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Hyper-Parameter Optimization for Wireless network Traffic Prediction Models with A Novel Meta-Learning Framework

IEEE Internet of Things Journal 2025年

作者： Wang, Liangzhi Zhang, Jie Gao, Yuan Zhang, Jiliang Wei, Guiyi Zhou, Haibo Zhuge, Bin Zhang, Zitian Northeastern University College of Information Science and Engineering Shenyang China University of Sheffield Department of Electronic and Electrical Engineering SheffieldS10 2TN United Kingdom Wireless Network Design Ltd CambridgeCB23 3UY United Kingdom Shanghai University School of Communication and Information Engineering Shanghai China Zhejiang Gongshang University School of Information and Electronic Engineering Hangzhou China Nanjing University Department of Electrical and Computer Engineering Nanjing China

This paper proposes a novel meta-learning based hyper-parameter optimization framework for wireless network traffic prediction (NTP) models. The primary objective is to accumulate and leverage the acquired hyper-parameter optimization experience, enabling the rapid determination of optimal hyper-parameters for new tasks. In this paper, an attention-based deep neural network (ADNN) is employed as the base-learner to address specific NTP tasks. The meta-learner is an innovative framework that integrates meta-learning with the k-nearest neighbor algorithm (KNN), genetic algorithm (GA), and gated residual network (GRN). Specifically, KNN is utilized to identify a set of candidate hyper-parameter selection strategies for a new task, which then serves as the initial population for GA, while a GRN-based chromosome screening module accelerates the validation of offspring chromosomes, ultimately determining the optimal hyper-parameters. Experimental results demonstrate that, compared to traditional methods such as Bayesian optimization (BO), GA, and particle swarm optimization (PSO), the proposed framework determines optimal hyper-parameters more rapidly, significantly reduces optimization time, and enhances the performance of the base-learner. It achieves an optimal balance between optimization efficiency and prediction accuracy. © 2014 IEEE.

关键词： Genetic algorithms

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Socially-Critical Software Systems: Is Extended Regulation Required? 1

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29th European Systems, Software and Services Process Improvement, EuroSPI 2022

作者： Dagg, Niall Kostick, Conor Fallon, James O’Neill, Alex Yilmaz, Murat Messnarz, Richard Clarke, Paul M. School of Computing Dublin City University Dublin Ireland Department of Computer Engineering Gazi University Ankara Turkey ISCN the International Software Consulting Network Graz Austria Lero the Science Foundation Ireland Research Center for Software Limerick Ireland

ISBN: (数字)9783031155598

ISBN: (纸本)9783031155581

Data has become a prevailing aspect of our daily lives, becoming ever more present since the beginning of the 21st century. It is a commodity in today’s world and the amount of data being produced has increased enormously. One of the major ways data is produced and collected is from the use of websites and web-based applications. This data is later used for many different purposes. This paper presents findings from a multivocal literature review, exploring the methods of how this data is collected, what the data is used for once it has been collected, the ethics of data and its collection, and the future of data collection. Among the possible futures, we introduce the concept of socially-critical applications, where data harvesting in web-based applications might require pre-market disclosure and evaluation by notified bodies (instructed by regulation) as a means to break the existing cycle of technology companies outpacing under-resourced and ill-equipped regulators. Rather than regulators continually falling short of enacting laws to satisfy the common good, a new class of socially-critical application could be created in law to permit pre-market evaluation of applications (or versions of applications) that could undermine or interrupt the common good. © 2022, Springer Nature Switzerland AG.

关键词： Websites

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Vehicle Re-Identication Model Based on Optimized DenseNet121 with Joint Loss

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computers, Materials & Continua 2021年第6期67卷 3933-3948页

作者： Xiaorui Zhang Xuan Chen Wei Sun Xiaozheng He Jiangsu Engineering Center of Network Monitoring Engineering Research Center of Digital ForensicsMinistry of EducationSchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Nanjing University of Information Science&TechnologyNanjing210044China Department of Civil and Environmental Engineering Rensselaer Polytechnic InstituteTroyNY12180USA

With the increasing application of surveillance cameras,vehicle re-identication(Re-ID)has attracted more attention in the eld of public *** Re-ID meets challenge attributable to the large intra-class differences caused by different views of vehicles in the traveling process and obvious inter-class similarities caused by similar *** existing methods focus on local attributes by marking local ***,these methods require additional annotations,resulting in complex algorithms and insufferable computation *** cope with these challenges,this paper proposes a vehicle Re-ID model based on optimized DenseNet121 with joint *** model applies the SE block to automatically obtain the importance of each channel feature and assign the corresponding weight to it,then features are transferred to the deep layer by adjusting the corresponding weights,which reduces the transmission of redundant information in the process of feature reuse in *** the same time,the proposed model leverages the complementary expression advantages of middle features of the CNN to enhance the feature expression ***,a joint loss with focal loss and triplet loss is proposed in vehicle Re-ID to enhance the model’s ability to discriminate difcult-to-separate samples by enlarging the weight of the difcult-to-separate samples during the training *** results on the VeRi-776 dataset show that mAP and Rank-1 reach 75.5%and 94.8%,***,Rank-1 on small,medium and large sub-datasets of Vehicle ID dataset reach 81.3%,78.9%,and 76.5%,respectively,which surpasses most existing vehicle Re-ID methods.

