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共 10292 条记录，以下是431-440 订阅

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Analysis of Magnetic Field Characteristics of High Current Cables 10

Analysis of Magnetic Field Characteristics of High Current C...

引用

10th IEEE international conference on computer Science and Network Technology, ICCSNT 2022

作者： Cao, Bin He, Xiaodong Lu, Jiajun Yu, Ziying Qi, De Li, Bohan Marine Design and Research Institute Shanghai China Nuclear Power Institute Chengdu China

ISBN: (数字)9781665470612

ISBN: (纸本)9781665470612

the increasing use of high current cables in ships may cause electromagnetic interference problems. In this paper, the single cable and two cables are modeled and electromagnetic simulation is carried out for the high current cable, and the magnetic field characteristics of the high current cable are obtained, which has a guiding role in solving the electromagnetic interference and ensuring the electromagnetic safety of the ship system. © 2022 IEEE.

关键词： Signal interference

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Civil Engineering design in IoT: Leveraging Improved Swarm Intelligence Optimization 17

Civil Engineering Design in IoT: Leveraging Improved Swarm I...

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IEEE Congress on Cybermatics: 17th IEEE international conference on Internet of things, ithings 2024, 20th IEEE international conference on Green Computing and Communications, GreenCom 2024, 17th IEEE international conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE international conference on Smart Data, SmartData 2024

作者： Fu, Weiheng Chen, Rongzhong Chen, Kaiwen Xie, Xiaojun Fuzhou University College of Computer and Data Science Fuzhou China Xiamen Meteorological Bureau Xiamen Key Laboratory of Straits Meteorology Xiamen China Florida Transportarion Engineeeing Inc Roadway Design Department Punta Gorda United States Fuzhou University Zhicheng College Office of Network Security and Information Fuzhou China

ISBN: (纸本)9798350351637

Nowadays, swarm intelligence algorithms are used to solve various problem in IoT environments because of their excellent performance, and the particle swarm algorithm(PSO) is a superior algorithm in swarm intelligence algorithms. the original PSO, however, exhibits certain limitations. For instance, the utilization of random initialization results in a less diverse population distribution for PSO. During the algorithm iteration process, excessively large or small weight factors can also detrimentally impact the performance of the algorithm. Moreover, when dealing with multi-modal problems, the PSO algorithm can quickly converge to local optimal because of its "precocious". In this paper, a Double-Population Particle Swarm Optimization(DP-PSO) algorithm is proposed. Firstly, the chaotic mechanism is used to initialize the population to make its distribution more uniform and obtain better convergence results. Secondly, the oscillation characteristic of the sine function is used to improve the updating method of weight by adding the sine factor, and the search area of the particle is expanded. Finally, the double-population variation mechanism is introduced to enhance the variation ability and improve the solving accuracy in the later iteration. the experimental results show that the DP-PSO is superior to other algorithms in performance and has obvious improvement in the ability to expand the search space of the population and jump out of the local optimal solution. When applied to cantilever beam design, DP-PSO also has good competitiveness in terms of stability, robustness, and scalability. © 2024 IEEE.

关键词： Swarm intelligence

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Application of Genetic Algorithms for Personalized Cancer Treatment Planning 10

Application of Genetic Algorithms for Personalized Cancer Tr...

引用

10th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2023

作者： Yadav, Kanchan Sharma, Manish Deepak, A. Mayuri, K. Sararswat, Manish Srivastava, Amit Gla University Department of Electrical Engineering Mathura India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Saveetha School of Engineering Saveetha Institute of Medical and Technical Saveetha University Tamilnadu Chennai India Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad India Lloyd Institute of Engineering and Technology Greater Noida India Lloyd Law College Greater Noida India

