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Pipelined Training and Transmission for Federated Learning 29

Pipelined Training and Transmission for Federated Learning

引用

29th IEEE International conference on Parallel and Distributed Systems, ICPADS 2023

作者： Shen, Yihui Zhang, Hong Jia, Juncheng Deng, Tao Wang, Zhenhua Teng, Zhiwei Dong, Mianxiong Soochow University School of Computer Science and Technology Suzhou215006 China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing China China Merchants New Intelligence Technology Co. Ltd. Beijing China Muroran Institute of Technology Muroran050-8585 Japan

ISBN: (纸本)9798350330717

Federated learning is a distributed machine learning framework that enables distributed edge devices to jointly train machine learning models without exchanging private data. Because federated learning can leverage edge devices' data and computing resources, the research on federated learning has set off an upsurge. However, one of major challenges faced by federated learning is the limited computation and communication resources of edge devices, which leads to low efficiency of federated learning. In this paper, we propose a federated learning framework FedPipeline, which focuses on the local training and uploading process to improve the convergence efficiency. Different from the existing federated learning algorithms with disjoint sequential steps of training and uploading for devices, FedPipeline exploits the parallelism of training and uploading that devices upload part of the model updates in advance while they are conducting local training simultaneously. In this way, the computation and communication resources of devices can be better utilized. We further design strategies for the scheduling of early uploading and the selection of uploaded updates to maximize the benefit of FedPipeline. Experimental results show that FedPipeline can effectively accelerate the convergence speed of federated learning and preserve the accuracy of the final model. © 2023 IEEE.

关键词： Federated Learning Machine Learning Pipeline Training Transmission

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Process Route Optimization for Generalized Energy Efficiency and Production Time in Machining System

Process Route Optimization for Generalized Energy Efficiency...

引用

2019 IEEE International conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Tang, Ying Yang, Qingshan Li, Congbo Xiao, Qinge Chen, Xingzheng Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 USA United States Institute of Smart Education Qingdao Academy of Intelligent Industries Qingdao266109 China School of Information Science and Technology Dalian Maritime University Dalian116026 China State Key Laboratory of Mechanical Transmission Chongqing University Chongqing400044 China CET-college of Engineering and Technology Southwest University Chongqing400715 China

ISBN: (纸本)9781728128535

Total consumption of direct electric energy and average embodied energy of cutters and cutting fluid as well as other auxiliary resource consumed in machining a part are defined as generalized energy consumption. In this paper, a process route optimization model oriented for improvement of generalized energy efficiency and production time is proposed. The selection of machining sequence, machine tools, cutting tools, tool access direction and processing parameters in process route is optimized through a SA-QPSO hybrid algorithm. Results indicate that the balance between generalized energy efficiency and machining time is achieved and detailed analysis of process route influence on these two objectives is given afterwards. © 2019 IEEE.

关键词： Energy efficiency

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One-Shot Verification for Paper Certificates in Public Service System

One-Shot Verification for Paper Certificates in Public Servi...

引用

2024 International conference on Information technology Systems and innovation, ICITSI 2024

作者： Aditama, Raditya Maulana, Maulvi Ziadinda Harisman, M. Rifki Virziadeili Hariyanto, Agus Susanto, Teguh T. D Universitas Indonesia Faculty of Computer Science Depok Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Universitas Kristen Teknologi Solo Department of Informatics Engineering Surakarta City Indonesia Universitas Negeri Jakarta Department of Educational Management Jakarta Indonesia

ISBN: (纸本)9798331511470

Even if an explosive number of proposals and prototype systems of blockchain based certificates and verification have been suggested and implemented since 2015, still in the public service areas paper certificates are prevalent. Because of advancement of color duplication and editing tools obtainable at almost no price in the internet, paper certificates are easily forged and modified. For the reason, the verification technology of the paper certificates needs need regressive research and can provide abundant research opportunities. In this research, various research suggestions and technical implementation are reviewed and a new system, called 'one-shot' verification is briefly described. The one-shot verification captures the image and QR code of the printed certificates with mobile devices before sending them to block-chained server. The block-chained server decides whether the printed certificates are tampered or not, with the OCR content by comparing hash value with hash value of the original content. The image OCR of the paper was trained with more than 1,700 images using YOLOv8. In the testing with preprocessing, the technology showed 96% accuracy. © 2024 IEEE.

