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Abstracts for the 6th Congress of Asian Sleep Research Society

Sleep and Biological Rhythms 2009年第4期7卷 A1-A49页

作者： Seog Ju Kim In Kyoon Lyoo Yu-Jin Lee Do-Un Jeong Hirohiko Kanai Masanori Ookubo Atsushi Yoshimura Masako Okawa Noto Yamada Takeshi Munezawa Yoshitaka Kaneita Yoneatsu Osaki Hideyuki Kanda Tadahiro Ohtsu Masumi Minowa Kenji Suzuki Susumu Hijuchi Hiroyuki Suzuki Takashi Ohida Takashi Abe Yoko Komada Shoichi Asaoka Yuichi Inoue Jin-Seong Lee Sang-Yong Cho Deependra Kumar Hruda N. Mallick Velayudhan M. Kumar Mahesh K. Kaushik Akihiro Karashima Noiihiro Katayama Mitsuyuki Nakao Ravindra P. Nagendra Sathiamma Sulekha Sathyaprabha T. Narasappa Pradhan Nityanadan Bindu M. Kutty M. Nirmala P. N. Ravindra Basavaraj Ramappa Tubaki T. N. Sathyaprabha D. Sudhakar G. S. Lavekar C. R. Chandrashekar Kazuyoshi Kitaoka Mika Shimizu Sachiko Chikahisa Kazuo Yoshizaki Hiroyoshi Sei Jong-Won Kim Misa Takegami Shin Yamazaki Yasuaki Hayashino Rei Ono Koji Otani Miho Sekiguchi Shinichi Konno Shunichi Fukuhara Antonia J. Jakobson Paul Fitzgerald Russell Conduit Xin Shirley Li Siu Ping Joyce Lam Wai Man Mandy Yu Yun Kwok Wing Kazue Okamoto-Mizuno Koh Mizuno Mituaki Yamamoto Shuichiro Shirakawa Hirokazu Doi Mikako Kato Kazuyuki Shinohara Masako Tamaki Shiori Matsuda Katsuo Yamazaki Tadao Hori Keiko Ogawa Kazumi Takahashi Kunio Kitahama Katuo Yamazaki Yoshimasa Koyama Kohei Shioda Yugo Ueda Yukiko Nakamura Clara Inoue Kazushige Goto Sunao Uchida Yuko Morita Yoshiko Honda Tohru Kodama Mari Hagihara Toru Nakajima Masato Saito Yoshihiko Koga Shinichiro Tanaka Hiroshi Yamadera Madoka Takahara Sachiko Suwa Minoru Onozuka Sadao Sato Fumiharu Togo Taiki Komatsu Takeshi Mitani Jongbae Choi Bin Zhang Taeko Sasai Hiromi Mitsubayashi Mitsuhiro Ohtsu Isao Hasegawa Tatsuya Ishii Akira Komori Asami Suzuki Yue Nakahara Mitsuyasu Hiroki Mariko Nakauma Nobuo Someya Tomomasa Ochiai Shouhei Komori Rayleigh Ping-Ying Chiang Zai-Ting Yeh Seong T. Kim Seung H. Yoon Jeong S. Kwon Jong H. Choi Hyung J. Ahn Youngsoo Kim Bolortuya Yunren Lichao Chen Radhika Basheer Robert W. Mccarley Robert E. Strecker Makoto Honda Tetsuaki Arai Miyuki Fukazawa Yutaka Honda Kuniaki T Department of Psychiatry Gachon University of Medicine and Science Incheon Republic of Korea Department of Psychiatry Seoul National University Seoul Republic of Korea Department of Neuropsychiatry and Center for Sleep and Chronobiology Seoul National University Hospital Seoul Republic of Korea Department of Neuropsychiatry Seoul National University Hospital Seoul Republic of Korea Seoul National University Hospital Seoul Republic of Korea Department of Psychiatry Shiga University of Medical Science Otsu Japan Division of Public Health Department of Social Medicine Nihon University School of Medicine Tokyo Japan Department of Public Health Nihon University School of Medicine Tokyo Japan Division of Environmental and Preventive Medicine Department of Social Medicine Faculty of Medicine Tottori University Yonago Japan Department of Hygiene and Preventive Medicine Fukushima Medical University Fukushima Japan Department of Public Health Showa University School of Medicine Tokyo Japan Faculty of Humanities Seitoku University Matsudo Japan Section on Behavioral Science Division of Clinical Research National Hospital Organization Kurihama Alcoholism Center Yokosuka Japan Department of Otolaryngology Second Hospital Fujita Health University Nagoya Japan National Hospital Organization Kurihama Alcoholism Center Kanagawa Japan Metropolitan Police Department Criminal Investigation Laboratory Tokyo Japan Japan Somnology Center Neuropsychiatrie Research Institute Tokyo Japan Department of Somnology Tokyo Medical University Tokyo Japan Japan Somnology Center Neuropsychiatric Research Institute Tokyo Japan Department of Somnology Tokyo Medical and Dental University Tokyo Japan Center for Sleep and Chronobiology Department of Psychiatry and Behavioral Science Seoul National University College of Medicine Seoul Republic of Korea Department of Psychiatry and Behavioral Science Center for Sleep and Chronobiology Seoul Republic of Korea Department of Physiology Al

