Understanding the internal operation of the V1+CNN+FC model and mapping on super-efficient architecture
Overview of the project
The students can understand the internal operation of the image
recognition model written in C language, and perform mapping and
implementation on the Domain Specific Architecture (DSA) which is becoming
one of computing platforms beyond CPU and GPGPU. The principle of operation
of DSA including non-Neumann computers will help combining algorithms and
special hardwares with no von Neumann bottleneck.
Schedule
July and August
Equipment or software to be used
RSIM … V1+CNN+FC model simulator IMAX … DSA with 40x64x4=10240 parallelism and compiler ALVEO … XILINX high-level synthesis accelerator
Text, reference
Will be distributed when needed.
Maximum number of participants
4
Selection criterion in case of overflow
Students who know DSA well take the priority.
Notes
None
コンピューティング・アーキテクチャ（張任遠）
(A1-2) 再構成できるアナログ近似計算回路の設計と評価
Renyuan ZHANG (Computing Architecture Lab.)
(A1-2) Design and Evaluation of Re-configurable Analog Approximate Computing Units
Design and Evaluation of Re-configurable Analog Approximate Computing Units
Overview of the project
This project aims at developing novel computing architectures on the basis of single-wire-driving data representations. As a promising candidate of next generation for high performance computing, analog approximate computing units are implemented. At the end of semiconductor scaling-down, the efforts from this project are expected to achieve high efficiency for general purpose. Escaping from the conventional binary presentations and deductive computations, the hardware implementing approximate computations is developed through machine learning technologies such as regression and statistics, which are powered by some novel algorithms and circuit elements.
Schedule
July, August
Equipment or software to be used
HSPICE, C++, necessary technology libraries
Text, reference
Will be distributed when needed
Maximum number of participants
8
Selection criterion in case of overflow
Who has interests and basic knowledge of VLSI design takes the priority
CARE-IMD-OMI Collaborative PBL-II : Reproducing experiments appeared in top conferences
Overview of the project
This project continues from CARE-IMD-OMI Collaborative PBL-1. In this term, students are required to reproduce experiments appeared in top conferences.
Schedule
Forth semester (Irregular, about 30 hours in total)
Equipment or software to be used
Depends on the topic
Text, reference
Depends on the topic
Maximum number of participants
40
Selection criterion in case of overflow
We will have an interview for students who are not a member of CARE, IMD, and OMI labs.
Notes
Programming skills are necessary depending on the topic. It is necessary to finish CARE-IMD-OMI Collaborative PBL-I in advance.
The objective of this project is to acquire basic knowledge and skills for social computing tasks such as data crawling, data processing, data analysis, etc.
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 III and Ⅳ
Equipment or software to be used
Laptop, Python, etc.
Text, reference
Will be provided as necessary
Maximum number of participants
7
Selection criterion in case of overflow
Students in Social Computing Lab. are prioritized
Notes
ソフトウェア工学（石尾隆、Raula Gaikovina Kula）
(A4-1) プログラミングスタイル・マイニング
Takashi Ishio and Raula Gaikovina Kula (Software Engineering Laboratory)
データ分析にノートパソコンとソフトウェア工学研究室の計算サーバを 使用する。解析プログラムの作成に Java, Python, R を用いる。これらの技術は、演習を通じて習得すればよく、プロジェクト開始時に使える必要はない。
教科書、参考書
資料として論文等を配布する。参考書: Andy Oram, Greg Wilson 編, 久野 禎子, 久野 靖 訳: Making Software - エビデンスが変えるソフトウェア開発, オライリージャパン, 2011.
受け入れ可能人数
10名
希望者が受け入れ可能人数を越えた場合の選択基準
研究及び興味の関連性から判断する。
特記事項
Project ID
A4-1
Instructor, laboratory, or group
Takashi Ishio and Raula Gaikovina Kula (Software Engineering Laboratory)
Project title
Programming Style Mining
Overview of the project
Participants conduct statistical analysis on the usage of programming languages in open source software projects from some perspective, e.g. the impact of project domain and time series. Instructors explain basic techniques for repository mining, source code parsing, and visualization so that participants can acquire data analysis skills and understand programming languages during the project.
Schedule
15 hours in November and December.
Equipment or software to be used
A computation server in Software Engineering Laboratory and a laptop for data analysis. Java, Python, and/or R. The skills are not required to participate the project. Participants are expected to learn the skills through the project.