ISBN: (纸本)9798350382471

In order to maximize therapeutic treatments based on unique patient genetics characteristics, this study studies the use using genetic algorithms (GAs) towards individualized cancer therapy planning. A deductive technique is used, utilizing secondary data streams for a design that is descriptive, and adopting an interpretative mindset. Data initial processing, genome encoding, and the creation of a multiple-purpose fitness function are all required for the technical execution. With a focus on computational effectiveness and resolution behavior, the procedure for optimization is rigorously assessed. the enhanced efficacy and decreased toxicity of GA-derived treatments are highlighted by comparison with traditional treatment tactics. Analyses of the technique's sensitivity as well as robustness show that it can adjust to changes in parameter values and maintain stability in a range of clinical settings. the practical advantages of individualized treatment plans are highlighted by clinical validation, which is supported by examples and shows superior responses to therapy and results for patients. Challenges are identified through critical analysis, such as the requirement for instantaneous information integration and ethical constraints. Future research is advised to focus on modifying parameter values, investigating hybrid optimization strategies, and using cutting-edge technologies. It is recommended to do ongoing research with long follow-up times to evaluate the long-term effects of individualized strategies. By demonstrating how GAs have the potential to transform chemotherapy planning and provide customized therapeutic methods that maximize efficacy with minimizing side effects, this research helps to shape the developing field of personalized oncology. © 2023 IEEE.

关键词： cancerarranging clinical characteristics genetic algorithms personalized treatment treatment alternatives

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A Unified Framework for Chili Leaf Disease Classification Using Federated Learning CNN 10

A Unified Framework for Chili Leaf Disease Classification Us...

引用

10th IEEE Uttar Pradesh Section international conference on Electrical, Electronics and computer Engineering, UPCON 2023

作者： Kaur, Arshleen Kukreja, Vinay Chamoli, Sushant Mehta, Shiva Garg, Ashish Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Graphic Era Hill University Computer Science and Engineering Uttarakhand Dehradun India Graphic Era Deemed to Be University Computer Science and Engineering Uttarakhand Dehradun India

ISBN: (纸本)9798350382471

the increasing complexities in agricultural practices, namely in identifying chili leaf diseases, need intelligent systems that can efficiently analyze large volumes of data. this research presents a unique methodology that utilizes the combination of Federated Learning and Convolutional Neural Networks (CNNs) to facilitate the categorization of five distinct classes of chili leaf illnesses among five separate clients. the architectural design incorporates four convolutional layers, four max-pooling layers, and two fully connected layers. this configuration supports a dimensionality of 234×234 pixels, resulting in ten output nodes representing twelve distinct classes. the technique used in this study yields a distinctive global model via the synthesis of local data models using Federated Averaging methods. While doing the Result Analysis, a comprehensive assessment was conducted on three distinct forms of averages: Macro, Micro, and Weighted. the objective of this evaluation was to get a thorough understanding of the overall performance of the global model. For example, one of the five customers, ES-l, exhibited a Macro average of 82.77%, Weighted average of 83.81%, and Micro average of 83.84%. At the upper range of the spectrum, ES-5 recorded percentages of 91.44%, 91.60%, and 91.60% for Macro, Weighted, and Micro averages, respectively. the figures above demonstrate the model's resilience and ability to effectively manage the trade-off between accuracy and recall across several classes, as seen by an Fl-Score spanning 82.75% to 91.44%. For example, ES-l had a worldwide accuracy rate of 94%, but ES-5 achieved a peak performance with an accuracy rate of 97%. © 2023 IEEE.

关键词： (CNN)_(FL) Augmentation image Chilli_leaves Disease Leaf diseases

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Parasitic Patch Antenna with Beam Switching for 5G Millimeter-Wave Frequencies 10

Parasitic Patch Antenna with Beam Switching for 5G Millimete...

引用

10th international conference on Engineering and Emerging Technologies, ICEET 2024

作者： Nurgali, Raiymbek Ahmad, Jawad Hashmi, Mohammad School of Engineering and Digital Science Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798331532895

this paper presents a novel millimeter-wave (mmWave) antenna design for 5G applications, featuring a parasitic elliptical patch antenna with beam-switching capabilities and coaxial feeding. the antenna was initially designed as a single-element patch antenna for the 28 GHz mmWave band, demonstrating favorable impedance matching and broadside radiation patterns. Circular parasitic patches with and without vias were strategically placed around the main radiator to enhance the radiation pattern and gain. the single-element design achieved an impedance bandwidth of 2.7 GHz (26.8-29.5 GHz) and a gain of 7.5 dBi at 28 GHz. the optimized parasitic structure, consisting of carefully positioned open and short circular patches, significantly improved the antenna's performance. the parasitic design exhibited an enhanced return loss of -30.5 dB, indicating excellent impedance matching, and a gain of approximately 8 dBi. the proposed antenna exhibits enhanced performance characteristics in terms of gain, return loss, and beam steering capabilities, and it is suitable for next-generation wireless communication systems. © 2024 IEEE.

