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Distributed Resource Allocation in Dispersed Computing Environment Based on UAV Track Inspection in Urban Rail Transit

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computers, Materials & Continua 2024年第7期80卷 643-660页

作者： Tong Gan Shuo Dong Shiyou Wang Jiaxin Li Division of Consulting Beijing Metro Consultancy Corporation Ltd.Beijing100037China Department of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China

With the rapid development of urban rail transit,the existing track detection has some problems such as low efficiency and insufficient detection coverage,so an intelligent and automatic track detectionmethod based onUAV is urgently needed to avoid major safety *** the same time,the geographical distribution of IoT devices results in the inefficient use of the significant computing potential held by a large number of *** a result,the Dispersed Computing(DCOMP)architecture enables collaborative computing between devices in the Internet of Everything(IoE),promotes low-latency and efficient cross-wide applications,and meets users’growing needs for computing performance and service *** paper focuses on examining the resource allocation challenge within a dispersed computing environment that utilizes UAV inspection ***,the system takes into account both resource constraints and computational constraints and transforms the optimization problem into an energy minimization problem with computational *** Markov Decision Process(MDP)model is employed to capture the connection between the dispersed computing resource allocation strategy and the system ***,a method based on Double Deep Q-Network(DDQN)is introduced to derive the optimal ***,an experience replay mechanism is implemented to tackle the issue of increasing *** experimental simulations validate the efficacy of the method across various scenarios.

关键词： UAV track inspection dispersed computing resource allocation deep reinforcement learning Markov decision process

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A TREE STRUCTURE FOR STORAGE, ACCESS AND COLLISION DETECTION OF DISKS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer science 2023年第1期85卷 53-64页

作者： Sohrabi, S. Moradinejad, A. Asgharian, A. Department of Mathematics Faculty of Science Urmia University Urmia57561-51818 Iran Faculty of Engineering Urmia University Urmia Iran Department of Computer Engineering Faculty of Electrical and Computer Engineering Urmia University Urmia57561-51818 Iran

This paper presents a new and efficient tree data structure for sorting and collision detection of disks in 2D based on a new tree-based data structure, called hexatree, which is introduced for the first time in this paper. The data structure relies on mapping the objects to a space 1 dimension higher and then doing an appropriate range query in that range which is 3D range queries with circular cones of fixed direction and opening angle. Once the tree is constructed in O(n log n) time, disk collision detection queries can be answered in time O(n0.61). The proposed algorithm, in principle, is a dynamic structure;that is, it’s a structure that can be modified once it’s built. The proposed algorithm can be used for designing CAD softwares and other issues that require searching for a disk among a multitude of 2D disks. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： computer aided design

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iSummary: Workload-Based, Personalized Summaries for Knowledge Graphs 20th

iSummary: Workload-Based, Personalized Summaries for Knowled...

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20th International Conference on The Semantic Web, ESWC 2023

作者： Vassiliou, Giannis Alevizakis, Fanouris Papadakis, Nikolaos Kondylakis, Haridimos Department of Electrical and Computer Engineering HMU Heraklion Greece Computer Science Department UOC Heraklion Greece Institute of Computer Science FORTH Heraklion Greece

ISBN: (纸本)9783031334542

The explosion in the size and the complexity of the available Knowledge Graphs on the web has led to the need for efficient and effective methods for their understanding and exploration. Semantic summaries have recently emerged as methods to quickly explore and understand the contents of various sources. However, in most cases, they are static, not incorporating user needs and preferences, and cannot scale. In this paper, we present iSummary, a novel, scalable approach for constructing personalized summaries. As the size and the complexity of the Knowledge Graphs for constructing personalized summaries prohibit efficient summary construction, in our approach we exploit query logs. The main idea behind our approach is to exploit knowledge captured in existing user queries for identifying the most interesting resources and linking them, constructing as such high-quality, personalized summaries. We present an algorithm with theoretical guarantees on the summary’s quality, linear in the number of queries available in the query log. We evaluate our approach using three real-world datasets and several baselines, showing that our approach dominates other methods in terms of both quality and efficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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Evolutionary Optimization with a Simplified Helper Task for High-Dimensional Expensive Multiobjective Problems

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ACM Transactions on Evolutionary Learning and Optimization 2024年第4期4卷 1-32页

作者： Wu, Xunfeng Lin, Qiuzhen Zhou, Junwei Liu, Songbai Coello Coello, Carlos A. Leung, Victor C. M. College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan430070 China Mexico City07300 Mexico Department of Electrical and Computer Engineering University of British Columbia VancouverBCV6T 1Z4 Canada

