Hiroshima University Syllabus

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Japanese
Academic Year 2022Year School/Graduate School Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Smart Innovation Program
Lecture Code WSS21201 Subject Classification Specialized Education
Subject Name データ駆動型スマートシステム特別講義
Subject Name
(Katakana)
データクドウガタスマートシステムトクベツコウギ
Subject Name in
English
Special Lecture on Data-Driven Smart Systems
Instructor See the class timetable.
Instructor
(Katakana)
ジュギョウジカンワリヲサンショウ
Campus Higashi-Hiroshima Semester/Term 1st-Year,  First Semester,  2Term
Days, Periods, and Classrooms (2T) Inte
Lesson Style Lecture Lesson Style
(More Details)
 
Lecture
 
Credits 2.0 Class Hours/Week   Language of Instruction J : Japanese
Course Level 6 : Graduate Advanced
Course Area(Area) 25 : Science and Technology
Course Area(Discipline) 11 : Electrical, Systems, and Control Engineering
Eligible Students
Keywords Model-based development (MBD), artificial intelligence, neural networks 
Special Subject for Teacher Education   Special Subject  
Class Status
within Educational
Program
 
Criterion referenced
Evaluation
 
Class Objectives
/Class Outline
This lecture will be divided into two main parts.
[1] Model-based development (MBD) in the application of control technology to products.
[2] Basic concepts and industrial applications of artificial intelligence. 
Class Schedule [1] (7.5 frames)
Although the automotive industry is increasingly trying to develop in line with the MBSE (Model-Based Systems Engineering) approach, the more mature components are lagging behind when it comes to the introduction of control technology. On the other hand, as with other products such as smartphones, upgrading the control technology that forms the backbone is considered essential to improve performance through software upgrades.
In this lecture.
(1) Problems in the introduction of control technology into vehicle development.
(2) 'Functional distribution' utilised to overcome this.
(3) Examples of improved control technology.
The lecture will cover the following topics.
[2] (7.5 frames)
Artificial Intelligence (AI) is a discipline that is currently advancing at an ever-increasing pace. Although today's computers have very high processing speeds, they are not as flexible as humans. Artificial Intelligence aims to turn them into "great wits". One of the directions in this direction is to realize computers that can recognise and understand events in the external world, understand natural language and respond to them, just like humans, without the need to create computers and program that can respond flexibly.
The aim of this lecture is to introduce the basic concepts of artificial intelligence, pattern understanding systems and problem solving systems for the realization of intelligent robots, with the aim of acquiring basic knowledge of the fundamentals of neurocomputers and the realization of autonomous driving of cars and intelligent robots.

Evaluation is mainly based on reports. 
Text/Reference
Books,etc.
Textbooks will be announced on a bulletin board later. 
PC or AV used in
Class,etc.
 
(More Details) PowerPoint. 
Learning techniques to be incorporated  
Suggestions on
Preparation and
Review
Be sure to listen and understand lecture contens, because it is an intensive lecture. 
Requirements Basic knowledge on control engineering is required. 
Grading Method Evaluation is based on the report tasks assigned for each of [1] and [2] above. 
Practical Experience  
Summary of Practical Experience and Class Contents based on it  
Message  
Other This lecture is given as an intensive course, but some lectures may be held on weekdays for the convenience of the lecturers. You will be notified in advance so that you can make arrangements to attend.
 
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. 
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