关键词： Blockchain

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A novel velocity forecast method for improving predictive energy management of plug-in hybrid electric vehicles 14

A novel velocity forecast method for improving predictive en...

引用

14th IEEE Vehicle Power and Propulsion conference, VPPC 2017

作者： Guo, Ningyuan Chen, Zheng Wu, Yitao Shen, Jiangwei Xiao, Renxin Faculty of Transportation Engineering Kunming University of Science and Technology Kunming Yunnan650500 China

ISBN: (纸本)9781538613177

In this paper, a novel velocity predicted method based on Wavelet Transform (WT) and Radial Basis Function Neural Network (RBF-NN) is introduced to achieve the predictive energy management for plug- in hybrid electric vehicles (PHEVs). Three cases including RBF-NN, 1 RBF-NN with WT and 2 RBF-NN with WT, are taken into account for comparison. The corresponding model predictive contorl (MPC) algorithm is employed to testify the improvement of fuel economy based on the predicted velocity profile. Simulation results show that the combined algorithm of 1 RBF-NN and WT can attain satisfactory performance, which increases the prediction accuracy by 7.31% compared with that by other two cases. In addition, the computational time of the proposed predictive method is 2.8649 ms, justifying that it can be efficiently employed in the practical application. © 2017 IEEE.

关键词： Model predictive control

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HSFL: Efficient and Privacy-Preserving Offloading for Split and Federated Learning in IoT Services

HSFL: Efficient and Privacy-Preserving Offloading for Split ...

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2023 IEEE International conference on Web Services, ICWS 2023

作者： Deng, Ruijun Du, Xin Lu, Zhihui Duan, Qiang Huang, Shih-Chia Wu, Jie Fudan University School of Computer Science Shanghai China Ministry of Education Engineering Research Center of Cyber Security Auditing and Monitoring Shanghai China Shanghai Blockchain Engineering Research Center Shanghai China Pennsylvania State University Information Sciences and Technology Department AbingtonPA United States National Taipei University of Technology Department of Electronic Engineering Taiwan

ISBN: (纸本)9798350304855

Distributed machine learning methods like Federated Learning (FL) and Split Learning (SL) meet the growing demands of processing large-scale datasets under privacy restrictions. Recently, FL and SL are combined in hybrid SLFL (SFL) frameworks to exploit both methods' advantages to facilitate ubiquitous intelligence in the Internet of Things (IoT), for example, smart finance. Despite its significant impact on the performance and costs of SFL, model decomposition that splits an ML model into the client-server pair has not been sufficiently studied, especially for SFL in a large-scale dynamic IoT environment. In this paper, we propose a new SFL framework HSFL with a lightweight model decomposition method to offload a part of model training to the edge server. Specifically, we develop a method for estimating the training latency of HSFL and designed a metric for measuring privacy leakage in HSFL, based on which we formulate model decomposition in HSFL as an optimization problem with privacy protection as a constraint. Then, we transform the formulated problem into a contextual bandit problem and design an efficient algorithm to solve it. We have conducted thorough evaluations of the proposed HSFL framework through extensive experiments on a prototype testbed and a simulation platform. The experimental results validate the superiority of HSFL over the state-of-the-art benchmarks in terms of training latency, efficiency, scalability, and privacy protection. © 2023 IEEE.

关键词： Internet of things

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Generating summarized preview for education resource based on exploring and comparing GUIs 28

Generating summarized preview for education resource based o...

