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Resource-Adaptive Newton’s Method for Distributed Learning 29th

Resource-Adaptive Newton’s Method for Distributed Learning

引用

29th international computing and Combinatorics conference, COCOON 2023

作者： Chen, Shuzhen Yuan, Yuan Tao, Youming Cai, Zhipeng Yu, Dongxiao School of Computer Science and Technology Shandong University Qingdao266237 China Shandong University Jinan250100 China Department of Computer Science Georgia State University AtlantaGA30303 United States

ISBN: (纸本)9783031491894

By leveraging curvature information for improved performance, Newton’s method offers significant advantages over first-order methods for distributed learning problems. However, the practical applicability of Newton’s method is hindered in large-scale and heterogeneous learning environments due to challenges such as high computation and communication costs associated with the Hessian matrix, sub-model diversity, staleness in training, and data heterogeneity. To address these challenges, this paper introduces a novel and efficient algorithm called Resource-Adaptive Newton Learning (RANL), which overcomes the limitations of Newton’s method by employing a simple Hessian initialization and adaptive assignments of training regions. The algorithm demonstrates impressive convergence properties, which are rigorously analyzed under standard assumptions in stochastic optimization. The theoretical analysis establishes that RANL achieves a linear convergence rate while effectively adapting to available resources and maintaining high efficiency. Moreover, RANL exhibits remarkable independence from the condition number of the problem and eliminates the need for complex parameter tuning. These advantages make RANL a promising approach for distributed learning in practical scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Optimization

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Local-Area Communication Network Optimization for Secondary Control of Active Distribution System Based on MISDP Model

Local-Area Communication Network Optimization for Secondary ...

引用

international conference on Green Energy, computing and Sustainable technology (GECOST)

作者： Sheng, Lina Lou, Guannan Gu, Wei Lu, Shuai Chen, Chang Southeast Univ Sch Cyber Sci Engn Nanjing Peoples R China Southeast Univ Sch Elect Engn Nanjing Peoples R China Southeast Univ Sch Elect Engn Sch Cyber Sci Engn Nanjing Peoples R China

ISBN: (纸本)9781665486637

With the high participation of renewable distributed generation (DG) units, the power supply reliability of the active distribution system (ADS) under extreme events has been improved, but its operation control also faces new challenges. Since the secondary control layer of the ADS relies on the local-area communication network to realize the information interaction, the time delay is an inevitable inherent factor that affects the dynamic performance of the entire system seriously. This paper first proposes an optimal design method to simultaneously design the topology and link weights of sparse communication networks based on mixed integer positive semidefinite programming (MISDP). The balance between time delay robustness and convergence speed of secondary control in the ADS can be adjusted by setting weights of optimal indexes. Finally, the proposed optimization problem is solved by Yalmip with Mosek 9.3. The methods are verified by the simulation results based on MATLAB/Simulink.

关键词： distributed generation time delay robustness convergence speed communication network optimization MISDP active distribution system

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Explainable Artificial Intelligence Model for Electricity Usage Prediction in Nigeria 5

Explainable Artificial Intelligence Model for Electricity Us...

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5th IEEE international conference on Electro-computing Technologies for Humanity, NIGERCON 2024

作者： Alilu, Grace Egbi Okorie, Grace Chinenye Ayoade, Idowu Adetona Obonna, Ugochukwu Onyekachi Akinde, Olusola Kunle Nwakanma, Cosmas Ifeanyi Hallmark University Ijebu-Itele Nigeria Obafemi Awolowo University Ile Ife Nigeria University of Johannesburg Johannesburg South Africa Federal University of Technology Oweri Nigeria First Technical University Ibadan Nigeria Kumoh National Institute of Technology Ict Convergence Research Center Gumi South Korea

ISBN: (纸本)9798331542559

This study developed a model to predict electricity usage in Nigeria for policy and decision-making. Using XGBoost and LSTM, results showed XGBoost performed better with an RMSE of 0.089, MAPE of 18.51%, and R² of 0.8, making it the selected model. SHAP-based explainable AI (XAI) provided insights into key factors affecting electricity usage, with the hour of the day being the most significant, followed by the day, month, temperature, wind speed, cloud cover, pressure, and humidity. The model effectively predicts electricity usage and offers valuable insights for improving energy policies and decision-making. © 2024 IEEE.

关键词： dependence plot electricity consumption electricity usage prediction explainable AI SHAP XG Boost

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An Energy Efficiency Resource Allocation Scheme for Mobile Edge computing

An Energy Efficiency Resource Allocation Scheme for Mobile E...