In recent years, surrogate-Assisted evolutionary algorithms (SAEAs) have been sufficiently studied for tackling computationally expensive multiobjective optimization problems (EMOPs), as they can quickly estimate the qualities of solutions by using surrogate models to substitute for expensive evaluations. However, most existing SAEAs only show promising performance for solving EMOPs with no more than 10 dimensions, and become less efficient for tackling EMOPs with higher dimensionality. Thus, this article proposes a new SAEA with a simplified helper task for tackling high-dimensional EMOPs. In each generation, one simplified task will be generated artificially by using random dimension reduction on the target task (i.e., the target EMOPs). Then, two surrogate models are trained for the helper task and the target task, respectively. Based on the trained surrogate models, evolutionary multitasking optimization is run to solve these two tasks so that the experiences of solving the helper task can be transferred to speed up the convergence of tackling the target task. Moreover, an effective model management strategy is designed to select new promising samples for training the surrogate models. When compared to five competitive SAEAs on four well-known benchmark suites, the experiments validate the advantages of the proposed algorithm on most test cases. © 2024 held by the owner/author(s).

关键词： Multitasking

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Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

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Digital Communications and Networks 2024年第1期10卷 38-44页

作者： Mianjie Li Senfeng Lai Jiao Wang Zhihong Tian Nadra Guizani Xiaojiang Du Chun Shan School of Electronics and Information Guangdong Polytechnic Normal UniversityGuangzhou510665China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Schoolof Electrical Engineering and Computer Science Washington State UniversityPullmanWA99164USA Department of Computer and Information Science Temple UniversityPhiladelphiaPA19122USA

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication *** that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of *** multiwatermarking process employs spread transform dither *** the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading ***,multiple watermarks can be simultaneously embedded into the same position of a multimedia ***,the multiple watermarks can be extracted without affecting one another during the extraction *** analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

关键词： B5G Multimedia information security Spread transform dither modulation Spreading vector measurement Unit maximum capacity

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Backup subscription scheme for differential protection using IEC61850-9-2 sampled values

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Energy Informatics 2024年第1期7卷 110页

作者： Katoulaei, Mohammad Khalili Rahmani, Aamir Høidalen, Hans Kristian Oleinikova, Irina Mork, Bruce Department of energy systems Norwegian University of Science and Technology Trondheim Norway Department of electrical power system Michigan Technical University Michigan United States Department of Electrical Power Engineering Norwegian University of Science and Technology Trondheim Norway Department of Electrical and Computer Engineering Michigan Technological University HoughtonMI49931 United States

In IEC-61850-based digital substations, the protection IED’s performance is dependent on merging unit’s vendor implementation, communication networks, and measurement circuit’s health conditions. As the process bus Sampled Value(SV) enables the availability of all sensor data on a communication network, this paper proposes a Backup Subscription scheme (BSS) for a transformer differential protection (87T, PDIF) function. BSS utilizes sensor data in digital substations to achieve a flexible protection scheme using a dynamic subscription feature. Thus, in case of failure of one sensor, differential protection would be maintained. The paper presents the implementation and verification of a prototyped scheme using a Hardware-in-the-loop simulation test bed. The main result is that BSS integration into differential protection ensures its dependability and security. Moreover, delay compensation and seamless switching feature increases the availability of differential protection. © The Author(s) 2024.

关键词： Hardware-in-the-loop simulation

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Evaluating ASCON Lightweight Encryption Algorithm for Image Encryption

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SN computer science 2024年第8期5卷 1-16页

作者： Alghamdi, Yousef Munir, Arslan Department of Computer Science Kansas State University Manhattan 66506 KS United States Department of Electrical Engineering and Computer Science Florida Atlantic University Boca Raton 33431 FL United States

Researchers over the past few decades have proposed specialized algorithms for image encryption, in order to solve the slow encryption speed and high computational requirements of traditional encryption algorithms. The National Institute of Standards and Technology (NIST) selected the Ascon algorithm as the new standard for lightweight cryptography applications. In this paper, the Ascon algorithm is tested and evaluated for image encryption. Experimental results show that the Ascon is fast, reliable, and secure. Experimental results further reveal that the Ascon either outperforms most of the contemporary image encryption algorithms in terms of image encryption metrics for quality, efficiency, and security or performs similar to other algorithms. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Ascon Image encryption NIST Permutation Substitutions

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FedRME: Federated Learning for Enhanced Distributed Radiomap Estimation 100

FedRME: Federated Learning for Enhanced Distributed Radiomap...