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Background subtraction under varying illumination

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Systems and Computers in Japan 2006年第4期37卷 77-88页

作者： Matsuyama, Takashi Wada, Toshikazu Habe, Hitoshi Tanahashi, Kazuya Graduate School of Informatics Kyoto University Kyoto 606-8501 Japan Mitsubishi Electric Corporation NTT Data Corporation Department of Intelligence Science and Technology Graduate School of Informatics Kyoto University International Association for Pattern Recognition IEICE Information Processing Society of Japan Japanese Society for Artificial Intelligence IEEE Computer Society Department of Computer and Communication Sciences Faculty of Systems Engineering Wakayama University IEEE

Background subtraction is widely used as an effective method for detecting moving objects in a video image. However, background subtraction requires a prerequisite in that image variation cannot be observed, and the range of application is limited. Proposed in this research paper is a method for detecting moving objects by using background subtraction that can be applied to cases in which the image has varied due to varying illumination. This method is based on two object detection methods that are based on different lines of thinking. One method compares the background image and the observed image using invariant features of illumination. The other method estimates the illumination conditions of the observed image and normalizes the brightness before carrying out background subtraction. These two methods are complementary, and highly precise detection results can be obtained by ultimately integrating the detection results of both methods. © 2006 Wiley Periodicals, Inc.

关键词： Lighting

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New evaluations of heavy nuclide data for JENDL-3.3

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Journal of Nuclear science and technology 2002年 39卷 108-111页

作者： Kawano, Toshihiko Matsunobu, Hiroyuki Murata, Toru Zukeran, Atsushi Nakajima, Yutaka Kawai, Masayoshi Yoshida, Tadashi Ohsawa, Takaaki Shibata, Keiichi Nakagawa, Tsuneo Iwamoto, Osamu Baba, Mamoru Ishikawa, Makoto Department of Advanced Energy Engineering Science Kyushu University Kasuga 816-8580 6-1 Kasuga-kouen Japan Data Engineering Inc. Fujisawa 251-0038 5-13-21 Matsu-ga-oka Japan AITEL Corporation Tokyo 105-1106 1-5-9 Shiba Japan Power and Industrial System R and D Laboratory Hitachi 319-1221 Hitachi Ltd. 7-2-1 Omika Japan Research Organization for Information Science and Technology Tokai-mura 319-1106 Ibaraki Japan High Energy Accelerator Research Organization Tsukuba 305-0801 Oho Japan Faculty of Engineering Musashi Institute of Technology Tokyo 158-8557 1-28-1 Tamatsutsumi Japan Department of Nuclear Engineering Kinki University Higashi-Osaka 577-8502 Kowakae Japan Japan Atomic Energy Research Institute Tokai-mura 319-1195 Ibaraki Japan Cyclotron and Radioisotope Center Tohoku University Sendai 980-8578 Aoba-ku Japan Japan Nuclear Cycle Development Institute O-arai-machi 311-1393 Ibaraki Japan

New evaluations of nuclear data for Uranium, Plutonium, and Thorium isotopes which are essential for applications to nuclear technology were carried out for the Japanese Evaluated Nuclear data Library, JENDL-3.3. The objectives of the current release of JENDL were to fix several problems which have been reported for the previous version, to improve the accuracy of the data, and to evaluate covariances for the important nuclides. Quantities in JENDL-3.2 were extensively re-evaluated or replaced by more reliable values. The heavy nuclide data in JENDL-3.3 were validated with several benchmark tests, and it was reported that the current release gave a good prediction of criticalities. © 2014 Atomic Energy Society of Japan.

