Investigation of state-of-the-art research in dependability
Overview of the project
Participants read papers on state-of-the-art technologies in dependability including autonomous mobile robot swarms, self-stabilizing distributed systems, and integrated circuit reliability, and deepen understanding through presentations by each person and discussion among participants.
Schedule
15 hours in Semesters II & III
Acceptable for student from October
Yes
Equipment or software to be used
Note PC
Text, reference
Nothing
Maximum number of participants
2
Selection criterion in case of overflow
Interview
Notes
ディペンダブルシステム学
(A2-2) ディペンダブルシステム学先端技術実践
Dependable System
(A2-2) Implementation of state-of-the-art research in dependability
Implementation of state-of-the-art research in dependability
Overview of the project
Participants implement and evaluate state-of-the-art technologies in dependability including autonomous mobile robot swarms, self-stabilizing distributed systems, and integrated circuit reliability, and learn implementation skills and evaluation methods.
Schedule
15 hours in Semesters III & IV
Acceptable for student from October
Yes
Equipment or software to be used
Depends on the project. Kilibots are available.
Text, reference
Depends on the project.
Maximum number of participants
2
Selection criterion in case of overflow
Interview
Notes
ユビキタスコンピューティングシステム
(B3-1) オブジェクト情報を用いた宅内マイクロ行動認識
Ubiquitous Computing Systems
(B3-1) In-home micro-activity recognition using object information
In-home micro-activity recognition using object information
Overview of the project
In-home activity recognition is important for improving the quality of in-home services, such as monitoring the elderly and predicting electricity demand. Conventional activity recognition aims to estimate roughly grained activity classes such as "cooking" and "eating," and it is difficult to apply the recognition results to services. For practical use of activity recognition, micro-activity recognition with finer granularity, such as "washing hands" and "cutting food," is required. Therefore, in this PBL, we will conduct practical exercises on the topic of micro-activity recognition in specific daily activities, using object information based on object detection as an important feature for micro-activity recognition.
Schedule
Semesters II - IV
Acceptable for student from October
Yes
Equipment or software to be used
PC, various sensors (cameras, ambient sensors, motion sensors, etc.). Python will be used for data analysis. scikit learn, keras, and pytorch are used as machine learning libraries.
Text, reference
Handouts are provided.
Maximum number of participants
4
Selection criterion in case of overflow
Interview
Notes
ソフトウェア工学
(A4-2) ソフトウェア工学分野の初学者向け文献調査カリキュラムの作成
Software Engineering
(A4-2) Building an introductory curriculum for reading, learning and presenting research in the field of Software Engineering
Building an introductory curriculum for reading, learning and presenting research in the field of Software Engineering
Overview of the project
It is critical for students to keep up with the latest trends, and progress that has been made in Software Engineering. One way is by obtaining the knowledge from research journals and conference articles. This PBL focuses on conducting a systematic methodology to break down a research article, then how to build a presentation that reflects the key ideas of the paper. The goal is to create a three-month curriculum so that it can be implemented for the incoming master students, and also can be flexible for other fields outside of Software Engineering.
Schedule
November to March
Acceptable for student from October
Yes
Equipment or software to be used
Laptops and signage boards available in SE Lab
Text, reference
Software engineering textbooks, papers, and tools available in SE Lab
The goal of this exercise course is not only for developing programming skills but also for getting an experience of a software development process from upper process to lower process and project management skills through a team development project targeting a certain size of application.
Schedule
4th quarter
Acceptable for student from October
Yes
Equipment or software to be used
ITC's laptops
Text, reference
No texts but slides will be provided on demand.
Maximum number of participants
8
Selection criterion in case of overflow
Determined through interviews
Notes
サイバーレジリエンス構成学
(B6-1) レジリエントなネットワーク機能開発
Cyber Resilience
(B6-1) Development of resilient network function
課題 ID
B6-1
担当教員・研究室・グループ
サイバーレジリエンス構成学
課題名
レジリエントなネットワーク機能開発
実習の概要
レジリエンスを備えるネットワーク機能開発を通して、関連する技術・知識の獲得を目指す。
実習日程の概要
受講生と相談の上、柔軟に設定
秋入学学生の受入れの可否
No
使用する主な装置、ソフトウェアなど
C/C++, python, etc.
教科書、参考書
特になし
受け入れ可能人数
3
希望者が受け入れ可能人数を越えた場合の選択基準
自研究室を優先
特記事項
Project ID
B6-1
Instructor, laboratory, or group
Cyber Resilience
Project title
Development of resilient network function
Overview of the project
The aim of this project is to acquire skills and knowledge related to resilience of network through trying to make resilient network functions.
Schedule
Flexibly scheduled
Acceptable for student from October
No
Equipment or software to be used
C/C++, python, etc.
Text, reference
None
Maximum number of participants
3
Selection criterion in case of overflow
Students in cyber resilience lab have priority
Notes
自然言語処理学
(A9-1) 自然言語処理に関する基盤技術
Computational Linguistics
(A9-1) Fundamental Techniques in Natural Language Processing
Daniel Jurafsky and James H. Martin. Speech and Language Processing https://web.stanford.edu/~jurafsky/slp3/
受け入れ可能人数
2
希望者が受け入れ可能人数を越えた場合の選択基準
面談の上、希望テーマと希望の強さにより決定
特記事項
Project ID
A9-1
Instructor, laboratory, or group
Computational Linguistics
Project title
Fundamental Techniques in Natural Language Processing
Overview of the project
Participants learn basic techniques in natural language processing by running popular tasks such as syntactic parsing, document analysis, information extraction, summarization and machine translation.
