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arXiv 2018年

作者： Aresta, Guilherme Araújo, Teresa Kwok, Scotty Chennamsetty, Sai Saketh Safwan, Mohammed Alex, Varghese Marami, Bahram Prastawa, Marcel Chan, Monica Donovan, Michael Fernandez, Gerardo Zeineh, Jack Kohl, Matthias Walz, Christoph Ludwig, Florian Braunewell, Stefan Baust, Maximilian Vu, Quoc Dang Nhat To, Minh Nguyen Kim, Eal Kwak, Jin Tae Galal, Sameh Sanchez-Freire, Veronica Brancati, Nadia Frucci, Maria Riccio, Daniel Wang, Yaqi Sun, Lingling Ma, Kaiqiang Fang, Jiannan Kone, Ismael Boulmane, Lahsen Campilho, Aurélio Eloy, Catarina Polónia, António Aguiar, Paulo INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal Faculty of Engineering of University of Porto Porto4200-465 Portugal Seek AI Limited Hong Kong Bangalore India Gurgaon India Chennai India Center for Computational and Systems Pathology Dpt. of Pathology Icahn School of Medicine at Mount Sinai Mount Sinai Hospital New York United States Konica Minolta Laboratory Europe Munich Germany Institute of Pathology Faculty of Medicine LMU Munich Munich Germany Department of Computer Science and Engineering Sejong University Seoul05006 Korea Republic of Chicago IL United States Naples Italy University of Naples "Federico II" Naples Italy Key Laboratory of RF Circuits and Systems Ministry of Education Hangzhou Dianzi University Hangzhou310018 China Zhejiang Provincial Laboratory of Integrated Circuits Design Hangzhou Dianzi University Hangzhou310018 China p2MIA Research Group LEM2A Lab Faculté des Sciences Université Moulay Ismail Meknes Morocco qLaboratório de Anatomia Patológica Ipatimup Diagnósticos Rua Júilio Amaral de Carvalho 45 Porto4200-135 Portugal Faculdade de Medicina Universidade do Porto Alameda Prof Hernâni Monteiro Porto4200-319 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal Universidade do Porto Rua Alfredo Allen 208 Porto4200-135 Portugal

Breast cancer is the most common invasive cancer in women, affecting more than 10% of women worldwide. Microscopic analysis of a biopsy remains one of the most important methods to diagnose the type of breast cancer. This requires specialized analysis by pathologists, in a task that i) is highly time- and cost-consuming and ii) often leads to nonconsensual results. The relevance and potential of automatic classification algorithms using hematoxylin-eosin stained histopathological images has already been demonstrated, but the reported results are still sub-optimal for clinical use. With the goal of advancing the state-of-the-art in automatic classification, the Grand Challenge on BreAst Cancer Histology images (BACH) was organized in conjunction with the 15th International Conference on Image Analysis and Recognition (ICIAR 2018). BACH aimed at the classification and localization of clinically relevant histopathological classes in microscopy and whole-slide images from a large annotated dataset, specifically compiled and made publicly available for the challenge. Following a positive response from the scientific community, a total of 64 submissions, out of 677 registrations, effectively entered the competition. The submitted algorithms improved the state-of-the-art in automatic classification of breast cancer with microscopy images to an accuracy of 87%. Convolutional neuronal networks were the most successful methodology in the BACH challenge. Detailed analysis of the collective results allowed the identification of remaining challenges in the field and recommendations for future developments. The BACH dataset remains publicly available as to promote further improvements to the field of automatic classification in digital pathology. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Fuzzy logic controller design for intelligent air-conditioning system

Fuzzy logic controller design for intelligent air-conditioni...

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IEEE International Conference on Control science and Systems engineering (CCSSE)

作者： Nizam Uddin Ahamed Zahari Bin Taha Ismail Bin Mohd Khairuddin M.F. Rabbi S.A.M. Matiur Rahaman Kenneth Sundaraj Mechatronic and System Design Lab Faculty of Manufacturing Engineering Universiti Malaysia Pekan Pahang Malaysia Faculty of Manufacturing Engineering Universiti Malaysia Pekan Pahang Malaysia College of Computer Science and Information System Najran University Saudi Arabia AI-Rehab Research Group Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (纸本)9781467398732

In efficient air cooling systems may cause of wasting energy in a great amount specially in the urban area. Being the most popular cooling system, air-conditioners have been used in domestic usage as well as in industrial applications. However, the unintelligent nature of such cooling system gives rise to excess energy consumption which causes a huge problem in the current energy hungry world. In this paper, we present design of a fuzzy logic controller for the intelligent air-conditioning system. The performance of the controller is also simulated. The proposed controller has the adaptive nature to control fan and compressor speed which leads to reducing power consumption. Also, the system controls the operation mode to retain the healthy oxygen level and humid condition of the indoor environment.

关键词： Humidity Fuzzy logic Fans Energy consumption Power demand

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Sensitivity study on the stray voltage of low voltage residential networks

Sensitivity study on the stray voltage of low voltage reside...

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International Conference on Power Electronics and Motion Control (IPEMC)

作者： Chen Jiang Qingxin Shi Yu Tian Xiaoyu Li Shunfu Lin Yu Liu North China Power Engineering Co. LTD Beijing China Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA Powertech Lab. Inc. Vancouver BC Canada Southwest Electric Power Design Institute China Power Engineering Consulting Group Chengdu China Shanghai University of Electric Power Shanghai China College of Energy and Electrical Engineering Southeast University Nanjing China

ISBN: (纸本)9781509012114

Stray voltages have always been a power quality concern to utility companies and customers. The long-term exposure to sufficient stray voltage can be harmful to human being's and animals' health. The stray voltage in the low voltage network is generally related to the load unbalance, grounding condition and network structure. Through analytical study and detailed system simulations, this paper makes a sensitivity study on how serious these factors affect the stray voltage in low voltage networks. Therefore some recommendations can be formulated to prevent the excessive stray voltage. On the other hand, this paper also provides guidance on how to identify the cause of excessive stray voltage incidence if it is detected.

