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A Proposal of the Improved Method for Measuring Insulation Resistance between a Photovoltaic Module String and the Earth using the Self-biased Method

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IEEJ Transactions on Power and Energy 2025年第1期145卷 13-20页

作者： Kazama, Takuro Kato, Kazuhiko Doctoral Program in Risk and Resilience Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba305-8573 Japan Renewable Energy Research Center National Institute of Advanced Industrial Science and Technology 2-2-9 Machiikedai Koriyama963-0298 Japan

For safe operation of a photovoltaic generating system, an insulation monitoring function, which can immediately detect deterioration of insulation between photovoltaic module strings and the earth, is indispensable. This function requires accurate measurement, low leakage current and suppression of rising voltage against the earth. In this paper, a new insulation monitoring method of photovoltaic module strings is proposed by the improved existing self-biased method that has an inevitable voltage rise under measurement. In this new method, both terminals of photovoltaic module strings are always connected to the ground with appropriate resistors. Theoretical discussion and experiments for this new method showed precise measurement, and acceptable leakage current under various outdoor conditions. In addition, it was confirmed that this method could sufficiently decrease in the voltage rise compared with the existing self-biased method. © 2025 The Institute of Electrical Engineers of Japan.

关键词： Photovoltaics

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Establishing Utilization Decision Criteria for Open-Source Software Projects Based on Issue Resolution Time Evaluation

Establishing Utilization Decision Criteria for Open-Source S...

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IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW

作者： Keisuke Inoue Kazuhiko Tsuda Doctoral Program in Risk and Resilience Engineering University of Tsukuba Tsukuba Japan Faculty of Business Sciences University of Tsukuba Tsukuba Japan

ISBN: (数字)9798331534677

ISBN: (纸本)9798331534684

In the face of growing demand for high-quality software solutions at reduced costs and development times, the use of open-source software (OSS) has become increasingly prevalent. This study evaluates the speed of OSS support activities—an essential quality factor for OSS users—and proposes a method for early-stage evaluation based on issue resolution time. We analyzed 100 popular OSS projects hosted on GitHub, collecting data on issue creation and completion dates. The results indicate a correlation coefficient of 0.587 between 30 and 180 days of observation, aligning with previous findings on OSS support continuity. Notably, a satisfactory correlation of 0.525 was achieved at just 21 days, suggesting that organizations can assess OSS support speed earlier and potentially accelerate their decision-making process. Our findings provide a practical criterion for evaluating the speed of OSS support activities, which may help organizations adopt OSS with greater confidence and enhance productivity in software-related projects. Future research will expand these criteria by exploring additional factors affecting issue resolution time, such as project scale and corporate support.

关键词： Productivity Correlation coefficient Software testing Q-factor Correlation Standards organizations Decision making Open source software Faces Software development management

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Sparse Possibilistic Clustering with L1 Regularization

Sparse Possibilistic Clustering with L1 Regularization

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IEEE International Conference on Granular Computing (GRC)

作者： Ryo Inokuchi Sadaaki Miyamoto Doctoral Program in Risk Engineering University of Tsukuba Ibaraki Japan Department of Risk Engineering University of Tsukuba Ibaraki Japan

Possibilistic clustering is an efficient method to detect high density regions and more robust than fuzzy c-means. However, it is not 'sparse', since a cluster center is expressed as a linear combination of all data. In this paper, we propose a sparse possibilistic clustering method with 11 regularization to find compact clusters. Due to a non- negative constraints for a membership, the baseline constant is introduced into the regularizer. The effectiveness of the proposed method is shown in illustrative examples.

关键词： Clustering algorithms Clustering methods Partitioning algorithms Data mining Noise robustness Machine learning algorithms Machine learning Virtual colonoscopy Euclidean distance Constraint optimization

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Influence of cognitively distracting activity on driver’s eye movement during preparation of changing lanes

Influence of cognitively distracting activity on driver’s e...

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SICE Annual Conference

作者： Huiping Zhou Makoto Itoh Toshiyuki Inagaki Doctoral Program in Risk Engineering Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Japan Department of Risk Engineering Faculty of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (纸本)9784907764302

This paper investigates driverpsilas behavior of checking a traffic situation by analyzing driverpsilas eye movement when the driver is cognitively distracted during preparation of changing lanes. We made an experiment with a motion-based driving simulator under conditions of several types of secondary tasks. Collected data resulted in lower detection rates of intent of changing lanes, less checking behaviors and longer time length of checking behavior. These facts clarified that there are discrepancies between secondary tasks and no secondary one. It showed an influence of cognitively distracting activity on driverpsilas behavior.

关键词： Eye movement Distraction Driver behavior Intent inference Changing lanes Eye Movements Driver Behavior distractability Lanes Drivers detection rate (DR) activity driver circuits

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The influence of different camera perspectives and display devices on Beyond Visual Line of Sight (BVLOS) UAV operations

The influence of different camera perspectives and display d...