引用

international conference on Information and Communication technology convergence (ICTC)

作者： Kang Liu Zaichen Zhang Jian Dang Liang Wu School of Information Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

This paper proposes a new energy-efficient scheme for a mobile edge computing (MEC) related wireless communication system. Specifically, a new energy efficiency model is proposed that computation energy con-sumption is considered. In this paper, computation energy is defined as the rate related energy used to provide the computing power in the information processing. Based on the model, we further formulate an optimization problem to maximize the weighted sum energy efficiency (WSEE) of all MEC servers. By applying the dual problem and the iterative methods, the optimization problem is solved and we present an energy-efficient allocation scheme. The simu-lation result shows the influence of the computation energy consumption on the system energy efficiency analysis. In addition, the result shows that the proposed allocation scheme outperforms both average allocation scheme and water-filling scheme.

关键词： Wireless communication Energy consumption Multi-access edge computing Computational modeling Energy efficiency Computational efficiency Resource management Servers Iterative methods Optimization

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EfficientNet-V2-B3 Transfer Learning for High-Accuracy Indian Bird Species Classification 15

EfficientNet-V2-B3 Transfer Learning for High-Accuracy India...

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15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Pillai, Rudresh Sharma, Neha Upadhyay, Deepak Devliyal, Swati Kaur, Gurjot Chitkara University Institute of Engineering & Technology Chitkara University Punjab India Graphic Era Hill University Computer Science & Engineering Uttarakhand Dehradun India Graphic Era Deemed to be University Computer Science &engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350370249

This research paper presents a study on classifying images of Indian birds into 25 different types using the EfficientNet-V2-B3 transfer learning model. The research focuses on using deep learning techniques to accurately classify images of Indian birds, which is important for many ecological and conservation efforts. The ' Indian-Birds-Species-Image-Classification' dataset, which contains 37,500 descriptive images of 25 Indian birds, was used in the study. To train and evaluate the model, the data was split into training, validation, and testing sets. The EfficientNet-V2-B3 model was chosen for its efficiency and effectiveness in image classification, especially through transfer learning. During training, the model was trained on 24,000 images in training set and their weights were adjusted to learn the unique characteristics of Indian birds. The validation set contained 6000 images and was used to monitor the performance of the model and prevent overfitting. The pre-trained EfficientNetB3 model was adjusted throughout the training phase using stochastic gradient descent and backpropagation. Measurements like accuracy and loss were monitored throughout several epochs during the training and validation phases to get insight into the model's convergence. A confusion matrix, which provides a thorough perspective of classification accuracy and misclassifications across species, was used to examine the model's performance. The confusion matrix created from the test results provides information on performance standards for each bird species, including several performance metrics. In test phase, the model classified images of Indian birds by species with 97% accuracy. This result highlights the effectiveness of the transfer learning methodology and the EfficientNet-V2-B3 architecture's adaptability for challenging classification problems. The implications for ornithology and biodiversity preservation are profound since this automated technique streamlines the procedures f

关键词： Deep Learning EfficientNet-V2-B3 Fine-Tuning Indian Birds Species Classification Ornithology Transfer Learning

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Emerging 5G, IoT and WSN: Opportunities, Challenges and Remedies

Emerging 5G, IoT and WSN: Opportunities, Challenges and Reme...

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international conference on Web Research (ICWR)

作者： Mohammad Reza Saadatmand Mohsen Ghotbi Technical & Network Operation Department Information Technology Business Intelligence MCI Tehran Iran Research & Development Department MCI Tehran Iran

ISBN: (数字)9798331508913

ISBN: (纸本)9798331508920

The convergence of 5th generation (5G) technology with the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) will be investigated in this paper. This convergence of these concepts will bring many benefits to the quality of life in communities by increasing the number of connected devices more safely and resulting in higher data rates. However, like any other uprising, it will have challenges, concerns, and bottlenecks. We offer resolutions and remedies to make applying the above three elements more feasible, accessible, and tangible. Future research directions for industries, academia, and policymakers will also be suggested.

关键词： Wireless communication Industries Wireless sensor networks Quantum computing 5G mobile communication Merging Ultra reliable low latency communication Internet of Things Sustainable development convergence

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Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions 7

Adding Common Sense to Robots by Completing the Incomplete N...

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7th IEEE international conference for convergence in technology, I2CT 2022

作者： De Silva, G.W.M.H.P. Rajapaksha, Samantha Jayawardena, Chandimal Sri Lanka Institute of Information Technology Faculty of Graduate Studies and Research Sri Lanka Sri Lanka Institute of Information Technology Faculty of Computing Sri Lanka

ISBN: (纸本)9781665421683

This system is developed to identify and complete the human's instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks. © 2022 IEEE.

关键词： Mobile robots

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Enhancement of Network Security in MANET Using Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO) for IoT Applications 6

Enhancement of Network Security in MANET Using Refined Adapt...

