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Proceedings of the 2016 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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UTILIZING RESERVE ASSETS - MUTUAL SUPPORT AT SUPSHIP BATH

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NAVAL ENGINEERS JOURNAL 1993年第6期105卷 39-42页

作者： GOLDA, EM PORPORA, GA Cdr. Eugene Michael Golda:is a Naval Reserve engineering duty officer and is commanding officer of NR NavSea PMS Det 302. He has developed and directed mutual support programs assisting the Supervisor of Shipbuilding Brooklyn and has participated in the training and mutual support programs at the Supervisor of Shipbuilding Bath. He received a Ph.D. and M.S. in materials science and engineering from Stevens Institute of Technology Hoboken N.J. A 1977 graduate of the United States Naval Academy Cdr. Golda has been a member of ASNE since 1974. Cdr. Golda is a materials engineer at the Annapolis Detachment Carderock Division Naval Surface Warfare Center working on naval applications of superconducting technology. LCdr. Gregory A. Porpora:is an IBM market support representative who provides technical consulting support in application development with computer aided software engineering (CASE) tools. Prior to joining IBM he was a senior design engineer for a defense contractor involved in design and development of radar and ASW systems including the AN/BSY-1 combat system trainer. LCdr. Porpora is a member of IEEE the Naval Institute and the Naval Reserve Association. He holds a BSEE and MSEE from the Polytechnic Institute of Technology New York. LCdr. Porpora is currently assigned to NR SupShip Det 502 which provides extensive mutual support for the Supervisor of Shipbuilding Bath and the resident office in Brooklyn New York.

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A step-down frequency-modulated zero-current switching quasi-resonant converter-fed DC drive

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 1996年第1期6卷 61-66页

作者： Reddy, SR Lakshmikanth, A Raj, VB Chellamuthu, C Salhi Rama Reddy (1963) received AMIE in Electrical Engineering from the institution of Engineers (India) in 1984. He received M.E. degree from Anna University Madrid India in 1986. He worked at Tab Consulting Engineers Bangalodndia from 1987 to 1989 when he was appointed as Assistant Engineer. Subsequently he worked as a lecturer at Madras University from 1990 to 1992. Presently he is working as a lecturer in the Power Systems Division College of Engineering Madras. His current research activities are. in the area of power electronics and microprocessor control of electrical drives. (College of Engineering Madras - 600025 India T +9144/2351723-3352 Fax + 009144/2350397) Ananta Lakshmikanth (1970) received the B.E. in Electrical Engineering from the College of Engineering Anna University Maddndia. in 199 I. Presently he is a post graduate scholar at Power Electronics division Anna University. His fields of interest are electrical drives design and sirnulation of power electronic circuits. (Power Electronics Division Anna University Madras 600 025 India T +9144/235 17233349 Fax +9144/2350397) Vasu Babu Raj (1969) received the B.E. in Electrical Engineering from the Regional Engineering College Trichy/ India in 1991. He received the M.E. degree from Anna University Madras/ India in 1993. Since January 1994 he is working as a Software Engineer at Tata Consultancy Services (TCS) New Delhflndia. (TCS Gulab Bhawan 6 Bahadur Shah Zabar Marg New Delhi-110002 T+91 11/3318402) Chinasamy Chellamuthu (1942) received B.E. degree in Electrical Engineering and M.Sc (Engng.) in Power Systems from Madras University and Ph.D. degree in Power Electronics from Indian Institute of Technology Madradndia in 1965. 1967 and 1982 respectively. He worked as a faculty member of Govt. College of Technology Coimbatore. from 1967 to 1977. Presently he is working as Professor of Power Electronics at Anna University Madras. His fields of interest include simulation of power-semiconductor controlled drives an

The simulation and implementation of a step-down frequency-modulated zero-current switching quasi-resonant converter (FM-ZCS-QRC) fed DC drive are presented. A parallel resonant QRC is used for the speed control of a DC motor. The FM-ZCS-QRC-fed DC drive is modelled and simulated. A microprocessor-based prototype system is also implemented for controlling the drive speed and the results predicted by simulation are verified experimentally. It is found that the FM-ZCS-QRC-fed DC drive has several advantages over those fed from phase-controlled converters, DC choppers and PWM converters.

