授業科目名				担当教員
メカトロニクス工学特別講義I				藤代　一成／小澤　賢司／石井　孝明
時間割番号	単位数	コース	履修年次	期別	曜日	時限
GTJ601	1	(未登録)	1	前期	金	III
［概要と目標］
メカトロニクス工学の関連分野において最先端で活躍している大学・民間企業および公的機関の技術者・研究者を講師に招き，最新の研究開発動向について学習する機会を設ける。本年度の概要は以下のとおりで，英語により開講する。 The main target of this course is computer visualization, which provides insights gained through visual analysis of salient structures and behaviors embedded in large and complex data. In this course, several up-to-date R&D topics are chosen to discuss the potentials of the technology, including vector and tensor field visualization, information visualization, visual analytics, XR-based visualization, computational journalism, and computation aesthetics.
[到達目標]
To acquire proficiency in fundamental principles and representative techniques; To be able to visualize practical datasets with standard tools such as Paraview; and To acquire familiarity with recent R&D topics of computer visualization.
［必要知識・準備］
Prerequisite includes basic knowledge about database, computer graphics, image processing, and numerical analysis.
［評価基準］
No 評価項目 割合 評価の観点 1 小テスト／レポート  100  % Short quizzes: 50% (Level of understanding the content of each class) , Report: 50% (Literature survey or visualizing practical datasets)
［教科書］
Handouts will be distributed.
［参考書］
NIH/NSF Visualization Research Challenge Report January 2006. NVAC: Illuminating the Path: The Research and Development Agenda for Visual Analytics, 2005. T. Munzner: Visualization Analysis and Design, AK Peters/CRC Press, 2014. M. Nakajima and I. Fujishiro (eds.): Computer Visualization (in Japanese), Kyoritsu-Syuppan, 2000.
［講義項目］
1: Orientation 2: Visualizing vector fields 3: Visualizing tensor fields 4: Fundamentals of information visualization 5: Introduction to visual analytics 6: XR-based visualization: Juxtaposition and multi-modality 7: Computational journalism 8: Computational aesthetics