关键词： Vehicle re-identication densenet joint loss focal loss SE block

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A Battery Swapping Service Management System Reliability-Based Design Concerning Station Information Delay

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IEEE Transactions on Consumer Electronics 2025年

作者： Li, Xinyu Cao, Yue Hu, Ziyi Zhang, Xu Liu, Zhi Lei, Xinhai Wuhan University School of Cyber Science and Engineering Wuhan430073 China Wuhan Institute of Technology Hubei Key Laboratory of Intelligent Robot Wuhan430250 China School of Computing Sciences Norwich United Kingdom University of Electro-Communications Department of Computer and Network Engineering Tokyo Japan Wuhan Public Resources Trading Center Wuhan China

Since the long duration associated with traditional plug-in charging modes inevitably causes range anxiety to electric vehicle (EV) drivers, the battery swapping technology has emerged as a promising alternative. It thus becomes imperative to develop a reliable battery swapping service system, efficiently managing the large-scale energy replenishing demands from EVs. Firstly, this paper considers drivers' trip destination to minimize total trip duration, and the expense paid for battery swapping service to save users' service cost. By optimizing the requirement of battery swapping service during peak-price period, the expenditure for energy supplement can be reduced. Secondly, concerning in practice that the transmission delay is a crucial factor impacting the overall network and system reliability, this paper further investigates the impact of station information delay between the global controller and battery swapping stations (BSSs). By characterizing the delay into two types, namely, low and large delays, the scenario based on a known delay type are investigated. Thirdly, delay cases with multiple BSSs are also taken into account and a mixed decision-making method is developed. Finally, simulation results indicate the desirable performance of proposed scheme in satisfying user demand and alleviating impact of station information delay. © 1975-2011 IEEE.

关键词： Decision making

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Free convection investigation for a Casson-based Cu−H₂O nanofluid in semi parabolic enclosure with corrugated cylinder

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Heliyon 2025年第1期11.0卷 e40960页

作者： Hameed, Rafel H. Hussein, Rana Ali Al-Salami, Qusay H. Alomari, Mohammed Azeez Hassan, Ahmed M. Alyousuf, Farah Q.A. Alqurashi, Faris Flayyih, Mujtaba A. University of Babylon College of Engineering Mechanical Engineering Department Iraq Power Mechanics Engineering Department Al-Musaib Technical College Al-Furat Al-Awsat Technical Babylon Hillah Iraq Department of Business Administration College of Administrative and Financial Sciences Cihan University-Erbil Iraq Department of Mechanical Engineering University of Al-Qadisiyah Ad-Diwaniyah 58001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbala Iraq Department of Mechanical Engineering University of Al-Qadisiyah Al-Qadisiyah 58001 Iraq Department of Computer Network College of Engineering and Computer Science Lebanese French University Kurdistan Region Erbil Iraq Department of Mechanical Engineering College of Engineering University of Bisha P.O. Box 551 Bisha 61922 Saudi Arabia Biomedical Engineering Department College of Engineering and Technologies Al-Mustaqbal University Hillah Iraq

The optimization of heat transfer in various engineering applications, such as thermal management systems and energy storage devices, remains a crucial challenge. This study aims to investigate the potential of Casson-based Cu-H₂O nanofluids in enhancing free convection heat transfer within complex geometries. The research examines the free convection heat transfer and fluid flow characteristics of a Casson-based Cu-H₂O nanofluid within a semi-parabolic enclosure that includes a wavy corrugated cylinder. Utilizing numerical simulations based on the Galerkin Finite Element Method, the study investigates the impact of different factors, including the Rayleigh number (10³ ≤ Ra ≤ 10⁶), Casson fluid parameter (0.1 ≤ γ ≤ 1), corrugation number (3 ≤ N ≤ 10), nanoparticle volume fraction (0 ≤ ϕ ≤ 0.15), and enclosure inclination angle (0° ≤ ζ ≤ 60°), on both heat transfer efficiency and flow patterns. The results reveal that increasing the Rayleigh number and Casson fluid parameter enhances heat transfer performance, with the average Nusselt number increasing by up to 165 % as Ra increases from 10³ to 10⁶. An optimal range of corrugation numbers is identified for maximizing heat transfer at higher Rayleigh numbers. The addition of nanoparticles significantly improves heat transfer, with a 20 % increase in the average Nusselt number observed at Ra = 10⁵ when the nanoparticle volume fraction increases from 0 to 0.15. These findings provide valuable insights for designing more efficient thermal management systems in applications such as electronics cooling, solar thermal collectors, and heat exchangers, potentially leading to improved energy efficiency and performance in various industrial and technological sectors. © 2024