Text, reference
Instructors provide technical papers related to the project. Reference Book: Andy Oram, Greg Wilson (Ed.): Making Software - What Really Works, and Why We Believe It. O'Reilly, 2010.
Maximum number of participants
10
Selection criterion in case of overflow
Participants' research topics and interests
Notes
ソフトウェア工学（石尾隆、Raula Gaikovina Kula）
(A4-2) 開発者のコーディング能力指標
Takashi Ishio and Raula Gaikovina Kula (Software Engineering Laboratory)
データ分析にノートパソコンとソフトウェア工学研究室の計算サーバを 使用する。解析プログラムの作成に Java, Python, R を用いる。これらの技術は、演習を通じて習得すればよく、プロジェクト開始時に使える必要はない。
教科書、参考書
資料として論文等を配布する。参考書: Andy Oram, Greg Wilson 編, 久野 禎子, 久野 靖 訳: Making Software - エビデンスが変えるソフトウェア開発, オライリージャパン, 2011.
受け入れ可能人数
10名
希望者が受け入れ可能人数を越えた場合の選択基準
研究及び興味の関連性から判断する。
特記事項
Project ID
A4-2
Instructor, laboratory, or group
Takashi Ishio and Raula Gaikovina Kula (Software Engineering Laboratory)
Project title
Developer Coding Ability Metrics
Overview of the project
Participants mine the developer activities in open source software projects to form empirical measurements of ability, e.g. contributions based on experience. Instructors will explain basic techniques for repository mining, source code parsing, and visualization so that participants can acquire paper replication and data analysis skills with practical software data.
Schedule
15 hours in November and December.
Equipment or software to be used
A computation server in Software Engineering Laboratory and a laptop for data analysis. Java, Python, and/or R. The skills are not required to participate the project. Participants are expected to learn the skills through the project.
Text, reference
Instructors provide technical papers related to the project. Reference Book: Andy Oram, Greg Wilson (Ed.): Making Software - What Really Works, and Why We Believe It. O'Reilly, 2010.
Understand the background and purpose of System Assurance then experience system assurance activities demonstrating system and software risks in a convincing manner based on evidence. Also, students acquire discussion skills to describe descriptive techniques, analytical techniques and arguments necessary for argumentation structurally. Corporate visits, workshops with companies, internships may be included. Finally presentation of the results at a SIG in academic organization is planned.
Kohei Ichikawa, Keichi Takahashi (Software Design and Analysis Lab.)
Project title
Exercise in Practical Software Development
Overview of the project
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
Equipment or software to be used
ITC Workstation
Text, reference
No texts but slides will be provided on demand.
Maximum number of participants
20
Selection criterion in case of overflow
Determined through interviews
Notes
ソフトウェア設計学（田中康）
(B5-3) Design as UX演習
Laboratory for Software Design and Analysis, Yasushi Tanaka
Laboratory for Software Design and Analysis, Yasushi Tanaka
Project title
Design as UX PBL
Overview of the project
The purpose of this lecture is to gain practical skills based on the activities of practitioners in terms of the processes and methodologies required for requirements development called ultra-upstream.
Schedule
Every other Saturday from 15:00 to 18:00, camp in August
Implementation and Evaluation of Graphs Algorithms
Overview of the project
The purpose of this course is to learn fundamental graph algorithms such as shortest path, minimum spanning, and max flow. The participants will deeply understand the algorithms by implementing and evaluating them.
The purpose of this course is to learn fundamental distributed algorithms such as spanning tree and leader election. To thoroughly understand the algorithms, the participants will implement the algorithms in kilobots (very small robots). If coming to campus is still difficult, we implement a simulation program and do not use kilobots.
LSI design becomes complex. To address the issue, machine-learning based LSI design techniques have been intensively researched. In this course, the students learn the fundamental of the machine learning and some application examples to the LSI design.
Schedule
October to December, 15 hours
Equipment or software to be used
PC, Python
Text, reference
Handouts are provided
Maximum number of participants
5
Selection criterion in case of overflow
Interview
Notes
ディペンダブルシステム学
(A6-4) ダブルパルステスタ回路の設計と評価
Dependable System Laboratory
(A6-4) Design and evaluation of double-pulse tester
The double pulse circuit is a basic circuit configuration to evaluate the switching characteristics of power devices. In this project, we design a double pulse circuit using a commercial circuit simulator, mount it on a printed circuit board, measure it, and evaluate the switching speed and power consumption of a SiC power MOSFET.
