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A modified lumped parameter model of distribution transformer winding

Global Energy Interconnection 2020年第2期3卷 158-165页

作者： Qingqing Ding Yao Yao Bingqian Wang Jingwei Fu Wei Zhang Chao Zeng Xiaoping Li Stanimir Valtchev State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityHaidian DistrictBeijing100084P.R.China State Grid Hubei Electric Power Co. Research Institute(HBEPRI)Hongshan DistrictWuhan 430077P.R.China Flexible Transmission Engineering Department Nari-Relays Electric Company210003 NanjingP.R.China State Grid Hubei Electric Power Co. LtdHongshan District430077 WuhanP.R.China Department of Electrical and Computer Engineering Faculty of Science and TechnologyUNLPortugal

The modelling of the distribution transformer winding is the starting point and serves as important basis for the transformer characteristics analysis and the lightning pulse response prediction.A distributed parameters model can depict the winding characteristics accurately,but it requires complex *** parameter model requires less calculations,but its applicable frequency range is not *** paper studies the amplitude-frequency characteristics of the lightning wave,compares the transformer modelling methods and finally proposes a modified lumped parameter model,based on the above *** proposed model minimizes the errors provoked by the lumped parameter approximation,and the hyperbolic functions of the distributed parameter *** this modification it becomes possible to accurately describe the winding characteristics and rapidly obtain the node voltage *** proposed model can provide theoretical and experimental support to lightning protection of the distribution transformer.

关键词： Wide band frequency response Distributed parameter model Lumped parameter model Distribution transformer Lightning protection

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The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

arXiv

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

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CRNN Based Jersey-Bib Number/Text Recognition in Sports and Marathon Images

CRNN Based Jersey-Bib Number/Text Recognition in Sports and ...

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International Conference on Document Analysis and Recognition

作者： Sauradip Nag Raghavendra Ramachandra Palaiahnakote Shivakumara Umapada Pal Tong Lu Mohan Kankanhalli Department of Computer Science & Engineering Kalyani Government Engineering College Kalyani India Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Norway Faculty of Computer System and Information Technology University of Malaya Malaysia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University China Department of computer science National University of Singapore Singapore

The primary challenge in tracing the participants in sports and marathon video or images is to detect and localize the jersey/Bib number that may present in different regions of their outfit captured in cluttered environment conditions. In this work, we proposed a new framework based on detecting the human body parts such that both Jersey Bib number and text is localized reliably. To achieve this, the proposed method first detects and localize the human in a given image using Single Shot Multibox Detector (SSD). In the next step, different human body parts namely, Torso, Left Thigh, Right Thigh, that generally contain a Bib number or text region is automatically extracted. These detected individual parts are processed individually to detect the Jersey Bib number/text using a deep CNN network based on the 2-channel architecture based on the novel adaptive weighting loss function. Finally, the detected text is cropped out and fed to a CNN-RNN based deep model abbreviated as CRNN for recognizing jersey/Bib/text. Extensive experiments are carried out on the four different datasets including both bench-marking dataset and a new dataset. The performance of the proposed method is compared with the state-of-the-art methods on all four datasets that indicates the improved performance of the proposed method on all four datasets.

关键词： Text recognition Sports Image recognition Hip Thigh Torso Biological system modeling

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Optimal Kernel Classifier in Mobile Robots for Determining Gases Type

Optimal Kernel Classifier in Mobile Robots for Determining G...

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2018 International Conference on Electrical engineering and computer science, ICECOS 2018

作者： Husni, Nyayu Latifah Muhaajir, M Al Prihatini, Ekawati Silvia, Ade Nurmaini, Siti Yani, Irsyadi Electrical Engineering Politeknik Negeri Sriwijaya Palembang Indonesia Intelligent System Research Group Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia Mechanical Engineering Department Faculty of Engineering Universitas Sriwijaya Palembang Indonesia

ISBN: (纸本)9781538657201

The use of TGS sensor and Arduino could create a robot to be capable of detecting and classifying some gases. In this research, 3 kinds of SVM Kernel Classifiers are investigated. Robots equipped with 3 TGS sensors are used to classify methanol and acetone. Xbee modul is used as a communication medium between robots and server. The robots are run in the experimental environment. When they detect the gas, they will get closer to the source and classify the gas type. The classified gas data is then sent to the server. From this research, it can concluded that polynomial and RBF have better performance in classifying methanol and acetone. © 2018 IEEE.