引用

28th International conference on Software Engineering and Knowledge Engineering, SEKE 2016

作者： Ma, Chao Chen, Xiangping Rao, Yongsheng Lin, Mouguang School of Data and Computer Science Sun Yat-sen University Guangzhou China Research Institute Sun Yat-sen University in Shenzhen Shenzhen China Institute of Advanced Technology Sun Yat-sen University Guangzhou China School of Computer Science and Educational Software Guangzhou University Guangzhou China Institute of Advanced Technology National Engineering Research Center of Digital Life Sun Yat-sen University Guangzhou China

ISBN: (纸本)189170639X

Compared to traditional education resource, Interactive education Resource (IER) includes dynamic content to interact with users in order to enhance comprehension. The contents of IERs are relatively complex because of its dynamic feature. Exploring IERs and understanding its content during resource search become time-consuming. In this paper, we propose a preview generation approach based on automated software testing and image processing. Our approach first analyzes IERs to collect interactive elements and the event list. Based on the interaction related information, our approach simulates user actions and record snapshots step by step. Our approach compares snapshots to generate an image including the basic content, interaction region and dynamic contents. The image is used as the overall preview and the animation of snapshots collected during simulation is used as detail preview of the IER. In the experiment, we evaluate the completeness, correctness, and comprehension of the preview. The experiment result shows that the preview can be used to provide most information in the resource correctly and easy to understand. Our approach can save time for users in understanding the IERs. Copyright © 2016 by KSI Research Inc. and Knowledge Systems Institute Graduate School.

关键词： Image processing

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2nd International conference on Global Economic Revolutions, ICGER 2023

2nd International Conference on Global Economic Revolutions,...

引用

2nd International conference on Global Economic Revolutions, ICGER 2023

ISBN: (纸本)9783031505171

The proceedings contain 18 papers. The special focus in this conference is on Global Economic Revolutions. The topics include: Foreword;fintech-Enabled Financial Inclusion for Rural Networking;students Intention Towards Digital Entrepreneurship – Industry 5.0;quantifying the Dynamic Enablers of Blockchain technology to Achieve Operating Performance: A Conceptual Framework;effect of Socio-Demographic Factors on Consumer’s Attitude Towards Artificial Intelligent Based Digital Voice Assistant;the "Metaverse Mania" in Healthcare education: Students’ technology Acceptance;semiparametric Score-Driven Exponentially Weighted Moving Average Model;Impact of Social Media Marketing, innovation, and Effective Management on SMEs Performance: A Conceptual Study;Distributed Denial of Service Attack Detection Using Sequence-To-Sequence LSTM;enhanced Bubble Sorting Visualizer with Sound;machine-Learning Holistic Review in Tourism and Hospitality;does Blockchain technology Adoption Affect Decision-Making Performance: Evidence from Jordan;link Adaptation Performance in the Narrow Band Internet of Things;New Retail Format, Sales Management Applications for Business Using AI and Wireless Network;the Critical Factors Affecting the Feasibility of the Construction and Operation of a Co-location Datacenter in Kuwait;a Review of Job Postings in India Concerning Artificial Intelligence and Machine Learning Skills;performance Evaluation of Electric Vehicle Stocks: Paving a Way Towards Green Economy.

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Integration and Promotion: Integrating Sustainability Research into computer science Teaching through Serious Games Assignments 18

Integration and Promotion: Integrating Sustainability Resear...

