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Methodologies and Intelligent Systems for Technology Enhanced Learning, 9th International Conference, 2019 2020年 1007卷 v-vi页

作者： Gennari, Rosella Vittorini, Pierpaolo De la Prieta, Fernando Di Mascio, Tania Temperini, Marco Silveira, Ricardo Azambuja Carranza, Demetrio Arturo Ovalle Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Department of Computer Science and Automation Control University of Salamanca SalamancaSalamanca Spain Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Dipartimento di Ingegneria Informatica Automatica e Gestionale Sapienza Università di Roma Rome Italy Department of Computer Science and Statistics Federal University of Santa Catarina Florianópolis Brazil Universidad Nacional de Colombia Medellin Colombia

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Ensuring the quality of fuel equipment joints in series production conditions by graded kitting

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AIP Conference Proceedings 2023年第1期2889卷

作者： Oleksandr Kupriyanov Hanna Hrinchenko Roman Strelchuk Mykhailo Kupriianov Ukrainian Engineering Pedagogics Academy Innovative Technologies Faculty Department of Information Computer Technologies and Mathematics 16 Universitetska st. Kharkiv 61003 Ukraine Ukrainian Engineering Pedagogics Academy Power Engineering and Automation Faculty Department of Automatization Metrology and Energy-Saving Technologies 16 Universitetska st. Kharkiv 61003 Ukraine National Technical University «Kharkiv Polytechnic Institute» Department of Integrated Technologies of Mechanical Engineering named after M.F. Semko 2 Kirpicheva st. Kharkiv 61002 Ukraine Kharkiv National University of Radio Electronics Faculty of Computer Science 14 Nauky Ave. 61166 Kharkiv Ukraine

A graded kitting method is proposed, which provides the required accuracy for a complete assemblage of a part batch. The new kitting method was tested on the example of fuel equipment produced by the Kharkiv Tractor Plant. The connection of the body and slide valve was studied under workshop conditions. Kitting accuracy and unfinished production were compared at full interchangeability, selective kitting, and graded kitting. The method proposes measuring the actual parameters of the parts and using them to improve and optimize the assembly process. The use of data on the part dimensions makes it possible to increase the efficiency of the assembly process at the expense of information support. These data must be linked to specific parts, which can be done by address buffer stations or special marking based on optical or magnetic tags. The graded kitting with full assemblage allows achieving the precision, which significantly exceeds the technological requirements. Therefore, by reducing the manufacturing requirements from the actual 5th-6th grade of accuracy for the body-slide valve connection to the 9th grade of accuracy, the total accuracy that is sufficient to ensure a structurally required fitting is achieved. The use of graded kitting makes it possible to achieve the required kitting accuracy for batches of 5 to 15 parts with easily achievable manufacturing precision requirements.

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Optical Solitons with Cubic–Quartic Complex Ginzburg–Landau Equation Using a Novel Approach

SSRN

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SSRN 2022年

作者： Arnous, Ahmed H. Nofal, Taher A. Biswas, Anjan González-Gaxiola, O. Moraru, Luminita Moldovanu, Simona Department of Mathematics and Physics Grambling State University GramblingLA71245 United States Research Group Department of Mathematics King Abdulaziz University Jeddah21589 Saudi Arabia Department of Mathematics and Applied Mathematics Sefako Makgatho Health Sciences University Medunsa Pretoria 0204 South Africa Department of Applied Sciences Cross–Border Faculty of Humanities Economics and Engineering Dunarea de Jos University of Galati 111 Domneasca Street Galati800201 Romania Department of Applied Mathematics National Research Nuclear University 31 Kashirskoe Hwy Moscow115409 Russia Applied Mathematics and Systems Department Universidad Autonoma Metropolitana–Cuajimalpa Vasco de Quiroga 4871 Mexico City05348 Mexico Faculty of Sciences and Environment Department of Chemistry Physics and Environment Dunarea de Jos University of Galati 47 Domneasca Street 800008 Romania Department of Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics Dunarea de Jos University of Galati 47 Domneasca Street Galati800008 Romania Taif University Saudi Arabia

The present work retrieves cubic–quartic optical soliton solutions to the complex Ginzburg–Landau equation that is considered with five forms of nonlinear refractive index. The proposed algorithm reveals a full spectrum of optical solitons as well as hybrid type solitons whose existence are guaranteed with the listed parameter constraints. © 2022, The Authors. All rights reserved.