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100th IEEE Vehicular Technology Conference, VTC 2024-Fall

作者： Zhang, Weishan Wang, Yue Liu, Lingjia Tian, Zhi George Mason University Department of Electrical and Computer Engineering FairfaxVA United States Georgia State University Department of Computer Science AtlantaGA United States Virginia Tech Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798331517786

For future intelligent communication systems, radiomap estimation (RME) is essential for acquiring panoramic awareness of spectrum spatial distribution in wireless environments. Recently, deep learning-based RME methods have been developed to reconstruct radiomaps from spectrum measurements collected at distributed sensors. However, these methods rely on gathering all input data at a central fusion center, resulting in large communication overheads, high computation costs, and privacy leakage concerns. To address these challenges, this work proposes a FedRME approach that makes federated learning applicable for distributed RME over a large-scale network, accommodating geographically heterogeneous transmitter locations and propagation environments. Specifically, we partition the large area into smaller regions to reduce the model complexity required for learning the radiomap in each region. Meanwhile, we incorporate the landscape map as an auxiliary input to induce a common learning model that adheres to the same propagation physics across all these heterogeneous regions. In doing so, fusion centers in all regions can collaborate through federated learning to enhance the overall RME performance. Simulation results indicate that our proposed method outperforms existing benchmarks, particularly under limited data, achieving higher learning accuracy with reduced model complexity and lower computational cost. © 2024 IEEE.

关键词： Federated learning

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Automatic Modulation Recognition Using Parallel Feature Extraction Architecture 18th

Automatic Modulation Recognition Using Parallel Feature Extr...

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18th International Conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Tang, Haolin Zhao, Yanxiao Kuzlu, Murat Luo, Changqing Catak, Ferhat Ozgur Wang, Wei Department of Electrical and Computer Engineering Virginia Commonwealth University RichmondVA United States Department of Engineering Technology Old Dominion University NorfolkVA United States Department of Computer Science Virginia Commonwealth University RichmondVA United States Department of Electrical Engineering and Computer Science University of Stavanger Rogaland Norway Department of Computer Science San Diego State University San DiegoCA United States

ISBN: (纸本)9783031714665

Automatic Modulation Recognition (AMR) plays a critical role in wireless communication and can be applied in various applications such as spectrum monitoring and signal surveillance. Recently, different AMR approaches have been proposed based on Deep Learning (DL), which are inspired by the powerful abilities of feature extraction in neural networks, i.e., Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). Among these solutions, hybrid methods extract spatial features and temporal features of signals by combining CNN and RNN into a single architecture to provide better performance. However, it is inefficient to extract two types of features using a single architecture since the temporal feature could be degraded after CNN layers, and the spatial feature may be compromised after RNN layers. To overcome this challenge, we propose a parallel neural network architecture for AMR, which extracts spatial features using CNN layers and temporal features using LSTM (Long Short-Term Memory) layers, respectively, in two parallel routes. Afterward, the extracted features will be combined to predict the modulation scheme of a signal. Extensive simulations are conducted on signals with 11 different modulation methods at a wide range of Signal-to-Noise Ratio (SNR) levels to evaluate our proposed parallel feature extraction architecture. In addition, we compare our solution against three other DL-based methods, and the results show that our method outperforms in terms of recognition accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

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Nano-structured metamaterial absorber based on a plus-shaped resonator for optical wavelength applications

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Journal of engineering and Applied science 2024年第1期71卷 134页

作者： Islam, Istiaq Mohammad Tanvirul Islam, Sikder Sunbeam Islam, Md. Rashedul Karim, Abu Naser Md. Rezaul Azim, Rezaul Department of Electrical and Electronic Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Computer Science and Engineering International Islamic University Chittagong Chittagong Bangladesh Department of Physics Chittagong University Chittagong Bangladesh

Metamaterial absorbers have sparked widespread interest due to their remarkable electromagnetic properties, which enable a wide range of applications in light absorption and manipulation. This study introduces a new three-layer nanomaterial absorber (NMA) unit cell composed of nickel (Ni), silicon dioxide (SiO2), and nickel (Ni) designed to operate across the entire visible spectrum (390–780 nm). We demonstrate the NMA’s exceptional absorption characteristics through rigorous numerical simulations using industry-standard software, achieving a mean absorption rate of 97.17% and a maximum absorption peak of 99.99% at 694.89 nm under standard angles. Furthermore, the NMA unit cell has good impedance matching, efficient coupling between capacitors and inductors, and significant plasmonic resonance properties. Fabrication feasibility and potential applications in solar energy harvesting, optical sensing, and light detection. © The Author(s) 2024.

关键词： Silica

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