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SICE Annual Conference

作者： Nianzi Tu Sungju Maeng Makoto Itoh Doctoral Program in Risk and Resilience Engineering University of Tsukuba Tsukuba Ibaraki Japan Institute of Systems and Information Engineering Center for Artificial Intelligence Research University of Tsukuba Tsukuba Ibaraki Japan

With the growth of the use of drones especially in populated areas, Beyond the Visual Line of Sight (BVLOS) operation is expected as a challenge for drone operation. The layout of the Ground Control System (GCS) interface and the drone camera screen via display devices are anticipated to be crucial to the performance of the BVLOS operation. Moreover, the camera perspectives may influence the behavior of operators as the situation. In this study, participants (n=29) in a variety of situations involving multiple takeoff and landing sites, obstacles, and weather were grouped according to the display devices and camera perspectives used. The result shows the Head Mounted Display (HMD) is physically uncomfortable with the possibility of VR sickness, which is more prevalent with the first-person view than the third-person view, but it crashes less and has a straighter flight path. Landing in a narrow area has a high crash rate but is safer with HMD.

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Layered neural network training with model switching and hidden layer feature regularization

Layered neural network training with model switching and hid...

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International Joint Conference on Neural Networks (IJCNN)

作者： K. Kameyama K. Taga Tsukuha Advanced Research Alliance University of Tsukuba Tsukuba Ibaraki Japan Doctoral Program in Risk Engineering Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan

This work introduces a scheme of layered neural network training, which incorporates a dynamical model alteration during training, and regularization of the features extracted in the hidden layer units. So far, use of Model Switching (MS), which is a simultaneous search scheme for an optimal model and parameter, proved to improve training efficiency and generalization ability as a side effect. In MS, the operation to switch the network to a different model involve orthogonalization of the features extracted in the hidden layer. Assuming that the orthogonalization contributes to the observed merits, joint use of MS and orthogonalization of the hidden layer feature by introducing a regularization term in the training, is introduced. The network trained by the proposed training scheme is applied to a pattern recognition problem, and some improvement in training efficiency and generalization ability were observed.

关键词： Neural networks Pattern recognition Feature extraction Switches Supervised learning Systems engineering and theory Data mining Probability density function Size measurement

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Regularization of hidden layer unit response for neural networks

Regularization of hidden layer unit response for neural netw...

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IEEE Pacific Rim Conference on Communications, Computers and Signal Processing

作者： K. Taga K. Kameyama K. Toraichi Doctoral Program in Risk Engineering Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Tsukuba Advanced Research Alliance University of Tsukuba Tsukuba Ibaraki Japan

In this paper, we looked into two issues in pattern recognition using neural networks trained by back propagation (BP), namely inefficient learning and insufficient generalization. We observed that these phenomena are partly caused by the way the hidden layer units responds to the inputs. In order to solve the issues, we introduced regularization of the hidden layer unit response which amounts to suppressing the correlation among the response of the hidden layer units, and pruning the unit with the method unit fusion. The results of using the proposed technique were compared with the case of conventional technique in pattern recognition problems. From the results of the experiments, the rate of correct recognition increased when using regularization in the hidden layer unit response is performed, and it turned out that the required number of training epochs also decreases.

关键词： Neural networks Feature extraction Systems engineering and theory Pattern recognition Computer vision Statistics

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The frustrating search for schizophrenia genes

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American Journal of Medical Genetics Part A 2002年第1期97卷

作者： Ming T. Tsuang Stephen V. Paraone Guest Editor Dr. Tsuang is the Stanley Cobb Professor of Psychiatry Director Harvard Institute of Psychiatric Epidemiology and Genetics and Superintendent and Head Harvard Department of Psychiatry at Massachusetts Mental Health Center. He received an M.D. degree at the College of Medicine National Taiwan University and his Ph.D. at the Institute of Psychiatry Faculty of Medicine University of London. Dr. Tsuang also received a Doctor of Science (D.Sc.) in Psychiatric Epidemiology and Genetics Faculty of Science University of London. Professor Tsuang has worked throughout his career as a clinician teacher researcher and administrator in a variety of private state federal and international mental health care settings. He has been recognized both nationally and internationally for his research in schizophrenia and other major psychiatric disorders including manic-depressive illness and substance abuse. One of his areas of interest is in the rapidly developing field of research related to the interactions between genetic and environmental risk factors for severe mental disorders. Professor Tsuang is the recipient of a myriad of awards for his work among them the First Prize in Clinical Research Award from the American Academy of Clinical Psychiatrists the Rema Lapouse Award for Mental Health Epidemiology from the American Public Health Association and the Stanley Dean Award for Basic Research in Schizophrenia from the American College of Psychiatrists. He is also a Member of the Institute of Medicine National Academy of Sciences and Member Academia Sinica of Taiwan. Recently Professor Tsuang received the Lifetime Achievement Award from the International Society of Psychiatric Genetics and the Taiwanese-American Award for Achievement in Science and Engineering. He has authored or co-authored nearly 400 publications including publications in peer reviewed journals in book chapters and also in books in the areas of psychiatric epidemiology psychiatric genetics nosology of major psychoses ne

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