关键词： Slot antennas

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Retouching System to Ease Difficulty of Craft design for Paper-Cutting 10th

Retouching System to Ease Difficulty of Craft Design for Pap...

引用

10th international conference on Culture and Computing (C and C) Held as Part of the 24th international conference on Human-computer Interaction (HCII)

作者： Higashi, Takafumi Tokyo Denki Univ Adachi Ku Senjuasahimachi 5 Tokyo Japan

ISBN: (纸本)9783031054341;9783031054334

We present our system for quantifying artistic production difficulty and adjusting retouching difficulty to improve production. A paper-cutting artwork is created by controlling a knife and cutting designed paper. Paper-cutting craft designs have two parts: a white area for cutting out and a black area for painting. We have measured the difficulty of the picture based on the thickness of the cutting borderlines. In this paper, we have developed the retouching system that eases the difficulty of craft design by adjusting the line thickness. We have experimented with the effect of this system on the novice's production. As a result, we found that the system improved the accuracy and psychological state (flow state) by retouching craft design.

关键词： Cutting Pressure Steering law Flow theory Human motor performance

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Parallel-EvoCluster: An Open-Source Parallel Nature-Inspired Optimization Clustering 1

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10th Annual international conference on Information Management and Big Data (SIMBig)

作者： Alvarez-Mamani, Edwin Yarahuaman-Rojas, Milagros Huillca-Huallparimachi, Raul Pontificia Univ Catolica Peru Engn Dept Lima Peru Univ Nacl San Antonio Abad Cusco Dept Informat Cuzco Peru Univ Nacl Mayor San Marcos Fac Syst Engn & Informat Lima Peru

ISBN: (数字)9783031636165

ISBN: (纸本)9783031636158;9783031636165

Bio-inspired algorithms are a branch of Artificial Intelligence in which the behavior of natural systems is emulated to design non-deterministic heuristic methods for search, clustering, optimization, and simulation. Clustering algorithms search for patterns in the data and identify groups into clusters having similar features. the objective of this research is to improve the execution times of ten bio-inspired serial algorithms to solve clustering problems. To achieve our objective, we use parallelization techniques to reduce execution time by utilizing all processing resources. We proposed Parallel-EvoCluster to parallelize ten algorithms through two parallelization approaches, such as shared-memory and distributed-memory architecture using Open Multi-Processing and Message Passing Interface APIs respectively. Both approaches were performed using 24 CPU cores. the results show a significant improvement in runtimes of the parallel algorithms, parallelization with MPI on average is 10.14x times faster and the average parallelization with OMP is 9.05x times faster than the serial versions. the code is available at: https://***/win7/Parallel EvoCluster.

关键词： Clustering Parallel computer Bio-inspired Model island MPI OMP

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Justrent (A House Rental Management System) 10

Justrent (A House Rental Management System)

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10th international conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Cholaraja, K. Vignesh, M. Srinidhi, B. Raghu Muthu Vishal, S. Rishin Nethaji, S. Sri Eshwar College of Engineering Department of Computer Science and Business Systems Coimbatore India

ISBN: (纸本)9798350384369

the new digital platform called the House Rental Management System is revolutionizing the management of rental properties. It provides a quick and convenient alternative for landlords and tenants to manage a variety of rental property issues. Tenant administration, tracking of rental listings and availability, automatic rent collection, handling of maintenance requests, financial tracking and reporting, and secure document management are some of the key features. this approach improves communication between landlords and tenants, streamlines procedures, and decreases paperwork. It guarantees timely rent collection, prompt maintenance response, and precise upkeep of financial records. the House Rental Management System is a useful tool for streamlining and improving the experience of managing rental properties, benefiting both property owners and tenants with its user-friendly design and robust features the House Rental Management System offers benefits that go beyond simple convenience. It encourages responsibility and openness in property management. through thorough financial reports, property owners may easily track rental revenue, expenses, and property performance, enabling well-informed decision-making. this system's transparency benefits tenants as well because it makes it simple for them to view lease agreements, payment histories, and maintenance records, assuring a fair and reliable rental experience. In the end, the House Rental Management System is a potent instrument that not only makes managing rental properties easier on a daily basis, but also promotes efficiency, trust, and financial stability for both landlords and tenants. It establishes a new benchmark for contemporary, trouble-free rental property administration. © 2024 IEEE.