关键词： Covariance Cross section Direct/semidirect capture Evaluation JENDL-3.3 Neutron Plutonium Prompt fission neutron spectrum Simultaneous evaluation Thorium Uranium

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Development and application of MCAL tools for marine radar instruction

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Computer Applications in Engineering Education 1995年第4期3卷 259-259页

作者： Guirguis, S. Korany, E. Abdel-Bary, A. Institute of Graduate Studies and Research Alexandria University Alexandria Egypt Shawkat K. Guirguis:obtained the BSc and M.Sc. degrees in Computer Science and Automatic Control Faculty of Engineering Alexandria University in 1981 and 1984 respectively. In 1988 he obtained a PhD degree in Electronics and Communications Faculty of Engineering Cairo University co-supervised by the Imperial College of Science and Technology University of London where he spent two years as an academic visitor. His current research interests include software quality management multimedia automatic programming and decision support systems. He is currently a lecturer of Computer Science at the Institute of Graduate Studies & Research Alexandria University. Ezzat A. Korany:received the BS degree in Electrical Engineering (Electronics Section) from the University of Alexandria Egypt in 1971 the MS degree in Electrical Engineering (Computer Section) from Ain Shams University Cairo Egypt in 1977 and the PhD degree in Electrical Engineering (Digital Systems) from Florida Institute of Technology U.S.A. in 1982. He is currently an associate professor of Computer Science at the Institute of Graduate Studies & Research University of Alexandria. His research interests are in data communications and multimedia applications computer networks image processing and pattern recognition. Abdel-Latif A. Abdel-Bary:obtained the BEng degree in Electronics Technology from Arab Maritime Transport Academy in 1986. In 1995 he obtained the MSc degree in Information Technology from the Institute of Graduate Studies & Research Alexandria University. His current research interests include ICAL hypermedia and automatic programming.

In this article a multimedia computer-assisted learning (MCAL) system is presented. The major objective of this work was to investigate the potential of using such systems as tools for transferring instructional course information through various types of computer media as opposed to the classic CAL systems. The philosophy and techniques employed to design the system are investigated. Usage of the implemented system and its merits have been illustrated through its application to teach engineering students and technicians the theory and concepts of marine radar. System design, implementation, test, and revision phases are presented and discussed.

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NEURAL-NETWORK MODEL FOR GENERATING SUBJECTIVE CONTOURS

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SYSTEMS AND COMPUTERS IN JAPAN 1994年第5期25卷 28-37页

作者： ISHIDERA, E TSUCHIYA, M TAKAHASHI, S KURITA, S ARAI, H MIYAUTI, H Faculty of Science and Technology Keio University Yokohama Japan 223 Members Shoichi Kurita (Ph.D.) received his B.E. in 1951 from Keio Univ. where he was a Research Associate in 1954 and then Lecturer Assoc. Prof. and Prof. (1972). Dr. Kurita is engaged in research on opto-electronics and visual information processing. Keio Univ. Award in 1966 and Jap. Illum. Soc. Award in 1971. Member of Jap. Acad. Eng. IEEJ and Soc. Appl. Phys. Advisory Member Jap. Illum Soc. Nonmembers Hiroko Miyauchi received a B.E. in 1991 from Keio Univ. and affiliated with NTT Comm. Data Ltd.

The human visual system has the ability to recognize a virtual line even for a discrete object such as a dot pattern. Even if there is no difference in color or brightness, a clear subjective contour can still be perceived. This phenomenon can be formulated as an interpolation problem. This paper proposes a hierarchical visual information-processing model based on physiological data. The model then is applied to the problem of interpolation, e.g., the perception of a virtual line and a subjective contour. To form the subjective contour, the actual outline of the visual object, the points comprising the subjective contour and the points that move to form a subjective contour must be determined. This is achieved by parallel processing in the proposed model which is composed of complex cells and hyper-complex cells. The complex cells receive the outputs of two kinds of simple cells (S and L), and executes contour detection and interpolation of a dot pattern by global processing. The hypercomplex cell detects the end point and the point of large curvature through which the subjective contour is supposed to pass. All these processes are executed by parallel processing. When the results of processing are ready, the points comprising the subjective contour are determined by weighting. The model in this study is constructed to detect the subjective contour as well as the actual edge by assembling the information from these hierarchical processing.

关键词： SUBJECTIVE CONTOUR VIRTUAL LINE VISUAL CORTEX NEURAL NETWORK MODEL DOG FILTER

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DKAS: A distributed knowledge acquisition system in a DSS

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Journal of Management information Systems 1992年第3期9卷 59-82页

作者： Kiang, Melody Yihwa Chi, Robert T. Tam, Kar Yan Department of Decision and Information Systems Arizona State University Department of Information Systems California State University Long Beach United States Faculty Member and A Weilun Fellow Hong Kong University of Science and Technology Research Scientist position at Electronic Data Systems (EDS)

Knowledge acquisition is the process of accumulating new information and relating it to what is already known. Knowledge acquisition has been regarded as the bottleneck in knowledge-based systems development. In this paper, a distributed knowledge acquisition system (DKAS) is introduced for automating decision rules construction from a set of examples in a decision support system. DKAS has the potential to include various learning mechanisms and employs a multi-agent and parallel processing paradigm. The implementation of a DKAS integrates inductive and deductive learning methods that use different learning strategies. A stock selection problem is used to demonstrate the effectiveness of DKAS in solving classification type problems. The performance of the DKAS in portfolio management is compared to the performance of the NYSE and the S&P 500. The results indicate that the rules derived from using the DKAS outperform both the NYSE and the S&P 500. © 1993, M.E. Sharpe, Inc.