Schedule
October to December, 15 hours
Equipment or software to be used
PC, oscilloscope, constant voltage source
Text, reference
Handouts are provided
Maximum number of participants
5
Selection criterion in case of overflow
Interview
Notes
ネットワークシステム学
(B7-1) 無線通信システムの計算機シミュレーション
Network Systems Laboratory
(B7-1) Computer Simulation for Digital Wireless Communication
課題 ID
B7-1
担当教員・研究室・グループ
ネットワークシステム学
課題名
無線通信システムの計算機シミュレーション
実習の概要
本実習では、ディジタル無線通信技術のMIMO (Multiple-Input Multiple-Output)-OFDM(Orthogonal Frequency Division Multiplexing)通信方式の計算機シミュレータの実装を行う。 ディジタル変復調方式、フェージング伝搬路、OFDM方式、空間フィルタリング等の計算機シミュレーション構成法を習得する。
実習日程の概要
I-IV期の30時間
使用する主な装置、ソフトウェアなど
matlab
教科書、参考書
Simulation and Software Radio for Mobile Communications
受け入れ可能人数
5名
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
特記事項
Project ID
B7-1
Instructor, laboratory, or group
Network Systems Laboratory
Project title
Computer Simulation for Digital Wireless Communication
Overview of the project
This course gives a computer simulation method for a broadband wireless communication based on MIMO (Multiple-Input Multiple-Output) - OFDM ( Orthogonal Frequency Division Multiplexing ) techniques. The aim of this course is to learn how to construct on wireless communication system on computer such as digital modulation/ demodulation, fading channel, OFDM, spatial filtering techniques.
Schedule
30 hours during term I to IV
Equipment or software to be used
matlab
Text, reference
Simulation and Software Radio for Mobile Communications
PC、スマートフォン・タブレット、ウェアラブルデバイス、マイコン（Arduiono、Raspberry Pi など）、サイネージシステム、サーバ、各種センサ、各種アクチュエータを使用する。 データ分析にはPythonを使用する他、アプリケーションを開発をするために必要な言語（python, golang, javascript など）を使用する。
教科書、参考書
資料を配布します。
受け入れ可能人数
8.0
希望者が受け入れ可能人数を越えた場合の選択基準
インタビュー
特記事項
Project ID
A8-1
Instructor, laboratory, or group
Yuki Matsuda / Yugo Nakamura
Project title
IoT Sensing & Nudging for Health Promotion
Overview of the project
Students will design and implement new applied technologies/systems to recognize people's daily acitivity by sensing with IoT devices, and provide promotion (intervention, nudge) for making healthy life. Students are teamed up and cooperate in designing, implementing and evaluating a system and writing an academic paper.
Schedule
Second quarter (15 slot)
Equipment or software to be used
PC, smartphones/tablets, wearable devices, microcontrollers (Arduino, Raspberry Pi etc.), digital signage systems, servers, sensors, actuators, is planned to use for this PBL. Student will use python for data analysis and required programming language for developing system (e.g., python, golang, javascript).
Text, reference
Handouts are provided.
Maximum number of participants
8
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
(A8-2) アクティブラーニングを使ったスマートホームでの行動認識
Ubiquitous Computing Systems lab.
(A8-2) Active learning for activity recognition in smart home
Active learning for activity recognition in smart home
Overview of the project
Labeling of activities of daily living (ADL) in a home is mandatory for constructing a recognition model but it is costly. To reduce the cost for labeling, we focus on active learning which is a kind of semi-supervised learning. In this PBL, the students will develop and evaluate an active learning model for recognizing ADLs, by extending the existing ADL recognition model developed in ubiquitous computing systems laboratory. The students will also develop a new labeling tool for ADLs suitable for active learning by extending the existing labeling tool. Moreover, the students will collect data in a smart home by using the developed tool.
Schedule
3rd and 4th term
Equipment or software to be used
PC and python
Text, reference
Some guidance material is provided.
Maximum number of participants
5
Selection criterion in case of overflow
Enthusiasm and skill
Notes
nothing
ユビキタスコンピューティングシステム
(A8-3) 観光キュレーションシステムの構築
Ubiquitous Computing System Lab.