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Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment

arXiv

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arXiv 2024年

作者： Wu, Jiaqi Zhang, Shihao Chen, Simin Wang, Lixu Wang, Zehua Chen, Wei He, Fangyuan Tian, Zijian Yu, F. Richard Leung, Victor C.M. Beijing100083 China Department of Electrical and Computer Engineering University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada University of Texas at dallas 800 W Campbell Rd RichardsonTX75080 United States Northwestern University 633 Clark St EvanstonIL60208 United States School of Computer Science and Technology China University of Mining and Technology Jiangsu province Xuzhou221116 China Department of Electrical and Computer Engineering The University of British Columbia Vancouver 2332 Main Mall VancouverBCV6T 1Z4 Canada Department of Systems and Computer Engineering Carleton University OttawaONK1S 5B6 Canada Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China College of Computer Science and Software Engineering Shenzhen University Shenzhen528060 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada College of Applied Science and Technology Beijing Union University Beijing100012 China

Recently, edge computing has emerged as a prevailing paradigm in applying deep learning-based object detection models, offering a promising solution for time-sensitive tasks. However, existing edge object detection faces several challenges: 1) These methods struggle to balance detection precision and model lightweightness. 2) Existing generalized edge-deployment designs offer limited adaptability for object detection. 3) Current works lack real-world evaluation and validation. To address these challenges, we propose the Edge Detection Toolbox (ED-TOOLBOX), which leverages generalizable plug-and-play components to enable edge-site adaptation of object detection models. Specifically, we propose a lightweight Reparameterized Dynamic Convolutional Network (Rep-DConvNet) that employs a weighted multi-shape convolutional branch structure to enhance detection performance. Furthermore, ED-TOOLBOX includes a Sparse Cross-Attention (SC-A) network that adopts a localized-mapping-assisted self-attention mechanism to facilitate a well-crafted Joint Module in adaptively transferring features for further performance improvement. In real-world implementation and evaluation, we incorporate an Efficient Head into the popular You-Only-Look-Once (YOLO) approach to achieve faster edge model optimization. Moreover, we identify that helmet detection—one of the most representative edge object detection tasks—overlooks band fastening, which introduces potential safety hazards. To address this, we build a Helmet Band Detection Dataset (HBDD) and apply an edge object detection model optimized by the ED-TOOLBOX to tackle this real-world task. Extensive experiments validate the effectiveness of components in ED-TOOLBOX. In visual surveillance simulations, ED-TOOLBOX-assisted edge detection models outperform six state-of-the-art methods, enabling real-time and accurate detection. These results demonstrate that our approach offers a superior solution for edge object detection. Copyright © 2024, T

关键词： Deep learning

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A regularized CNN approach for detecting cervical cancer

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AIP Conference Proceedings 2024年第1期3220卷

作者： Jesse Jeremiah Tanimu Mohamed Hamada Mohammed Hassan Tsentob Joy Samson Jane Simon Parah Department of computer Science Bayero Unoiversity Kano Kano Nigeria Division of information systems University of Aizu Aizu Japan Department of Software Engineering Bayero University Kano Kano Nigeria Department of computer Science Air Force Institute of Technology Kaduna Kaduna Nigeria Department of Mathematical and Physical Science Glorious Vision University Ogwa Benin Nigeria

This study delved into leveraging deep learning techniques to classify different types of cervical cancer images, recognizing the disease’s prevalence and criticality. We employed a dataset comprising cervical images and investigated the utilization of the VGG16 model as a foundational architecture. To enhance performance, we incorporated various improvements, such as L2 regularization and data augmentation. The outcomes underscored the efficacy of these enhancements, with the refined model achieving a remarkable accuracy of 94%, surpassing the VGG16 model’s baseline accuracy of 89%. These findings demonstrate the potential of deep learning to improve the classification of cervical cancer.

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The neuroprotective action of novel multitarget drug cemtirestat, a link with neuroinflammation and oxidative stress in peripheral neuropathy

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Neuroscience Applied 2023年 2卷

作者： M. Lepáček P. Boďo A. Ballóová M. Šoltésová Prnová Centre of experimental medicine- Slovak Academy of Sciences Institute of Experimental Pharmacology and Toxicology Bratislava Slovak Republic Faculty of Natural Sciences- Comenius University Department of Biochemistry Bratislava Slovak Republic Jessenius Faculty of Medicine- Slovak Academy of Sciences Department of Pharmacology Bratislava Slovak Republic Faculty of Informatics and Information Technologies- Slovak University of Technology Institute of Informatics- Information Systems and Software Engineering Bratislava Slovak Republic

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Sorbitol accumulation in ZDF rat’s brain as new link between diabetes and Alzheimer’s disease?