关键词： Efficiency

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Predictable Track-based Routing in Flying Ad hoc Networks 10

Predictable Track-based Routing in Flying Ad hoc Networks

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10th IEEE international conference on Cyber Security and Cloud Computing and 9th IEEE international conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Kai, Zhu Baokang, Zhao Xin, Qin National University of Defense Technology College of computer Changsha China University of the Faroe Islands Faculty of Science and Technology Faroe Islands Denmark

ISBN: (纸本)9798350312461

Flying Ad-hoc network (FANETs), a new kind of mobile AD hoc network, uses the aircraft as the air wireless communication node to construct a network and achieve effective communication at the network layer as a result of the ongoing expansion of communication networks into many industries. However, the high dynamics, limited node energy, and low network density of the FANETs present significant challenges to the FANETs routing protocol, which requires urgent attention in terms of its design. In order to address the issues associated with the routing metric of the FANETs routing protocol, such as the underutilization of link information and the inadequate consideration of the motion of UAVs, which result in high network packet loss rates, unstable routing, and long route reconvergence times, this paper proposes the Predictable Track-based Routing Protocol (PTP). PTP divides the routing protocol into three stages: route establishment, data transmission, and route maintenance. PTP creatively suggests Node Stability Factors (NSF) for UAV in the route establishment stage and develops a Q-learning algorithm to maintain it in accordance with the status of the nodes and nearby nodes. NSF combined the link quality calculated by HELLO messages to generate a link quality based on Q-learning(LQQ) metric. After that, the optimal path from the source node to the destination node is calculated based on this metric. In the data transfer phase, data is transmitted through the routes calculated in the route establishment phase. Create a new HELLO message during the routing maintenance phase to learn the location of the neighbor node and the two-hop neighbor node, predict the node's future location using the Kalman filter algorithm based on the node's past location, and react quickly when the link is about to change. Compared to conventional approaches, experiments demonstrate that PTP may successfully raise the successful data delivery rate by 10% to 30%, increase the average route s

关键词： Routing protocols

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Hardware Acceleration of Molecular Property Graph Prediction on a Heterogeneous Edge Platform 10

Hardware Acceleration of Molecular Property Graph Prediction...

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10th Nordic Circuits and Systems conference

作者： Grailoo, Mahdieh Nikoubin, Tooraj Nunez-Yanez, Jose Linkoping Univ Linkoping Sweden Univ Texas Dallas Dallas TX USA

ISBN: (纸本)9798331517663;9798331517670

Molecular property prediction is a critical task in computer-aided drug discovery workflows. In this context, representing molecules as graph structures has become a common approach, leading to the development of graph-based neural networks (GNNs). A prominent type of GNN are the graph convolution network (GCN) that incorporates a number of graph convolution layers followed by fully connected layers in the form of multi layer perceptrons (MLP). Addressing the need for enhanced efficiency, this paper introduces an innovative approach that maps different computation types to specialized accelerators in a heterogeneous edge platform. the proposed system integrates an FPGA accelerator for the sparse operations present in the GCN layer and an Edge TPU for ordinary dense operations in the fully connected layer. the FPGA accelerator is described using High-Level Synthesis (HLS) and optimized to handle the sparsity found on the graph structure and node features while the Edge TPU deploys a systolic array of MAC units optimized for dense matrix multiplication. this hardware/software co-designed GCN+MLP architecture utilizes Pynq and TensorFlow Lite Runtime functions, executed on a multi-core ARM CPU available in an AMD/Xilinx Zynq ultrascale+ device, in conjunction with the Edge TPU and programmable logic. Our results demonstrate performance improvements, achieving speedups of up to 47x compared to traditional software implementations.

关键词： Graph neural network hardware accelerators hardware/software co-design FPGA HLS streaming PYNQ overlay Edge TPU heterogeneous edge platform Molecular property prediction graph representation

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