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6th IEEE international conference on Emerging Smart computing and Informatics, ESCI 2024

作者： Satyanarayana, P. Sofi, Umar Bashir Ahmed, Bisma Farooq Naga Saranya, N. Padma Rao, G.V.S. Gokula Krishnan, V. V. R. Siddhartha Engineering College Department of ECE AP Vijayawada India Punjab Technical University Department of CSE Punjab India Sathyabama Institute of Science and Technology Department of Biomedical Engineering Tamil Nadu Chennai India Meenakshi College of Engineering Department of MCA Tamil Nadu Chennai India S.R.K.R. Engineering College Department of ECE AP Bhimavaram India Department of CSE Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350306613

The proliferation of Internet of Things (IoT) devices in Mobile Ad-Hoc Networks (MANETs) has introduced complex security challenges, demanding innovative solutions to safeguard data integrity and network functionality. This paper proposes a novel approach, the Refined Adaptive Harris Hawks Optimization Algorithm (RAHHO), tailored to fortify network security within MANETs for IoT applications. The RAHHO method integrates the efficient search capabilities of the Harris Hawks Optimization (HHO) algorithm with a dynamic updating mechanism, enhancing convergence speed and accuracy in optimizing security parameters. Leveraging the adaptability of HHO, RAHHO dynamically adjusts hawk positions and updates search strategies, enabling robust exploration of security parameter spaces crucial for MANETs. Moreover, the application of RAHHO in MANETs offers a multifaceted enhancement of security measures. The outcomes reveal varying degrees of susceptibility to attacks, with HHO displaying the highest vulnerability, followed by CHHSO and MU-HHO. RAHHO emerges as notably more resilient, being 73.33% less vulnerable than HHO, 40.5% less vulnerable than CHHSO, and 20% less vulnerable than MU-HHO. Simulation results demonstrate the efficacy of RAHHO in reinforcing network security, showcasing notable improvements in network performance metric such as cost function. The results establish RAHHO as the most secure algorithm in this specific context, showcasing superior performance. The progressive decrease in vulnerability from HHO to RAHHO corresponds to an increase in overall security. © 2024 IEEE.

关键词： CHHSO HHO IoT MANET MU-HHO Network security RAHHO

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Research of Low-Carbon computing Network in Integrated Satellite-Ground System

Research of Low-Carbon Computing Network in Integrated Satel...

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IEEE international conference on Software Engineering and Service Sciences (ICSESS)

作者： Rui Huang Jiakang Xu Haitao Xu Liang Li China Telecom Corporation Limited Beijing China Beijing Spaceiot Technology Development Co. LTD. Beijing China University of Science and Technology Beijing Beijing China

In this paper, research on low-carbon computing networks in integrated satellite-ground systems is given. We have reviewed the research works in the satellite-earth convergence network and multi-access edge computing technology in the integrated satellite-earth convergence network. The development trends are also given for edge computing in the integrated satellite-ground system. Key technologies are deeply researched and Future research directions are discussed in detail.

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Focus, Distinguish, and Prompt: Unleashing CLIP for Efficient and Flexible Scene Text Retrieval 24

Focus, Distinguish, and Prompt: Unleashing CLIP for Efficien...

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32nd ACM international conference on Multimedia, MM 2024

作者： Zeng, Gangyan Zhang, Yuan Wei, Jin Yang, Dongbao Zhang, Peng Gao, Yiwen Qin, Xugong Zhou, Yu School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing China State Key Laboratory of Media Convergence and Communication Communication University of China Beijing China Lenovo Research Beijing China Institute of Information Engineering Chinese Academy of Sciences Beijing China Laboratory for Advanced Computing and Intelligence Engineering Wuxi China TMCC College of Computer Science Nankai University Tianjin China

ISBN: (纸本)9798400706868

Scene text retrieval aims to find all images containing the query text from an image gallery. Current efforts tend to adopt an Optical Character Recognition (OCR) pipeline, which requires complicated text detection and/or recognition processes, resulting in inefficient and inflexible retrieval. Different from them, in this work we propose to explore the intrinsic potential of Contrastive Language-Image Pre-training (CLIP) for OCR-free scene text retrieval. Through empirical analysis, we observe that the main challenges of CLIP as a text retriever are: 1) limited text perceptual scale, and 2) entangled visual-semantic concepts. To this end, a novel model termed FDP (Focus, Distinguish, and Prompt) is developed. FDP first focuses on scene text via shifting the attention to the text area and probing the hidden text knowledge, and then divides the query text into content word and function word for processing, in which a semantic-aware prompting scheme and a distracted queries assistance module are utilized. Extensive experiments show that FDP significantly enhances the inference speed while achieving better or competitive retrieval accuracy compared to existing methods. Notably, on the IIIT-STR benchmark, FDP surpasses the state-of-the-art model by 4.37% with a 4 times faster speed. Furthermore, additional experiments under phrase-level and attribute-aware scene text retrieval settings validate FDP's particular advantages in handling diverse forms of query text. The source code will be available at https://***/Gyann-z/FDP. © 2024 ACM.

关键词： Semantics

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