AY 2020 Graduate School Course Catalog AY 2020 Graduate School Course Catalog AY 2020 Graduate School Course Catalog
| 2021/01/30 |
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| 開講学期 ／Semester |
2020年度／Academic Year 集中 ／Intensive course |
|---|---|
| 対象学年 ／Course for; |
1st year , 2nd year , 3rd year |
| 単位数 ／Credits |
1.0 |
| 責任者 ／Coordinator |
TSUKAHARA Tsuneo |
| 担当教員名 ／Instructor |
TSUKAHARA Tsuneo, ISHIBASHI Shiro, NAKAMOTO Junji |
| 推奨トラック ／Recommended track |
－ |
| 履修規程上の先修条件 ／Prerequisites |
－ |
| 使用言語 ／Language |
－ |
| 更新日／Last updated on | 2020/11/18 |
|---|---|
| 授業の概要 ／Course outline |
In recent years, there is a growing demand for the creation of innovative businesses based on the university's research. University-Business research collaboration, such as collaborative research projects, is one of key approaches to meet the demands. In order to achieve goals of the projects, it is often considered essential to obtain and utilize the intellectual property (IP) rights. In addition, IP management are becoming more important for not only these research projects but any R&D project of new technologies. In order to actively engage with these research project, the researchers need to be familiar with the IP system, especially patent system because it can protect the technical idea of research. |
| 授業の目的と到達目標 ／Objectives and attainment goals |
In the first half of the course, students of this class can mainly learn overview of IP, and learn how to file patent applications/how to obtain patent rights. In particular, the students can study how to draft an invention proposal based on research results for filing patent applications. In the last half of the course, the students are able to deepen their understanding of the use of IP, especially in relation to information and communication technology, through group discussions and exercises on some topics. |
| 授業スケジュール ／Class schedule |
Day 1 1. Overview of Intellectual Property (IP) 2. Overview of the patent system 3. Preparing documents related to patent applications (1) Overview of patent applications 4. Preparing documents related to patent applications (2) Search for prior art documents Day 2 5. Preparing documents related to patent applications (3) Preparation of an invention proposal 6. Exercise (drafting an invention proposal) 7. Exercise (drafting and invention proposal) 8. Exercise (searching the prior art) Day 3 9. Patent eligibility of computer software/Artificial Intelligence(AI)/Internet of Things(IoT) 10. Utilization of open source software 11. Discussion (Patent eligibility of computer software/AI/IoT, open source software) Day 4 12. Relationship between technical standards and patents 13. Open and close strategy 14. Discussion (Relationship between technical standards and patents, Open and close strategy) |
| 教科書 ／Textbook(s) |
In principle, handouts will be distributed in class. |
| 成績評価の方法・基準 ／Grading method/criteria |
Students will be evaluated on the basis of their contribution to each lecture and discussion (50%) and one report (50%). |
| 履修上の留意点 ／Note for course registration |
In principle, absence from the class is avoided in order to concentrate on acquiring practical knowledge in a short period of time. If it is truly unavoidable, students will be asked to submit additional reports afterwards, and the results will be reflected in their grades. |
| 参考(授業ホームページ、図書など) ／Reference (course website, literature, etc.) |
NAKAMOTO Junji has 20 years of experience in patent examination, appeal prosecution and operation of intellectual property policies at Japan Patent Office and Intellectual Property Office of Singapore. |
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| 開講学期 ／Semester |
2020年度／Academic Year 後期 ／Second Semester |
|---|---|
| 対象学年 ／Course for; |
1st year , 2nd year , 3rd year |
| 単位数 ／Credits |
1.0 |
| 責任者 ／Coordinator |
PAIK Incheon |
| 担当教員名 ／Instructor |
PAIK Incheon |
| 推奨トラック ／Recommended track |
－ |
| 履修規程上の先修条件 ／Prerequisites |
－ |
| 使用言語 ／Language |
－ |
| 更新日／Last updated on | 2020/09/29 |
|---|---|
| 授業の概要 ／Course outline |
As technology of computer science and engineering is changing rapidly, it is very necessary to catch up with hot issues accordingly for students who are carrying out research in this field. For example, artificial intelligence and its application on several domains, IoT technologies, distributed network and security issues, robotics, big data analytics, Bioinformatics, and other research topics in computer science and engineering can be illustrated as emerging topics. In keeping with this trend, this course deals with survey of current state of the art of hot topics and suggestion of important research issues related to the topics. Free discussions on the contents that have been covered in a course, will fill up possible deficiencies and improve the course with detailed issues among students in the discussion. Topics are decided not only by considering hot research trends based on study fields of GS basically, but by requests from faculties and students. The courses consist of presentation of teaching and discussion with Q&A. |
| 授業の目的と到達目標 ／Objectives and attainment goals |
This course aims to help of giving information and knowledge for students’ research and catching up with fast research changes on computer science and engineering. Also, it can give useful information for some idea on their researches. Through topics covered in this course, students will obtain information and knowledge on important research issues and figure out current state of the art of some hot topics in computer science and engineering, and can apply them to develop an idea for their researches. Grasp of broad knowledge on the issues can give a good chance toward fusion of the technologies too. |
| 授業スケジュール ／Class schedule |
List of tentative topics in this year is as follows. But some topics can be replaced as necessary with other topics such as a special hot topic at some period, key note speech at a conference in UoA, etc. 1. Course Introduction - Incheon Paik 2. Topics on AI and its application - Konstantin Markov 3. Topics on IoT – Lei Jing 4. Topics on Big Data Analytics – Uday Kiran Rage 5. Topics on Parallel/Distributed Computing – Naohito Nakasato 6. Topics on Bio Information Engineering – Xin Zhu 7. Topics on Computer/AI System – Yoichi Tomioka 8. Topics on Security – Chunhua Su |
| 教科書 ／Textbook(s) |
- A lecturer will provide necessary materials. |
| 成績評価の方法・基準 ／Grading method/criteria |
- Participation to discussion in the classes: 30% - Report on research topic survey: 70% |
| 履修上の留意点 ／Note for course registration |
- There can be homework such as pre-reading or material preparation by some lecturers. |
| 参考(授業ホームページ、図書など) ／Reference (course website, literature, etc.) |
- It will be introduced on lecture Web page. |