(A8-3) Development of tour curation system
課題 ID
A8-3
担当教員・研究室・グループ
ユビキタスコンピューティングシステム
課題名
観光キュレーションシステムの構築
実習の概要
動画データの収集，解析，および観光案内システムの構築を行う．
実習日程の概要
II期 （15コマ）
使用する主な装置、ソフトウェアなど
GoPro，pythonなど
教科書、参考書
なし
受け入れ可能人数
5.0
希望者が受け入れ可能人数を越えた場合の選択基準
担当教員の判断による
特記事項
Project ID
A8-3
Instructor, laboratory, or group
Ubiquitous Computing System Lab.
Project title
Development of tour curation system
Overview of the project
We collect video data, analyze it, and construct a tourist guidance system.
In this project, students will learn machine learning (reinforcement learning, imitation learning) algorithms and apply them to real/simulated robots so that the robots can acquire such dynamic motor skills as walking, kendama, throwing and so on.
Schedule
Quarters II, III, IV
Equipment or software to be used
Python, ROS, V-rep
Text, reference
Non
Maximum number of participants
8
Selection criterion in case of overflow
By interview
Notes
It is desirable to take the course "System Development using Middleware" provided from Intelligent System Lab in advance.
The purpose is to learn the skills necessary to construct robotic systems, such as kinematics and sensing and actually construct a robot system by usint the skills.
Schedule
2nd semester (irregular, about 20 hours)
Equipment or software to be used
RGB camera, RGB-D camera, LRF, robots in robotics laboratory.
Text, reference
Handout is provided if necessary.
Maximum number of participants
8
Selection criterion in case of overflow
Interview
Notes
Programming skills are required
ロボティクス
(A10-2) ロボットシステムの構築を助けるツール
Robotics Laboratory
(A10-2) Tools to support development of robotic systems
The applicants first investigate the software tools, libraries, and middlewares that support the development of robotic systems. Next, they learn how to use them.
Schedule
4th semester (irregular, about 20 hours)
Equipment or software to be used
C, C++, Python
Text, reference
Handout is provided if necessary.
Maximum number of participants
8
Selection criterion in case of overflow
Interview
Notes
Programming skills are required
ロボティクス
(A10-3) 家政系とロボット系の学生による家事ロボットに関する議論
Robotics Laboratory
(A10-3) Discussion on household robots with students on home-economics and robotics
Discussion on household robots with students on home-economics and robotics
Overview of the project
We invite the students on home economics and discuss with them the theme on household robots, such as the role of household robots, robotic solution for everyday life, and future life with household robots.
Schedule
3rd or 4th semester (One weekend during 3rd and 4th semesters)
Equipment or software to be used
Not specified
Text, reference
Handout is provided if necessary.
Maximum number of participants
12
Selection criterion in case of overflow
Interview
Notes
It is preferable to speak Japanese
計算システムズ生物学
(A11-1) RによるBayes検定アルゴリズムの実装
Computational Systems Biology Lab.
(A11-1) Implementation of Bayesian analysis using R language
Implementation of Bayesian analysis using R language
Overview of the project
Learn about the concepts of statistical tests based on Bayesian factors and Information criteria and implement the algorithms using R language. And apply those tools for multivariate analysis for biological and health care data for training.
Schedule
15 hours in Quarters III
Equipment or software to be used
R Language (bring your own PC)
Text, reference
Will be distributed when needed.
Maximum number of participants
5
Selection criterion in case of overflow
Based on interview
Notes
None
計算システムズ生物学
(A11-2) 深層学習を用いた生体信号の分析
Computational Systems Biology Lab.
(A11-2) Biomedical Signals analysis using Deep learning
This project is to introduce the relevant knowledge in applying deep learning to biomedical signals (medical images, time-series signal) analysis. You will learn the basic theory and the implementation of deep learning modeling through the project
Schedule
15 hours in Quarters III
Equipment or software to be used
Tensorflow, Keras (Bring your personal laptop)
Text, reference
Will be distributed when needed.
Maximum number of participants
5
Selection criterion in case of overflow
Based on Interview
Notes
None
自然言語処理学
(A12-1) 自然言語処理に関する基盤技術
Natural Language Processing Laboratory
(A12-1) Fundamental Techniques in Natural Language Processing
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, and summarization.
