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2022　Engineering Literacy IV d

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Academic unit or major
School of Engineering
Instructor(s)
Aoki Hirotaka  Shinozaki Takahiro  Nakahara Hiroki  Fukuda Emiko  Kawasaki Ryo  Matsumoto Ryutaroh  Takahashi Atsushi  Hara Yuko  Nagai Takehiro  Yu Jaehoon  Yoshimura Natsue  Li Dongju  Jinguji Akira 
Class Format
Lecture / Exercise    (Face-to-face)
Media-enhanced courses
Day/Period(Room No.)
Thr5-6(<初回>, W611　　　　　　　　　　, <前半>, W935, <後半>, W621)  
Group
d
Course number
XEG.B104
Credits
1
Academic year
2022
Offered quarter
4Q
Syllabus updated
2022/5/11
Lecture notes updated
-
Language used
Japanese
Access Index

Course description and aims

This course aims to become a bridge between general education at high school and specialized education in the subjects of No.200 or higher. This course also aims to cultivate not only basic knowledge of engineering but also sense and attitude for problem solving so that the freshmen of School of Engineering can learn actively specialized subjects after sophomore.
By taking all Engineering literacy I-IV, the students experience the following all seven subjects in Engineering Literacy.
【Manufacturing process 】
【Mechanical Design (Idea Realization)】
【Mechanical Design (CAD)】
【Control】
【Wireless electric car with microcomputer】
【Communication, Computation, and Intelligent Information Processing】
【Management Technology and Mechanism Design (Industrial Engineering and Economics)】

Student learning outcomes

By completing this course, students will be able to:
【Management Technology and Mechanism Design (Industrial Engineering and Economics)】
1) understand the outline of Industrial Engineering (IE) techniques.
2) apply IE techniques to simple cases.
3) understand the fundamental concepts of game theory and the significance of institutional design through participating economic experiment.
【Communication, Computation, and Intelligent Information Processing】
1) explain the connection between basic academics and the latest intelligent information processing techniques
2) explain the basic principle of the artificial neural network.
3) login to a supercomputer system and perform a massive computation.

Keywords

【Management Technology and Mechanism Design (Industrial Engineering and Economics)】
Management Technology, Industrial Engineering, Cognitive Engineering, Game Theory, Mechanism Design
【Communication, Computation, and Intelligent Information Processing】
Deep learning, neural network, intelligent information processing, parallel computing, communication

Competencies that will be developed

✔ Specialist skills Intercultural skills Communication skills Critical thinking skills ✔ Practical and/or problem-solving skills

Class flow

【Management Technology and Mechanism Design (Industrial Engineering and Economics)】
The lecture explains an outline of the Industrial Engineering techniques and their examples (Cognitive Engineering and Game Theory).
【Communication, Computation, and Intelligent Information Processing】
This course explains the connection between the latest deep learning based intelligent information processing technique and basic academic areas such as linear algebra, calculus, probability, numeric optimization, graph theory, and biological information processing, as well as network and computer techniques that provide the computation environment. Moreover, students choose a topic from image, speech, and text processing, and run a preliminary experiment using a deep neural network on a TSUBAME super-computer or a cloud computer. The first half of this lecture explains deep learning with its connection to various academic areas and computer techniques. The latter half is an exercise where students train and evaluate a deep neural network of their choice.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction Conduct class interview. Learn outline of Industrial Engineering techniques (Game theory). Learn how to use software.
Class 2 Industrial Engineering Techniques 1(Game theory) Understand the fundamental concepts of game theory and the significance of institutional design through participating economic experiment.
Class 3 Industrial Engineering Techniques 2(Cognitive task analysis) Carry out an evaluation of interface by applying cognitive task analysis technique.
Class 4 Industrial Engineering Techniques 3(Cognitive task analysis) Carry out an evaluation of interface by applying cognitive task analysis technique.
Class 5 Intelligent information processing I Can explain the basics of deep neural network
Class 6 Intelligent Information Processing II (Use of computer resource through Internet) Can access a crowd service through the Internet and run a script to train and evaluate a neural network.
Class 7 Intelligent Information Processing III (Train and evaluate deep neural network) Can look inside the script to get an overview and explain how neural net learning and evaluation is implemented.

Out-of-Class Study Time (Preparation and Review)

To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.

Textbook(s)

None required

Reference books, course materials, etc.

Documents will be distributed

Assessment criteria and methods

【Management Technology and Mechanism Design (Industrial Engineering and Economics)】
Evaluate short reports.
【Communication, Computation, and Intelligent Information Processing】
Evaluate the report.

Related courses

  • XEG.B101 ： Engineering Literacy I
  • XEG.B102 ： Engineering Literacy II
  • XEG.B103 ： Engineering Literacy III
  • XEG.B104 ： Engineering Literacy IV

Prerequisites (i.e., required knowledge, skills, courses, etc.)

This lecture is only for the freshmen of School of Engineering.
Students are strongly recommended to take all Engineering literacy I-IV to experience all subjects in Engineering Literacy.

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