关键词： Casson-based nanofluid Corrugated cylinder Cu-H2O nanofluid Free convection Heat transfer enhancement Semi-parabolic enclosure

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Sensing-Communication-Computing-Control Closed-Loop Optimization for 6G Unmanned Robotic Systems

arXiv

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arXiv 2024年

作者： Fang, Xinran Lei, Chengleyang Feng, Wei Chen, Yunfei Xiao, Ming Ge, Ning Wang, Cheng-Xiang State Key Laboratory of Space Network and Communications Department of Electronic Engineering Tsinghua University Beijing100084 China Department of Engineering University of Durham DurhamDH1 3LE United Kingdom Department of Information Science and Engineering School of Electrical Engineering and Computer Science Royal Institute of Technology Sweden National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China Purple Mountain Laboratories Nanjing211111 China

Rapid advancements in field robots have brought a new kind of cyber physical system (CPS)-unmanned robotic system-under the spotlight. In the upcoming sixth-generation (6G) era, these systems hold great potential to replace humans in hazardous tasks. This paper investigates an unmanned robotic system comprising a multi-functional unmanned aerial vehicle (UAV), sensors, and actuators. The UAV carries communication and computing modules, acting as an edge information hub (EIH) that transfers and processes information. During the task execution, the EIH gathers sensing data, calculates control commands, and transmits commands to actuators-leading to reflex-arc-like sensing-communication-computing-control (SC3) loops. Unlike existing studies that design SC3loop components separately, we take each SC3loop as an integrated structure and propose a goal-oriented closed-loop optimization scheme. This scheme jointly optimizes uplink and downlink (UL&DL) communication and computing within and across the SC3loops to minimize the total linear quadratic regulator (LQR) cost. We derive optimal closed-form solutions for intra-loop allocation and propose an efficient iterative algorithm for inter-loop optimization. Under the condition of adequate CPU frequency availability, we derive an approximate closed-form solution for inter-loop bandwidth allocation. Simulation results demonstrate that the proposed scheme achieves a two-tier task-level balance within and across SC3loops. © 2024, CC0.

关键词： Unmanned aerial vehicles (UAV)

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Block-based fine-grained and publicly verifiable data deletion for cloud storage: Block-based fine-grained and publicly verifiable..: C. Yang et al.

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Soft Computing 2024年第21期28卷 12491-12506页

作者： Yang, Changsong Liu, Yueling Ding, Yong Wu, Yongqiang Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin541004 China Lion Rock Labs of Cyberspace Security Institute of Cyberspace Technology HKCT Institute for Higher Education 999077 Hong Kong Guangxi Engineering Research Center of Industrial Internet Security and Blockchain Guilin University of Electronic Technology Guilin541004 China School of Computer Guangdong University of Science & Technology Dongguan523083 China South China Technical Support Department Topsec Network Technology Inc. Guangzhou510000 China

One of the most important services provided by cloud service providers (CSPs), cloud storage is economically attractive and can provide on-demand data storage service to resource-constrained tenants in the manner of pay-per-use. Therefore, by embracing cloud storage service, tenants can store their large-scale data on the remote cloud host to tremendously reduce local storage burden and computational overhead. However, due to the separation of cloud data ownership and management, cloud storage inevitably suffers from a few new security challenges, such as fine-grained cloud data deletion. To achieve data deletion in cloud storage, we design a vector-commitment-based publicly verifiable data deletion scheme, which can achieve data integrity auditing and block-based fine-grained data deletion. Specifically, our proposed scheme disguises the data deletion operation as data update operation. Therefore, the tenants can achieve data deletion by updating the cloud data blocks with some unrelated data blocks. Meanwhile, the tenants can prevent cloud data from being polluted by periodically performing data integrity auditing operation, thus guaranteeing that the cloud host sincerely maintains the data. Moreover, we formally analyze the security, which shows that our proposed scheme can satisfy all of the anticipative security requirements without interaction with a centralized third party. Finally, we develop a prototype system and evaluate the performance of our proposed scheme, which can intuitively demonstrate the high-efficiency and practicality of our proposal. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Data integrity

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An Integrated Fire Scene Information System Based on YOLOv4-Tiny and DeepSort Technologies

An Integrated Fire Scene Information System Based on YOLOv4-...