关键词： Solitons

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From 2015 to 2023: How Machine Learning Aids Natural Product Analysis

arXiv

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arXiv 2024年

作者： Shi, Suwen Huang, Ziwei Gu, Xingxin Lin, Xu Zhong, Chaoying Hang, Junjie Lin, Jianli Zhong, Claire Chenwen Zhang, Lin Li, Yu Huang, Junjie Department of Chemistry Boston University BostonMA02215 United States Department of Physics Boston University BostonMA02215 United States College of Professional Studies Northeastern University BostonMA02215 United States Department of Thoracic Surgery The First Affiliated Hospital School of Medicine Zhejiang University Zhejiang Hangzhou China Department of Electrical Engineering and Automation Guangdong Ocean University Guangdong China Cancer Hospital & Shenzhen Hospital Chinese Academy of Medical Sciences Peking Union Medical College Guangdong China Peking-Tsinghua Center for Life Sciences Academy for Advanced Interdisciplinary Studies Peking University Beijing China The Jockey Club School of Public Health and Primary Care Faculty of Medicine The Chinese University of Hong Kong Hong Kong Suzhou Industrial Park Monash Research Institute of Science and Technology Suzhou China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong

In recent years, conventional chemistry techniques have faced significant challenges due to their inherent limitations, struggling to cope with the increasing complexity and volume of data generated in contemporary research endeavors. Computational methodologies represent robust tools in the field of chemistry, offering the capacity to harness potent machine-learning models to yield insightful analytical outcomes. This review delves into the spectrum of computational strategies available for natural product analysis and constructs a research framework for investigating both qualitative and quantitative chemistry problems. Our objective is to present a novel perspective on the symbiosis of machine learning and chemistry, with the potential to catalyze a transformation in the field of natural product analysis. © 2024, CC BY.

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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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Corrigendum to “Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller” [Energy Rep. 10 (2023) 3272–3288]

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Energy Reports 2023年 10卷 3847-3847页

作者： Sk.A. Shezan Md. Fatin Ishraque GM Shafiullah Innobent Kamwa Liton Chandra Paul SM Muyeen Ramakrishna NSS Mohammed Zeehan Saleheen Polamarasetty P. Kumar School of Industrial Automation and Electrical Engineering Engineering Institute of Technology Melbourne VIC Australia School of Engineering and Energy Murdoch University Australia Department of Electrical Electronic and Communication Engineering Pabna University of Science and Technology Pabna Bangladesh Department of Electrical Engineering and Computer Engineering Laval University Quebec QC G1V 0A6 Canada Department of Electrical Engineering Qatar University Doha 2713 Qatar Department of Electrical and Electronics GMR Institute of Technology Rajam Andhra Pradesh 532127 India Department of Data Science & AI Faculty of IT Monash University Australia

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2019年 804卷 v-vi页

作者： di Mascio, Tania Vittorini, Pierpaolo Gennari, Rosella de la Prieta, Fernando Rodríguez, Sara Silveira, Ricardo Azambuja Temperini, Marco Popescu, Elvira Lancia, Loreto Department of Information Engineering Computer Science and Mathematics University of L’Aquila L’Aquila Italy Department of Life Health and Environmental Sciences University of L’Aquila L’Aquila Italy Computer Science Faculty Free University of Bozen-Bolzano Bolzano Italy BISITE Digital Innovation Hub University of Salamanca Salamanca Spain Department of Computer Science and Statistics Federal University of Santa Catarina Florianópolis Brazil Dipartimento di Ingegneria Informatica Sapienza Università di Roma Rome Italy Faculty of Automation Computers and Electronics Computers Information Technology Department University of Craiova Craiova Romania Department of Life Health and Environmental Sciences University of L’Aquila Coppito Italy

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Self-Awareness for Autonomous Systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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The medical segmentation decathlon