Schedule
15 hours during Quarters II, III, and IV
Equipment or software to be used
Task dependent. Instructed during the project work.
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
Equipment or software to be used
Task dependent. Instructed during the project work.
Hardware Implementation of Cryptographic Algorithms and Hardware Security Evalation
Overview of the project
In this course, we will implement cryptographic algorithms into FPGA, and evaluate performance and hardware security and learn attacks and countermeasures against a cryptographic module through hands-on experience.
Schedule
15 hours
Equipment or software to be used
Verilog HDL, Python, Oscilloscope
Text, reference
Will be distributed when needed.
Maximum number of participants
8
Selection criterion in case of overflow
Interview
Notes
Own windows PC is recommended
情報セキュリティ工学（Youngwoo Kim）
(A13-2) Hardware Security and Electromagnetic Information Leakage Simulation Technique
Youngwoo Kim (Information Security Engineering Lab)
(A13-2) Hardware Security and Electromagnetic Information Leakage Simulation Technique
課題 ID
A13-2
担当教員・研究室・グループ
情報セキュリティ工学（Youngwoo Kim）
課題名
Hardware Security and Electromagnetic Information Leakage Simulation Technique
実習の概要
In this lecture, we focus on simulation and analysis techniques for hardware security and electromagnetic information leakage. For accurate analysis, chip-package-interconnection-PCB must be analyzed simultaneously. During the lecture, these models will be provided and they will be assembled in the simulator. We will analyze various noises affecting the hardware security and information leakages via EM radiation. Leakage mechanism will be visualized using the EM simulator.
実習日程の概要
1 Credit Lecture, about 15 hours
使用する主な装置、ソフトウェアなど
Keysight ADS, MATLAB, HFSS
教科書、参考書
Elements of Electromagnetic
受け入れ可能人数
10.0
希望者が受け入れ可能人数を越えた場合の選択基準
It will be discuss later if happens.
特記事項
Project ID
A13-2
Instructor, laboratory, or group
Youngwoo Kim (Information Security Engineering Lab)
Project title
Hardware Security and Electromagnetic Information Leakage Simulation Technique
Overview of the project
In this lecture, we focus on simulation and analysis techniques for hardware security and electromagnetic information leakage. For accurate analysis, chip-package-interconnection-PCB must be analyzed simultaneously. During the lecture, these models will be provided and they will be assembled in the simulator. We will analyze various noises affecting the hardware security and information leakages via EM radiation. Leakage mechanism will be visualized using the EM simulator.
Schedule
1 Credit Lecture, about 15 hours
Equipment or software to be used
Keysight ADS, MATLAB, HFSS
Text, reference
Elements of Electromagnetic
Maximum number of participants
10
Selection criterion in case of overflow
It will be discuss later if happens.
Notes
情報基盤システム学（垣内正年）
(A14-1) ネットワーク構築
Kakiuchi Masatoshi (Internet Architecture and Systems Lab.)
Kakiuchi Masatoshi (Internet Architecture and Systems Lab.)
Project title
IP network construction
Overview of the project
Constructing IP network by using dynamic routing protocol such as OSPF and RIP on routers on L3 switches and virtual servers. And, setup various servers (ex. DHCP servers, DNS servers, and so on) on the network.
Schedule
from June to August
Equipment or software to be used
laptop computer, L3 switches, VMware
Text, reference
handouts are provided
Maximum number of participants
8
Selection criterion in case of overflow
Given priority to Internet Architecture and Systems Lab.
Introduction to machine learning and its application
Overview of the project
The purpose of this project is to learn the fundamentals of machine learning techniques. The participants will work on data analysis to get the skill to use them appropriately. In addition, we will give some lectures on how to write a scientific report.
Schedule
1st quarter
Equipment or software to be used
Python, Matlab
Text, reference
Bishop, C.: Pattern Recognition and Machine Learning, Cambridge Univ. Press, 2006. Raschka, S.: Python Machine Learning: Unlock Deeper Insights into Machine Learning with This Vital Guide to Cutting-edge Predictive Analytics, Packt Publishing, 2015. Murphy, K.P.: Machine Learning: A Probabilistic Perspective, MIT Press, 2018. Goodfellow, I., Bengio, Y, and Courville, A.: Deep learning, MIT Press, 2016. Hoffman, A.H.: Scientific Writing and Communication, 3rd ed., Oxford Univ. Press, 2017.
