Educational Visualization
- from e-Learning to Data mining -
Yoshiro Imai
Kagawa University, JAPAN
2217-20 Hayashi-cho, Takamatsu, Japan 761-0396 Email: imai@eng.kagawa-u.ac.jp
September 18th,2017 ICEEE2017@Lodz, Poland
Agenda
◆ INTRODUCTION
◆ PRACTICAL THEMES FOR VISUALIZATION
1. e-Learning for Information Engineering
2. e-Healthcare System for University Students
3. Data Mining for Visualization of Normally Unknown Relation
4. Visualization for Collaborative Design
◆ CONCLUSION & Perspective
September 18th,2017
ICEEE2017@Lodz, Poland
Introduction(1)
◆ Almost all the learners always want to have good overviews about their studies and their
applications.
◆ Visualization, I believe and we understand from our experiences, will be able to provide good and perspective overviews with suitable abstraction and to demonstrate focused functionality even for the beginners in a relatively short period!
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September 18th,2017
Introduction(2)
◆ In the case of designing e-Learning system, it is necessary to employ suitable and effective
visualization approach/methodology for learners to comprehend specific topics more entirely.
◆ Additionally, in the case of data mining and big data analysis, it is definitely necessary to utilize visualization techniques/strategies for the sake of users' efficient understanding.
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e-Learning for Information Engineering(1)
◆ (1) e-Learning System for Network Study: Chiaki Kawanishi and we had developed e-Learning
System for Network Study. The aim of this system is to learn how to design small network topology with routers, hosts and their connection and to demonstrate how a packet transfers from host of source to one of destination based on Routing Information Table.
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Themes of Visualization
September 18th,2017 ICEEE2017@Lodz, Poland
http://stwww.eng.kagawa-u.ac.jp/~imai/H24Labo/Kawanishi/
e-Learning for Information Engineering(2)
◆ (2) e-Learning System for CPU Scheduling
Algorithm: Kei Takeichi, Kyohei Nishiyama, Koji Kagawa and we had developed e-Learning
System for CPU Scheduling Algorithm. The aim of these systems is to learn the characteristics and comparison of three typical scheduling algorithms:
First-Come First-Served, The Shortest Processing Time First, and Round Robin/Time Sharing
Algorithm.
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Themes of Visualization
Running and Animating on Microsoft
Internet Explorer
Result of
FCFS
SRPTF
Round
Robin
September 18th,2017 ICEEE2017@Lodz, Poland
http://ymir.eng.kagawa-u.ac.jp/~nishiyama/vis/
e-Learning for Information Engineering(3)
◆ (3) e-Learning System for Computer Literacy/
Architecture: Yoshio Moritoh, Kazuki
Higashikakiuchi and we had developed e-Learning System for Computer Literacy/Architecture. We
have developed CPU simulators with Java and/or JavaScript for learners to understand how a
computer works graphically during utilization of our CPU simulators in a relatively short period.
ICEEE2017@Lodz, Poland
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Themes of Visualization
September 18th,2017 ICEEE2017@Lodz, Poland
http://stwww.eng.kagawa-u.ac.jp/~imai/H27Labo/Higashikakiuchi/
e-Learning for Information Engineering(4)
◆ (4) e-Learning System for Computer Literacy/
Architecture and Security Education: Especially, Shinya Hara of our Imai Laboratory, a master
course student of Kagawa University, and we
have finished developing Register-Transfer level CPU visual simulator with back trace function for learners to utilize program checking and recognize micro-operation based behavior of inner structure of CPU.
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Themes of Visualization
September 18th,2017 ICEEE2017@Lodz, Poland
http://stwww.eng.kagawa-u.ac.jp/~s17g477/simulator2/index.html
e-Healthcare System for University Students(1)
◆ (1) Health Screening System for Personal Health Data: Eiichi Miyazaki, Hiroshi Kamano and I had designed and implemented an Automatic Health Screening System for reliable and speedup
measurement of personal health data. The aims of this health screening system is to obtain personal health data such as blood pressure and others
automatically and to transfer them to DB server by means of user identification with IC(ID) Card.
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Themes of Visualization
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No1
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No2
e-Healthcare System for University Students(2)
◆ (2) e-Healthcare System for Health Management:
E. Miyazaki, H. Kamano and I had developed and managed an e-Healthcare System for ubiquitous and life-long health management. This system can maintain time series of personal health data in its DB and provide its graphical changes of them
through Web service with user identification. Staffs and students can check their health level/situation by IC Card.
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Themes of Visualization
September 18th,2017 ICEEE2017@Lodz, Poland User Authentication
Temporary data storage
Students’ physical (health) data
Data
collection &
transmission
Campus LAN
Database Server
Information retrieval for individual result from Health Education
No1
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No2
Data Mining for Visualization of Normally Unknown Relation(1)
◆ (1) Performance Evaluation of Line-sensor 3CCD Camera: H. Kawasaki had studied Performance Evaluation of Line-sensor 3CCD Camera and compared specialist’s determination with the results from Numerical Approach. Usually, a
specialist can detect problems of focused such camera’s functionality. With comparison between specialists determination and our approach, it had been confirmed that the latter had obtained more efficient and smart remarks than the former.
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Themes of Visualization
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What is the reason to occur the above phenomenon
called ``Pixel Shift” in the target 3CCD camera ?
Data Mining for Visualization of Normally Unknown Relation(2)
◆ (2) Data Mining by Smartphone and Big Data Analysis for Drivers Behavior: H. Kubota had
performed data mining by smartphone and done data analysis for drivers subconscious behavior at the corner. Smartphones are good to obtain
several data so that such data during car driving can be transferred to specified server through
HTTP connection. Our data mining approach can perform supervised machine learning to analyze data at the cornering to visualize driver’s behavior and characteristics.
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Themes of Visualization
Acquisition of Characteristics Data No1
For Tag Information
For Data Confirmation
For Data Transferring
No1
Procedures in the Server
1. Receiving Data through HTTP connection and storing them into the specific DB
2. Detecting Right/Left Turning with data of Direction Sensing
3. Extracting Characteristics data based on detection of Right/Left turning
4. Calculating Characteristics data for Driving Behavior -> Recognition Procedure
No2
Acquisition of Characteristics Data
No2
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