关键词： Decision support systems Deductive learning Distributed knowledge acquisition system Inductive learning Portfolio management

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Process Support and Knowledge Representation in Health Care 1

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丛书名： Lecture Notes in Computer science

1000年

作者： Richard Lenz Silvia Miksch Mor Peleg Manfred Reichert David Riaño Annette Teije

ISBN: (数字)9783642364389

ISBN: (纸本)9783642364372

This book constitutes thoroughly refereed revised selected papers from the BPM 2012 Joint Workshop on Process-Oriented information Systems and Knowledge Representation in Health Care, ProHealth 2012/KR4HC 2012, held in Tallinn, Estonia, in September 2012. The 9 papers presented were carefully reviewed and selected from 19 submissions. In addition the book contains 1 keynote paper and 2 invited contributions. The papers are organized in topical sections named: guidelines and summarization; archetypes and cooperation; and process mining and temporal analysis.

关键词： Artificial Intelligence information Systems Applications (incl. Internet) information Storage and Retrieval database Management User Interfaces and Human Computer Interaction Computer Communication Networks

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Advances in Knowledge Discovery and data Mining 1

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丛书名： Lecture Notes in Computer science

1000年

作者： Joshua Zhexue Huang Longbing Cao Jaideep Srivastava

ISBN: (数字)9783642208416

ISBN: (纸本)9783642208409

The two-volume set LNAI 6634 and 6635 constitutes the refereed proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and data Mining, PAKDD 2011, held in Shenzhen, China in May 2011. The total of 32 revised full papers and 58 revised short papers were carefully reviewed and selected from 331 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas including data mining, machine learning, artificial intelligence and pattern recognition, data warehousing and databases, statistics, knowledge engineering, behavior sciences, visualization, and emerging areas such as social network analysis.

关键词： Artificial Intelligence information Systems Applications (incl. Internet) information Storage and Retrieval database Management Algorithm Analysis and Problem Complexity Computer Communication Networks

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GSFL: A Privacy-preserving Grouping-Split Federated Learning Approach in Resource-constrained Edge Computing Scenarios

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ACM Transactions on Autonomous and Adaptive Systems 1000年

作者： Qi Liu Zhilu Wang Xiaokang Zhou Yonghong Zhang Xiaodong Liu Haiyang Lin Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services China and Nanjing University of Information Science and Technology School of Software China Nanjing University of Information Science and Technology School of Computer Science China Kansai University Faculty of Business Data Science Japan and RIKEN Center for Advanced Intelligence Project Japan Nanjing University of Information Science and Technology School of Automation China Edinburgh Napier University School of Computing UK Nanjing University of Information Science and Technology School of Software China

The advancement of mobile multimedia communications, 5G, and Internet of Things (IoT) has led to the widespread use of edge devices, including sensors, smartphones, and wearables. This has generated in a large amount of distributed data, leading to new prospects for deep learning. However, this data is confined within data silos and contains sensitive information, making it difficult to be processed in a centralized manner, particularly under stringent data privacy regulations. Federated learning (FL) offers a solution by enabling collaborative learning while ensuring privacy. Nonetheless, data and device heterogeneity complicate FL implementation. This research presents a specialized FL algorithm for heterogeneous edge computing. It integrates a lightweight grouping strategy for homogeneous devices, a scheduling algorithm within groups, and a Split Learning (SL) approach. These contributions enhance model accuracy and training speed, alleviate the burden on resource-constrained devices, and strengthen privacy. Experimental results demonstrate that the GSFL outperforms FedAvg and SplitFed by 6.53× and 1.18×. Under experimental conditions with \(\alpha=0.05\), representing a highly heterogeneous data distribution typical of extreme Non-IID scenarios, GSFL showed better accuracy compared to FedAvg by 10.64%, HACCS by 4.53%, and Cluster-HSFL by 1.16%. GSFL effectively balances privacy protection and computational efficiency for real-world applications in mobile multimedia communications.

关键词： Federated learning Split learning Non-IID Clustering

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data Management, Analytics and Innovation 1

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丛书名： Lecture Notes in Networks and Systems

1000年

作者： Neha Sharma Amol Goje Amlan Chakrabarti Alfred M. Bruckstein

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