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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Chien Ho Chen Yu Cheng Wang Shao An Yu Department of Leisure Industry and Health Promotion National Taipei University of Nursing and Health Sciences Taipei City Taiwan Department of Computer Information and Network Engineering & Master Program Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (数字)9798350366976

ISBN: (纸本)9798350366983

This research introduces a pioneering framework for flame, smoke detection, and personnel monitoring, developed to address the increasing frequency of fire-related incidents in Taiwan. These incidents have caused significant loss of life and property damage. To tackle these issues, we employ YOLOv4-Tiny and DeepSort technologies to detect flames, smoke, and monitor personnel within surveillance footage, providing essential information to users. Unlike previous studies, this system integrates flame and smoke detection with personnel monitoring, enhancing rescue efficiency and ensuring personnel safety. During testing, the system effectively analyzed danger levels, monitored personnel, and provided necessary information. However, smoke can reduce the accuracy of personnel monitoring, so future research will aim to improve this issue and optimize the detection and identification of individuals moving between different footage. In summary, this investigation proposes a system that analyzes danger levels and monitors personnel in fire scenes. A survey of firefighters and security personnel concluded that this system helps improve rescue efficiency and reduce personnel loss due to fire incidents.

关键词： Training Adaptation models Accuracy Target tracking Computational modeling Heuristic algorithms Fires

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Live Demonstration: Low Cost AES-256 Circuit Design and Application

Live Demonstration: Low Cost AES-256 Circuit Design and Appl...

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IEEE Asia-Pacific Conference on Circuits and Systems

作者： Chia-Chou Chuang Yu-Lun Jheng Chien Huang Lu-Ying Huang Pei-Yin Chen Narn-Yih Lee Program on Integrated Circuit Design Academy of Innovative Semiconductor and Sustainable Manufacturing National Cheng Kung University Tainan Taiwan Department of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan Network & Information Security Division Computer and Network Center National Cheng Kung University Tainan Taiwan

ISBN: (数字)9798350378771

ISBN: (纸本)9798350378788

With the advent of the post-quantum era, the most worrying issue is information security. Quantum computers have been able to crack common asymmetric cryptography, such as RSA, DSA, ECC, etc, by Shor’s Algorithm. In terms of common symmetric-key algorithm, Grover’s algorithm can reduce the difficulty of brute-force cracking from N attempt to $\sqrt{N}$ [1], which decreases the security. In other words, the symmetric-key algorithm doubling the key size can effectively resist quantum attacks. Hence, AES-256 will be a worthwhile research topic in the future.

关键词： computers Quantum computing Costs Circuits and systems Asia Information security Resists Elliptic curve cryptography Circuit synthesis Cryptography

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A Lightweight Cloud-Edge Collaborative Intelligence Inference Framework with Runtime Dynamic Optimization for Resource-Constrained Consumer Electronics

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IEEE Transactions on Consumer Electronics 2025年

作者： Wang, Chenlu Peng, Yuhuai Zhang, Dawei Alturki, Ryan Alshawi, Bandar Alotaibi, Majid Northeastern University College of Computer Science and Engineering Shenyang110819 China Zhiyuan Research Institute Xihu District Hangzhou China Zhengzhou University School of Computer and Artificial Intelligence Henan Zhengzhou450001 China Umm Al-Qura University College of Computing Department of Software Engineering Makkah24382 Saudi Arabia Umm Al-Qura University College of Computing Department of Computer and Network Engineering Makkah24382 Saudi Arabia

The proliferation of Internet of Things (IoT) and embedded computing has led to widespread deployment of smart consumer electronics requiring edge-based Artificial Intelligence (AI) capabilities. However, the heterogeneous nature of sensing data and dynamic edge environments poses significant challenges for efficient model inference on resource-constrained devices. To address these challenges, this paper presents a lightweight collaborative inference framework designed for consumer electronics. First, we formulate the inference optimization problem as a Mixed-Integer Nonlinear Programming (MINLP) problem, considering channel pruning, early exit and cloud offloading decisions to optimize the trade-off between accuracy and computational cost. Second, we propose a selective model activation mechanism based on Markov Decision Process (MDP), which employs a recursive self-attention mechanism to dynamically track inference budgets and guide decision-making through encoder-decoder architectures. The mechanism integrates entropy regularization during training to ensure robust and diverse execution paths. Comprehensive experiments demonstrate that our framework achieves 65.50% reduction in model parameters and 80.68% reduction in inference Floating Point Operations (FLOPs) while maintaining accuracy loss within 0.81% of the original model, making it suitable for real-time AI applications on resource-constrained consumer electronics. © 1975-2011 IEEE.

关键词： Markov processes

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