arXiv

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arXiv 2021年

作者： Antonelli, Michela Reinke, Annika Bakas, Spyridon Farahani, Keyvan Kopp-Schneider, Annette Landman, Bennett A. Litjens, Geert Menze, Bjoern Ronneberger, Olaf Summers, Ronald M. van Ginneken, Bram Bilello, Michel Bilic, Patrick Christ, Patrick F. Do, Richard K.G. Gollub, Marc J. Heckers, Stephan H. Huisman, Henkjan Jarnagin, William R. McHugo, Maureen K. Napel, Sandy Golia Pernicka, Jennifer S. Rhode, Kawal Tobon-Gomez, Catalina Vorontsov, Eugene Hulsmon, Hankan Meakin, James A. Ourselin, Sebastien Wiesenfarth, Manuel Arbeláez, Pablo Bae, Byeonguk Chen, Sihong Daza, Laura Feng, Jianjiang He, Baochun Isensee, Fabian Ji, Yuanfeng Jia, Fucang Kim, Namkug Kim, Ildoo Merhof, Dorit Pai, Akshay Park, Beomhee Perslev, Mathias Rezaiifar, Ramin Rippel, Oliver Sarasua, Ignacio Shen, Wei Son, Jaemin Wachinger, Christian Wang, Liansheng Wang, Yan Xia, Yingda Xu, Daguang Xu, Zhanwei Zheng, Yefeng Simpson, Amber L. Maier-Hein, Lena Cardoso, M. Jorge School of Biomedical Engineering & Imaging Sciences King’s College London London United Kingdom Heidelberg Germany Heidelberg Germany Faculty of Mathematics and Computer Science University of Heidelberg Heidelberg Germany University of Pennsylvania PhiladelphiaPA United States BethesdaMD United States Heidelberg Germany Electrical Engineering and Computer Science Vanderbilt University NashvilleTN United States Radboud University Medical Center Radboud Institute for Health Sciences Nijmegen Netherlands Quantitative Biomedicine University of Zurich Zurich Switzerland DeepMind London United Kingdom School of Computing Department of Biomedical and Molecular Sciences Queen’s University KingstonON Canada Department of Surgery Memorial Sloan Kettering Cancer Center New YorkNY United States BethesdaMD United States Department of Informatics Technische Universität München Germany Department of Radiology Memorial Sloan Kettering Cancer Center New YorkNY United States Department of Psychiatry & Behavioral Sciences Vanderbilt University Medical Center NashvilleTN United States Department of Radiology Stanford University StanfordCA United States Department of Computer Science and Software Engineering École Polytechnique de Montréal Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Medical Faculty University of Heidelberg Heidelberg Germany VUNO Inc. Seoul Korea Republic of Universidad de los Andes Colombia Department of Automation Tsinghua University Beijing China Heidelberg Germany Department of Computer Science Xiamen University Xiamen361005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Kakao Brain Korea Republic of Institute of Imaging & Computer Vision RWTH Aachen University Aachen Germany Cere

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD)—a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks;(2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability;(3) the training of accurate AI segmentation models is now commoditized to non AI *** Codes 68T07. © 2021, CC BY-NC-SA.

关键词： Image segmentation

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An invisible DWT watermarking algorithm using noise removal with application to dermoscopic images

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Journal of Physics: Conference Series 2021年第1期1730卷

作者： S Moldovanu F A (Damian) Michis L Moraru Dunarea de Jos University of Galati Department of Computer Science and Information Technology Faculty of Automation Computers Sciences Electronics and Electrical Engineering 2 Stiintei Street RO-800210 Galati Romania Dunarea de Jos University of Galati Modelling & Simulation Laboratory Galati Romania Dunarea de Jos University of Galati Faculty of Science and Environment 111 Domneasca Street RO-800201 Galati Romania Department of Chemistry Physics and Environment Faculty of Sciences and Environment Dunarea de Jos University of Galati 47 Domneasca Street 800008 Galati Romania

A new approach for the digital watermarking process is proposed to be part of the pre-processing stage of a computer-aided diagnosis system. We propose to embed a denoised image acting as the watermark image in the original host image with the final goal of improving the quality of demoscopic images for further image processing operation related to CAD. The proposed algorithm uses Discrete Wavelet Transform (DWT) corroborated with some basic properties of Human Visual System such as Contrast Sensitive Function (CSF) and Noise Visibility Function (NVF) with the goal of correlating the texture properties and noise. This approach hides the watermark (i.e. denoised version of the host image) in high-pass subbands that are focused on image features. The main concern is to evaluate the distortion produced to the host image by watermarking and an objective quality measure function, i.e. Weighted Peak Signal-to-Noise Ratio (WPSNR), is used to evaluate the existing differences between the original and watermarked images. The proposed approach is tested using the available skin lesion images from the digital image archive of the Department of Dermatology of the University Medical Center Groningen. The experiment results show the improved performance of the proposed scheme against a 3 × 3 median filtering attack in comparison with the a 5 × 5 median filtering attack.

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