Schedule
15 hours during Quarters II, III, and IV
Acceptable for student from October
Yes
Equipment or software to be used
It is task dependent. Instruction will be provided during the project work.
Text, reference
Daniel Jurafsky and James H. Martin. Speech and Language Processing https://web.stanford.edu/~jurafsky/slp3/
Maximum number of participants
2
Selection criterion in case of overflow
By interview. It is determined by your enthusiasm on the assigned topic.
Notes
自然言語処理学
(A9-2) 自然言語処理に関する応用技術
Computational Linguistics
(A9-2) Applications of Natural Language Processing
Daniel Jurafsky and James H. Martin. Speech and Language Processing https://web.stanford.edu/~jurafsky/slp3/
受け入れ可能人数
2
希望者が受け入れ可能人数を越えた場合の選択基準
面談の上、希望テーマと希望の強さにより決定
特記事項
Project ID
A9-2
Instructor, laboratory, or group
Computational Linguistics
Project title
Applications of Natural Language Processing
Overview of the project
Participants tackle various application tasks in natural language processing, including (but not limited to): document processing, knowledge extraction, and knowledge graph construction.
Schedule
15 hours during Quarters II, III, and IV
Acceptable for student from October
Yes
Equipment or software to be used
It is task dependent. Instruction will be provided during the project work.
Text, reference
Daniel Jurafsky and James H. Martin. Speech and Language Processing https://web.stanford.edu/~jurafsky/slp3/
Maximum number of participants
2
Selection criterion in case of overflow
By interview. It is determined by your enthusiasm on the assigned topic.
The objective of this project is to acquire basic knowledge and skills for social computing tasks by investigating literature such as research design, data crawling, data processing, data analysis, etc.
Schedule
15 hours during Quarters II-IV
Acceptable for student from October
Yes
Equipment or software to be used
Python
Text, reference
Will be provided as necessary.
Maximum number of participants
2
Selection criterion in case of overflow
Students in Social Computing Lab. are prioritized.
The objective of this project is to acquire advanced knowledge and skills for social computing tasks by surveying papers presented in recent top conferences and those published in journals. The participants will design a task and implement and evaluate systems for the task.
Schedule
15 hours during Quarters II-IV
Acceptable for student from October
Yes
Equipment or software to be used
Python
Text, reference
Will be provided as necessary.
Maximum number of participants
2
Selection criterion in case of overflow
Students in Social Computing Lab. are prioritized.
Goldsmith, A. (2005). Wireless communications. Cambridge university press.
受け入れ可能人数
2
希望者が受け入れ可能人数を越えた場合の選択基準
自研究室優先
特記事項
Project ID
A12-1
Instructor, laboratory, or group
Network Systems
Project title
Wireless transmission - Basic
Overview of the project
The objective is to set study theme on wireless/wired communication technique. The participants learn basic skill of the signal processing technique and related evaluation method through reading journal papers and text.
Schedule
2nd and 3rd Semesters
Acceptable for student from October
Yes
Equipment or software to be used
PC, matlab, python
Text, reference
Goldsmith, A. (2005). Wireless communications. Cambridge university press.
Goldsmith, A. (2005). Wireless communications. Cambridge university press.
受け入れ可能人数
2
希望者が受け入れ可能人数を越えた場合の選択基準
自研究室優先
特記事項
Project ID
A12-2
Instructor, laboratory, or group
Network Systems
Project title
Wireless communication - Advanced
Overview of the project
This course gives a computer simulation method for a wireless communication. The participant develops programming skill for implementing digital modulation, fading channel, OFDM, spatial filtering techniques.
Schedule
2rd and 4th Semester
Acceptable for student from October
Yes
Equipment or software to be used
PC, matlab, python
Text, reference
Goldsmith, A. (2005). Wireless communications. Cambridge university press.
Maximum number of participants
2
Selection criterion in case of overflow
Student who is a member of the Network Systems Lab. are prioritized.
Notes
生体医用画像
(A20-1) 生体医用画像解析技術に関する研究開発
Imaging-based Computational Biomedicine
(A20-1) Development of tools for biomedical image processing
Development of tools for biomedical image processing
Overview of the project
This project develops tools for biomedical image processing that covers various topics including deep learning, time-series medical image processing, multi-scale image analysis, large-scale medical image database, musculoskeletal anatomical, and functional analysis
Schedule
2nd to 4th terms
Acceptable for student from October
Yes
Equipment or software to be used
PC, software libraries for computer graphics and medical images
Text, reference
Handouts are provided
Maximum number of participants
3
Selection criterion in case of overflow
Interview
Notes
C/C++, Python, Matlab programming skill is preferable.
生体医用画像
(A20-2) 深層学習を用いた生体医用画像解析に関する研究開発
Imaging-based Computational Biomedicine
(A20-2) Deep-learning based biomedical image analysis
The participants learn deep learning and develop basic tools in biomedical image analysis such as image segmentation, registration, and reconstruction. The project uses annotated image database provided by the lab and deep learning as a core tool for understanding the data.
Schedule
2nd to 4th terms
Acceptable for student from October
Yes
Equipment or software to be used
PC, software libraries for computer graphics and medical images
Text, reference
Handouts are provided
Maximum number of participants
3
Selection criterion in case of overflow
Interview
Notes
C/C++, Python, Matlab programming skill is preferable.