Maximum number of participants
17
Selection criterion in case of overflow
Students who need machine learning skill will be given a priority.
Notes
Online presentation using Zoom and its whiteboard function.
Bishop, C.: Pattern Recognition and Machine Learning, Cambridge Univ. Press, 2006. Raschka, S.: Python Machine Learning: Unlock Deeper Insights into Machine Learning with This Vital Guide to Cutting-edge Predictive Analytics, Packt Publishing, 2015. Murphy, K.P.: Machine Learning: A Probabilistic Perspective, MIT Press, 2018. Goodfellow, I., Bengio, Y, and Courville, A.: Deep learning, MIT Press, 2016.
Advanced topics in machine learning and its application
Overview of the project
The purpose of this project is to learn the advanced topics of machine learning. The participants will work on data analysis to get the skill to use them appropriately.
Schedule
2nd quarter
Equipment or software to be used
Python, Matlab
Text, reference
Bishop, C.: Pattern Recognition and Machine Learning, Cambridge Univ. Press, 2006. Raschka, S.: Python Machine Learning: Unlock Deeper Insights into Machine Learning with This Vital Guide to Cutting-edge Predictive Analytics, Packt Publishing, 2015. Murphy, K.P.: Machine Learning: A Probabilistic Perspective, MIT Press, 2018. Goodfellow, I., Bengio, Y, and Courville, A.: Deep learning, MIT Press, 2016.
Maximum number of participants
17
Selection criterion in case of overflow
Students who received a course "Introduction to machine learning and its application" will be given a priority.
Notes
Online presentation using Zoom and its whiteboard function.
生体医用画像
(A16-1) 生体医用画像解析技術に関する研究開発
Imaging-based Computational Biomedicine Lab
(A16-1) 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
Equipment or software to be used
PC, software libraries for computer graphics and medical images
Text, reference
Handouts are provided
Maximum number of participants
5
Selection criterion in case of overflow
Interview
Notes
C/C++, Python, Matlab programming skill is preferable.
生体医用画像
(A16-2) 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 Lab
(A16-2) 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
Equipment or software to be used
PC, software libraries for computer graphics and medical images
Text, reference
Handouts are provided
Maximum number of participants
5
Selection criterion in case of overflow
Interview
Notes
C/C++, Python, Matlab programming skill is preferable.
大規模システム管理（笹部 昌弘，張 元玉）
(A17-1) Pythonによる大規模システムデータ処理・分析・可視化
Masahiro SASABE, Yuanyu ZHANG (Large-Scale Systems Management Lab.)
(A17-1) Python learning: processing, analyzing, and visualizing large-scale system data
Masahiro SASABE, Yuanyu ZHANG (Large-Scale Systems Management Lab.)
Project title
Python learning: processing, analyzing, and visualizing large-scale system data
Overview of the project
As for the various types of large-scale system data, e.g., road network data and blockchain data, students will learn how to retrieve the data, process and analyze the retrieved data, and make graphs from the analytical results.
Students in Large-Scale Systems Management Lab. are prioritized
Notes
Python programming skills are required. The recommended operating environment is a Mac device with macOS Catalina and Python 3.8.2+. (The initial settings of Python and the related software will be done at the first lecture.) Other operating environments are not supported. The lecture may be given remotely through a Webex meeting by considering the COVID-19 situations.
大規模システム管理（張 元玉，笹部 昌弘）
(A17-2) ブロックチェーンの実装
Yuanyu ZHANG, Masahiro SASABE (Large-Scale Systems Management Lab.)
Yuanyu ZHANG, Masahiro SASABE (Large-Scale Systems Management Lab.)
Project title
Implementing Blockchain
Overview of the project
Students are expected to learn some basic knowledge of the blockchain and implement
a simplified one during this project. In addition, they will also learn some other
skills, like Python programming, P2P networking and cryptographic algorithms.
Schedule
3rd and 4th quarters
Equipment or software to be used
Mac, Python3
Text, reference
Materials will be distributed if required
Maximum number of participants
7
Selection criterion in case of overflow
Students in Large-Scale Systems Management Lab. are prioritized
Notes
Python programming skills are required.