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Neuroscience Applied 2023年 2卷

作者： P. Bodo M. Lepacek A. Balloova M. Soltesova Prnova Centre of Experimental Medicine- Slovak Academy of Sciences Institute of Experimental Pharmacology and Toxicology Bratislava Slovak Republic Faculty of Natural Sciences- Comenius University Department of Biochemistry Bratislava Slovak Republic Jessenius Faculty of Medicine in Martin- Comenius University Department of Pharmacology Bratislava Slovak Republic Faculty of Informatics and Information Technologies- Slovak Technical University Institute of Informatics- Information Systems and Software Engineering Bratislava Slovak Republic

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New compound cemtirestat as a potential drug with multitarget properties: from diabetes to major depressive disorder?

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Neuroscience Applied 2023年 2卷

作者： A. Ballóová M. Lepáček P. Boďo M. Mach M. Šoltésová Prnová Centre of Experimental Medicine- Slovak Academy of Sciences Institute of Experimental Pharmacology and Toxicology Bratislava Slovak Republic Jessenius Faculty of Medicine in Martin- Comenius University Department of Pharmacology Bratislava Slovak Republic Faculty of Natural Sciences- Comenius University Department of Biochemistry Bratislava Slovak Republic Faculty of Informatics and Information Technologies- Slovak University of Technology Institute of informatics- Information Systems and Software Engineering Bratislava Slovak Republic

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Functional Synthetic Biology

arXiv

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arXiv 2022年

作者： Aldulijan, Ibrahim Beal, Jacob Billerbeck, Sonja Bouffard, Jeff Chambonnier, Gaël Delkis, Nikolaos Guerreiro, Isaac Holub, Martin Ross, Paul Selvarajah, Vinoo Sprent, Noah Vidal, Gonzalo Vignoni, Alejandro Systems Engineering Stevens Institute of Technology 1 Castle Point Terrace HobokenNJ07030 United States Intelligent Software & Systems Raytheon BBN Technologies 10 Moulton Street CambridgeMA02138 United States Molecular Microbiology Groningen Biomolecular Sciences and Biotechnology Institute University of Groningen Nijenborgh 7 Groningen9747 AG Netherlands Centre for Applied Synthetic Biology Department of Biology Concordia University 7141 Sherbrooke Street West MontréalQCH4B 1R6 Canada Department of Biological Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Plant and Environmental Biotechnology Laboratory Department of Biochemistry and Biotechnology University of Thessaly Viopolis Mezourlo Larissa41500 Greece iGEM Foundation 45 Prospect Street CambridgeMA02139 United States Delft University of Technology Van der Maasweg 9 2629 HZ Netherlands BioStrat Marketing 9965 Harbour Lake Circle Boynton BeachFL33437 United States Department of Chemical Engineering Imperial College London South Kensington Campus Exhibition Road SW7 2AZ United Kingdom Research Group School of Computing Newcastle University Devonshire Building Devonshire Terrace Newcastle Upon TyneNE1 7RU United Kingdom Synthetic Biology and Biosystems Control Lab Instituto de Automatica e Informatica Industrial Universitat Politecnica de Valencia Camino de Vera s/n Valencia46022 Spain

Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms. However, current paradigms in the field entangle sequence and functionality in a manner that makes abstraction difficult, reduces engineering flexibility, and impairs predictability and design reuse. Functional Synthetic Biology aims to overcome these impediments by focusing the design of biological systems on function, rather than on sequence. This reorientation will decouple the engineering of biological devices from the specifics of how those devices are put to use, requiring both conceptual and organizational change, as well as supporting software tooling. Realizing this vision of Functional Synthetic Biology will allow more flexibility in how devices are used, more opportunity for reuse of devices and data, improvements in predictability, and reductions in technical risk and cost. © 2022, CC BY.

关键词： Biological systems

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Preface

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2678卷 VI页

作者： van der Aalst, Wil ter Hofstede, Arthur Weske, Mathias Eindhoven University of Technology Department of Information and Technology P.O. Box 513 Eindhoven Netherlands Queensland University of Technology Centre for Information Technology Innovation GPO Box 2434 BrisbaneQLD Australia Potsdam University Hasso Plattner Institute for Software Systems Engineering Prof.-Dr.-Helmert-Str. 2-3 Potsdam Germany

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