引用

18th European conference on Games Based Learning, ECGBL 2024

作者： Haddick, Sean Puntha, Helen Harris, Matthew Brown, David J. Nottingham Trent University United Kingdom

ISBN: (纸本)9781917204194

"Serious Games" is a final-year 20 credit point module, undertaken as the default optional module for students on Undergraduate courses entitled BSc Computing and BSc computer science (Games technology) at Nottingham Trent University, UK. The module focuses on developing students’ critical evaluation skills, enhancing their ability to design and implement solutions for a real-world design brief, working with clients and making final products accessible to a broad target audience. Historically this was achieved through engagement with a single client, often via a wider research project or local educational establishment of some sort. More recently, the module has retained two client project briefs, which the students are then empowered to choose between. With each client brief the module team has sought to add extra value for the students. For the previous two academic years, the module team has partnered with Green Academy, a strategic team within the University whose priorities include stimulating pedagogical innovation and practice sharing within the area of sustainability and pioneering a shared understanding of sustainability education. The resulting partnership has introduced a brief for students which combines vital industry skills with sustainability literacy. Working with and alongside the students who are undertaking the module, the module has developed Serious Games on a diverse range of local and global sustainability issues and has exposed students to university research culture and our sustainability research specialisms. It has also necessitated that students engage with and contextualise the United Nations Sustainable Development Goals and the UNESCO ESD competencies which they are tasked with integrating into their design solutions. The long-term intent of this partnership is for these design decisions to be utilised in the Green Academy’s ongoing strategy to further enhance the University’s pedagogical framework and sustainability education offer, a

关键词： Students

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ESNet: Evolution and Succession Network for High-Resolution Salient Object Detection 41

ESNet: Evolution and Succession Network for High-Resolution ...

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41st International conference on Machine Learning, ICML 2024

作者： Liu, Hongyu Cong, Runmin Li, Hua Xu, Qianqian Huang, Qingming Zhang, Wei Institute of Information Science Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing China School of Control Science and Engineering Shandong University Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Computer Science and Technology Hainan University Hainan China Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

Preserving details and avoiding high computational costs are the two main challenges for the High-Resolution Salient Object Detection (HRSOD) task. In this paper, we propose a two-stage HRSOD model from the perspective of evolution and succession, including an evolution stage with Low-resolution Location Model (LrLM) and a succession stage with High-resolution Refinement Model (HrRM). The evolution stage achieves detail-preserving salient objects localization on the low-resolution image through the evolution mechanisms on supervision and feature;the succession stage utilizes the shallow high-resolution features to complement and enhance the features inherited from the first stage in a lightweight manner and generate the final high-resolution saliency prediction. Besides, a new metric named Boundary-Detail-aware Mean Absolute Error (MAEBD) is designed to evaluate the ability to detect details in high-resolution scenes. Extensive experiments on five datasets demonstrate that our network achieves superior performance at real-time speed (49 FPS) compared to state-of-the-art methods. Our code is publicly available at: https://***/rmcong/ESNet_ICML24. Copyright 2024 by the author(s)

关键词： Miocene

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Chest boundary shape estimation using a RGBD camera and pattern markers for robust lung electrical impedance tomography 17

Chest boundary shape estimation using a RGBD camera and patt...

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2017 International conference on Algorithms, Computing and Systems, ICACS 2017

作者： Na, Young Lee, Yunjung Kim, Jun-Geon Lee, Daeho Department of Electronic Engineering Kyung Hee University Yongin Korea Republic of Department of Computer Science and Engineering Postech Pohang Korea Republic of Humanitas College Kyung Hee University Yongin Korea Republic of

ISBN: (纸本)9781450352840

We propose a novel chest boundary estimation method using a RGBD camera for robust lung electric impedance tomography (EIT). For EIT imaging, sixteen electrodes are generally used, so we use the twelve electrodes as color markers and put pattern markers on the rest four electrodes. The color and pattern markers are detect to extract surface patches. The detected pattern markers are refined by affine parameters to correctly recognize the patterns. The boundary shapes are reconstructed by the registration using translation and rotation of consecutive surface patches. In the experiment results, the relative error of a round table is 0.0169, the processing fame rate is more than 12 frames/sec without GPU (graphics processing unit), and the more robust EIT reconstruction results are shown. © 2017 Association for Computing Machinery.

关键词： Electric impedance tomography

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