关键词： Methanol

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Fingerprint Matching Using Bozorth3 Algorithm and Parallel Computation on NVIDIA Compute Unified Device Architecture

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IOP Conference Series: Materials science and engineering 2020年第1期879卷

作者： S Supatmi I D Sumitra Department of Computer System Faculty of Engineering and Computer Science Universitas Komputer Indonesia Indonesia Departemen Magister Sistem Informasi Universitas Komputer Indonesia Indonesia

This paper studied fingerprint matching employing Bozorth3 Algorithm for matching fingerprint and parallel computation employing NVIDIA Compute Unified Device Architecture (NVIDIA CUDA). The objective of this study obtains the percentage and time processing of matching fingerprints. In this study, the fingerprint matching is done with parallel computing is applied to the GPU (Graphics Processing Unit). GPU device used in this study is the CUDA (Compute Unified Device Architecture), which is an Application Programming Interface (API) developed by NVIDIA. The development of applications with fingerprint matching serial computing on CPU and parallel computing on GPU can be applied to the CUDA API. The results from this study can be found in the performance process on the CPU and GPU. The results of this research are the process on CUDA execution time is better than the execution time on the CPU, the process is done at both the computation is to find a match in the fingerprint value.

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Room-Temperature Charge-to-Spin Conversion from Quasi-2D Electron Gas at SrTiO3-Based Interfaces

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physica status solidi (RRL) – Rapid Research Letters 2023年第6期17卷

作者： Utkarsh Shashank Angshuman Deka Chen Ye Surbhi Gupta Rohit Medwal Rajdeep Singh Rawat Hironori Asada X. Renshaw Wang Yasuhiro Fukuma Department of Physics and Information Technology Faculty of Computer Science and System Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka 820-8502 Japan Birck Nanotechnology Center School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907 USA School of Physical and Mathematical Sciences Nanyang Technological University 637616 Singapore Natural Sciences and Science Education National Institute of Education Nanyang Technological University 637616 Singapore Department of Physics Indian Institute of Technology Kanpur Kanpur 208016 India Graduate School of Sciences and Technology for Innovation Yamaguchi University 2-16-1 Tokiwadai Ube 755-8611 Japan School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore Research Center for Neuromorphic AI hardware Kyushu Institute of Technology Kitakyushu 808-0196 Japan

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Harmonized Software Quality Improvement Models for Sudanese SME Based on CMMI

Harmonized Software Quality Improvement Models for Sudanese ...

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International Conference on computer, Control, Electrical, and Electronics engineering (ICCCEEE)

作者： Zeinab Mahmoud Aiman Solyman Arafat Abdulgader Mohammed Elhag Department of Computer Science Faculty of Science and Technology Nile Valley University Sudan School of software engineering South china University of Technology SCUT China Department of Information System University of Bisha Saudi Arabia

ISBN: (数字)9781728110066

ISBN: (纸本)9781728110073

Software institutions recently implement more than one software process model in order to achieve a high value in their products and services. The challenges of implementing several quality models are increasing the risk of Multi-Model Environment (MME) failure and more resources are needed to support the MME. This kind of resources is not available in the Small and Medium Enterprises (SME), especially in Sudanese institutions. This study aims to provide a solution by encouraging the Sudanese SMEs to apply software models in their software development processes. We are seeking to make these institutions understand how to integrate product quality models with software process improvement models. To achieve this goal, we used a systematic harmonization technique to harmonize and map ISO/IEC 25010 standard onto Capability Maturity Model Integrity (CMMI) Dev 1.3 level 2 and 3. Also, we reviewed the related works of the previous studies on MMEs to achieve better results. The results show some of the processes and activities of CMMI Dev 1.3 considering software quality attributes on the early stage of the Software Development Lifecycle (SDLC). On the other hand, we presented how to apply the mapped models and suggest a tool for implementation. This kind of approach gives small organizations the ability to apply multi SPI models.