知能コミュニケーション
(A18-1) コミュニケーション支援技術
Augmented Human Communication Laboratory
(A18-1) Information technology for supporting human communication
課題 ID
A18-1
担当教員・研究室・グループ
知能コミュニケーション
課題名
コミュニケーション支援技術
実習の概要
音声・言語・生体信号等多様な情報を活用するコミュニケーション支援技術の習得
実習日程の概要
第II期〜第IV期
使用する主な装置、ソフトウェアなど
研究室で手配（タスクにより異なる）
教科書、参考書
特になし
受け入れ可能人数
12.0
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
特になし
Project ID
A18-1
Instructor, laboratory, or group
Augmented Human Communication Laboratory
Project title
Information technology for supporting human communication
Overview of the project
Learning information technology for supporting human communication using various information from speech, language, biological signals, etc.
Schedule
2nd-4th semesters
Equipment or software to be used
To be prepared in AHC lab. (different according to tasks)
Text, reference
Nothing in particular
Maximum number of participants
12
Selection criterion in case of overflow
Students in AHC lab. will be given preference.
Notes
Nothing in particular
知能コミュニケーション
(A18-2) コミュニケーション支援システム
Augmented Human Communication Laboratory
(A18-2) System development for supporting human communication
課題 ID
A18-2
担当教員・研究室・グループ
知能コミュニケーション
課題名
コミュニケーション支援システム
実習の概要
音声・言語・生体信号等多様な情報を活用するコミュニケーション支援システムの開発・評価
実習日程の概要
第III期〜第IV期
使用する主な装置、ソフトウェアなど
研究室で手配（タスクにより異なる）
教科書、参考書
特になし
受け入れ可能人数
12.0
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
特になし
Project ID
A18-2
Instructor, laboratory, or group
Augmented Human Communication Laboratory
Project title
System development for supporting human communication
Overview of the project
Developing a system supporting human communication using various information from speech, language, biological signals, etc.
Schedule
3rd-4th semesters
Equipment or software to be used
To be prepared in AHC lab. (different according to tasks)
Text, reference
Nothing in particular
Maximum number of participants
12
Selection criterion in case of overflow
Students in AHC lab. will be given preference.
Notes
知能システム制御研究室（小林 泰介）
(A19-1) ミドルウェアを用いたシステム開発
Taisuke Kobayashi (Intelligent System Control Lab.)
Taisuke Kobayashi (Intelligent System Control Lab.)
Project title
System Development using Middleware
Overview of the project
In this project, students will learn how to use middlewares necessary to control systems through practical training. Specifically, depending on the interests of the students, they will build respective control systems that can receive sensor values and send control inputs for real machines or simulation models, such as robot arms and/or inverted pendulum robots.
Schedule
Quarters II, III, IV
Equipment or software to be used
Python, ROS, Matlab
Text, reference
None
Maximum number of participants
8
Selection criterion in case of overflow
Students in Intelligent System Control Lab. and Robot Learning Lab. are prioritized
Notes
知能システム制御研究室（花田研太，杉本謙二）
(A19-2) MATLABを用いた制御システムの開発
Kenta Hanada and Kenji Sugimoto (Intelligent System Control Lab.)
(A19-2) Development of Control Systems with MATLAB
Kenta Hanada and Kenji Sugimoto (Intelligent System Control Lab.)
Project title
Development of Control Systems with MATLAB
Overview of the project
In this project, students will learn a control system with MATLAB. The students will learn about system control theory and how to implement simulations by using MATLAB and Simulink. After that, the students will develop a control system with MATLAB and Simulink for real machines such as inverted pendulum.
Schedule
15 hours within Quarters III, IV.
Equipment or software to be used
MATLAB, Simulink, and some real robotics such as an inverted pendulum.
Text, reference
Available in Japanese for a reference.
Maximum number of participants
8
Selection criterion in case of overflow
Students in Intelligent System Control Lab. and Robot Learning Lab. are prioritized.
Notes
Please make sure that you take a course of “System Development using Middleware” which is also held by Taisuke Kobayashi (Intelligent System Control Lab.).
情報基盤システム学（藤川和利，新井イスマイル）・情報セキュリティ工学（林優一，藤本大介）
(A20-1) SecCap PBL
Kazutoshi Fujikawa, Ismail Arai (Internet Architecture and Systems Lab.), Yuichi Hayashi, Daisuke Fujimoto (Information Security Engineering Lab.)