关键词： Conductors Grounding Zinc Impedance Sensitivity Resistance Electronic mail

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A trust evaluation fluctuation model in the e-commerce

A trust evaluation fluctuation model in the e-commerce

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第27届中国控制与决策会议

作者： Zhang Jing Yu Shengjun Fan Hongbo Rong Hui Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming University of Science and Technology Faculty of Art and Design Kunming Metallurgy College

ISBN: (纸本)9781479970186

E-commerce is becoming the main shopping *** trust decision-making is the most important factor which decides whether the transaction is successful or *** to offer people an accurate and objective trust is a basic issue that scholars must face and *** can measure the stability of a set of data and help us avoid risk to some *** order to prevent fraud and deception,this paper proposes a trust evaluation fluctuation model based on historical rating data.A new reward and punishment mechanism is added into the *** results of simulation experiments prove the practicality and validity of the model.

关键词： decision-making trust volatility fraud and deception

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A trust evaluation fluctuation model in the e-commerce 27

A trust evaluation fluctuation model in the e-commerce

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27th Chinese Control and Decision Conference, CCDC 2015

作者： Jing, Zhang Yu, Shengjun Fan, Hongbo Hui, Rong Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Faculty of Art and Design Kunming Metallurgy College Kunming Yunnan China

ISBN: (纸本)9781479970179

E-commerce is becoming the main shopping way. The trust decision-making is the most important factor which decides whether the transaction is successful or not. How to offer people an accurate and objective trust is a basic issue that scholars must face and solve. Volatility can measure the stability of a set of data and help us avoid risk to some extent. In order to prevent fraud and deception, this paper proposes a trust evaluation fluctuation model based on historical rating data. A new reward and punishment mechanism is added into the model. The results of simulation experiments prove the practicality and validity of the model. © 2015 IEEE.

关键词： decision-making fraud and deception trust volatility

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Network Energy Consumption Analysis and Dormancy Mechanism Based on Ant Colony Algorithm in Cloud Computing Environment for IOT Service and Real-time Embedded Industrial Control System

Network Energy Consumption Analysis and Dormancy Mechanism B...

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第27届中国控制与决策会议

作者： Shi Shaoling Zhang Jing Chen Moliang Rong Hui Cui Yi Fu Xiaodong Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming University of Science and Technology Faculty of Art and Design Kunming Metallurgy College Yunnan Academy of Scientific & Technical Information

ISBN: (纸本)9781479970162

At present,cloud computing technology is widely used in IOT(Internet of Things) service and real-time embedded industrial control system energy consumption,problem in the cloud computing has always been the hot topic of industry and academic *** paper analyzes the energy consumption of each equipment under the dormancy mechanism in the cloud computing ***,this paper introduces the ant colony algorithm into a basic network energy consumption model,thereby building a new model for the energy consumption *** simulation experiments were implemented on a cloud computing simulation platform *** comparison with two algorithms- Min LP and Dijkstra,the model presented in this paper was proved to be effective and more energy-efficient.

关键词： real-time embedded industrial control system

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Network energy consumption analysis and dormancy mechanism based on ant colony algorithm in cloud computing environment for IOT service and real-time embedded industrial control system 27

Network energy consumption analysis and dormancy mechanism b...

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27th Chinese Control and Decision Conference, CCDC 2015

作者： Shi, Shaoling Jing, Zhang Chen, Moliang Hui, Rong Yi, Cui Fu, Xiaodong Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming Yunnan China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming Yunnan China Faculty of Art and Design Kunming Metallurgy College Kunming Yunnan China Yunnan Academy of Scientific and Technical Information Kunming Yunnan China

ISBN: (纸本)9781479970179

At present, cloud computing technology is widely used in IOT(Internet of Things) service and real-time embedded industrial control system energy consumption, problem in the cloud computing has always been the hot topic of industry and academic research. This paper analyzes the energy consumption of each equipment under the dormancy mechanism in the cloud computing environment. Meanwhile, this paper introduces the ant colony algorithm into a basic network energy consumption model, thereby building a new model for the energy consumption optimization. The simulation experiments were implemented on a cloud computing simulation platform CLOUDSIM. In comparison with two algorithms - Min LP and Dijkstra, the model presented in this paper was proved to be effective and more energy-efficient. © 2015 IEEE.

关键词： ant colony algorithm cloud computing dormancy mechanism energy consumption analysis IOT service real-time embedded industrial control system

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Back Cover: H2S Sensors: Fumarate-Based fcu-MOF Thin Film Grown on a Capacitive Interdigitated Electrode (Angew. Chem. Int. Ed. 51/2016)

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Angewandte Chemie International Edition 2016年第51期55卷

作者： Dr. Omar Yassine Dr. Osama Shekhah Ayalew H. Assen Dr. Youssef Belmabkhout Prof. Khaled N. Salama Prof. Mohamed Eddaoudi Sensors Lab Electrical Engineering Program Division of Computer Electrical and Mathematical Sciences and Engineering King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia Functional Materials Design Discovery and Development research group (FMD3) Advanced Membranes & Porous Materials Center Division of Physical Sciences and Engineering King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia

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