关键词： Software quality ISO Standards Capability maturity model Organizations Analytical models

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Characterizing Project Evolution on a Social Coding Platform

Characterizing Project Evolution on a Social Coding Platform

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ACIS International Conference on Software engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Koji Toda Haruaki Tamada Masahide Nakamura Kenichi Matsumoto Department of Computer Science and Engineering Fukuoka Institute of Technology Fukuoka Japan Faculty of Information Science and Engineering Kyoto Sangyo University Kyoto Japan Graduate School of System Informatics Kobe University Hyogo Japan Riken AIP Tokyo Japan

Social coding platforms (SCPs) have realized spontaneous software evolution, where new source code and ideas are spontaneously proposed by altruistic developers. Although there are many projects operated by active communities performing spontaneous evolution, it is yet unclear that how such successful projects and communities have been formed and governed. In this paper, we propose a method that can investigate the history of every project in the SCP. Introducing the concept of project as a city, we consider every project in the SCP as a city, where a government and citizens develop a city through collaborative activities. We then identify essential attributes that characterize a state of a city. For each attribute, we develop metrics that quantity the state S(p, t) of a project p at time t. An experimental evaluation investigating GitHub projects of famous code editors shows that the proposed metrics well visualize the history of the projects from essential perspectives of a city.

关键词： Urban areas Software Measurement Encoding Sociology Statistics Government

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Toward evaluating the level of crowd wisdom using interval estimates

Toward evaluating the level of crowd wisdom using interval e...

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作者： Nguyen, Van Du Truong, Hai Bang Merayo, Mercedes G. Nguyen, Ngoc Thanh Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Viet Nam Department Sistemas Informáticos y Computación Universidad Complutense de Madrid Spain Faculty of Computer Science and Management Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50-370 Poland Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh city Viet Nam

Recently, the use of the wisdom of crowds (WoC) for finding solutions to a wide range of real-life problems has dramatically expanded. Prior studies have revealed that diversity, independence, decentralization, and aggregation are the determinants of collective wisdom. However, these findings are often based on the so-called point estimates - single values are used as the representations of individual predictions on the task of estimating unknown quantities or predicting outcomes of future events. In some situations, interval values, which are often called interval estimates, can be used for such representations. Accordingly, one can provide an individual prediction in the form of an interval value including a lower and an upper bounds. Taking into account this kind of representation, in this paper, we present a case study in which collectives of randomly selected predictions can outperform those of most accurate predictions. Then, we evaluate the WoC level by taking into account diversity and cardinality. The computational experiments have indicated that diversity is positively related to collective wisdom. Finally, we discuss some related theoretical and practical implications for further research. © 2019 - IOS Press and the authors. All rights reserved.

关键词： Forecasting

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An Orthogonal Algorithm for Key Management in Hardware Obfuscation

An Orthogonal Algorithm for Key Management in Hardware Obfus...

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IEEE Asian Hardware-Oriented Security and Trust (AsianHOST)

作者： Jiawei Wang Yuejun Zhang Pengjun Wang Zhicun Luan Xiaoyong Xue Xiaoyang Zeng Qiaoyan Yu Faculty of Electrical Engineering and Computer Science Ningbo University Zhejiang China State Key Laboratory of ASIC and System Fudan University Shanghai China College of Computer Science and Artificial Intelligence Wenzhou University Wenzhou China University of New Hampshire Durham NH USA

ISBN: (数字)9781728135441

ISBN: (纸本)9781728135458

The globalization of supply chain makes semiconductor chips susceptible to various security threats. Design obfuscation techniques have been widely investigated to thwart intellectual property (IP) piracy attacks. Key distribution among IP providers, system integration team, and end users remains as a challenging problem. This work proposes an orthogonal obfuscation method, which utilizes an orthogonal matrix to authenticate obfuscation keys, rather than directly examining each activation key. The proposed method hides the keys by using an orthogonal obfuscation algorithm to increasing the key retrieval time, such that the primary keys for IP cores will not be leaked. The simulation results show that the proposed method reduces the key retrieval time by 36.3% over the baseline. The proposed obfuscation methods have been successfully applied to ISCAS'89 benchmark circuits. Experimental results indicate that the orthogonal obfuscation only increases the area by 3.4% and consumes 4.7% more power than the baseline 1 .

关键词： IP networks Hardware Protocols Security Integrated circuits Licenses Reverse engineering

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