query Suggestion by Text Mining

Content:
The amount of electronic texts is rapidly growing,
making it difficult to analyze them by humans. We
especially focus on ``middle data’’ that is not so big but
not small data. Such data includes all Wikipedia pages
and operation reports in call centers, etc. We propose a``query suggestion system by real-time text mining.’’ Text
mining is a task to analyze how given words are used in
the given corpus (i.e., set of texts). We use the index
structure called ``suffix arrays’’ to provide two types oftext mining results, namely, usage extraction andsynonym extraction, for the given query. (See Figure 2.)
We also propose a system for mining numbers in text.
Many numbers are included in text, but most of existing
text mining systems treat them as mere strings of digits.
We propose a system that provide a function to use``range of numbers’’ as queries. (See Figure 3.)

Keywords：Text mining, Suffix arrays
E-mail: mino@tokushima-u.ac.jp
Tel. +81-88-656-9689
Fax: +81-88-656-9689
Fig.3: Mining Numbers on Text

コンタクト不良

Fig 1. Multi-hop wireless network set on drones. Drones
autonomous navigation and communication considers debattery discharge status of each individual drone.

Fig 2. Simulation of a realistic personal area wireless network
using the help of a Virtual Reality environment.

During the past few years, the interconnectivity between
small devices have rapidly increased. These devices
communicate with one another through networks used inappliances in our homes, medical equipment, security andmonitoring devices. The networks used by these small
devices are often limited and impose many challenges.
Furthermore, these networks may or may not be connectedto the Internet. While these type of networks are often
overlooked, they are one of the pillars that supports IoT(Internet of Things) and the development of future networks.
In these research, the following topics are studied:- Development of new communication protocols for
personal area and body area networks (IEEE 802.15.4 &IEEE 802.15.6 ).
- Measurement of energy consumption and development ofenergy efficient algorithms used in radio transceivers andvehicles (e.g. drones)- Development of simulation tools that support thedevelopment of these networks: (A) Simulated networks
using virtual reality environments. (B) Simulated energy
models for batteries and radio transceivers.
Keywords: Personal Area and Body Area Wireless Networks,
Network Protocols, Energy efficient Networks, Network
Simulation tools, Networks on Virtual Reality Environments.
E-mail: alramonet[ at ]tokushima-u.ac.jp