Detection of Electric Network Frequency in Audio Using Multi-HCNet by Yujin Li, Tianliang Lu, Shufan Peng, Chunhao He, Kai Zhao, Gang Yang, Yan Chen

“…With the increasing application of electrical network frequency (ENF) in forensic audio and video analysis, ENF signal detection has emerged as a critical technology. …”
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Optimizing Age of Information in Internet of Vehicles over Error-Prone Channels by Cui Zhang, Maoxin Ji, Qiong Wu, Pingyi Fan, Qiang Fan

“…Although many studies aim to minimize the average AoI of the system through optimized resource scheduling schemes, they often fail to adequately consider the queue characteristics. …”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…The aforementioned problem is formulated as a multi-objective optimization problem with two objectives: average task completion latency and device energy consumption. …”
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Optimized Multiplicative Pre-Distortion PAPR Reduction Scheme for OTFS Signals by Feiyang Liu, Jiayang Zhao, Guangliang Ren

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On Optimization of RIS-Assisted Secure UAV-NOMA Communications with Finite Blocklength by D. Zhao, L. Hu, W. Xiong, H. Cai, Y. Qian, Y. Xing

“…In this paper, we propose a secure RIS-assisted UAV communication system based on NOMA with finite blocklength (FBL) transmission. To maximize the average secrecy rate for all ground users under the mobility and power constraints of the UAV, we jointly optimize the phase shift of the RIS, the trajectory, the transmit power of the UAV, and the user scheduling. …”
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Prediction of Electric Vehicle Mileage According to Optimal Energy Consumption Criterion by Oleksii Chkalov, Roman Dropa

“…By representing the road network as a weighted directed graph tailored to the energy consumption model, an algorithm aids in mileage optimization by determining the optimal path for immediate use. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…To address these challenges, this paper proposes a novel time series prediction model based on Temporal Convolutional Network (TCN), Multi-Layer Perceptron (MLP), and attention mechanism (referred to as “TCN-MLP-Attention”), using daily average price data from the U.S. avocado market from 2015 to 2023. …”
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IMP‐DETR: Optimization model for defect detection of injection‐moulded products by Anzhan Liu, Lei Han

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Slope deformation prediction based on GA–BP neural networks by Wenhui TAN, Kai LI, Huimin LIU, Meifeng CAI, Qifeng GUO

“…This algorithm optimizes the initial weights and thresholds of the BP neural network, leading to the establishment of the time-series deformation prediction model of slopes based on the GA–BP neural network. …”
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Optimization model of random load balancing of heterogeneous nodes in complex buildings by Wenlei GUO

“…In order to improve the load balancing of a complex building complex IoT and maintain its stable operation, a random load balance optimization model for non-uniformly distributed nodes in a complex building complex IoT was proposed.Sensor devices were deployed and wireless networks were accessed in complex building clusters to build the Internet of things for complex building clusters.The distribution location of each node in the Internet of things environment was determined, and random load data of non-uniformly distributed nodes was collected and integrated.The priority of non-uniformly distributed nodes was calculated using the IALBR routing protocol.By generating scheduling links and calculating the scheduling amount, the node load balancing scheduling task of the model was completed, and the load balancing of the Internet of things was optimized.The experimental results show that compared with traditional models, the average value of the load balance index of nodes under the design model is 0.002.The application of the design model effectively reduces the congestion probability of the Internet of things and improved network throughput.…”
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Evaluating automatic sectioning efficiency in distribution network of Kaliningrad region by D. Kugucheva, M. Kharitonov

“…The methodology for calculating the main indicative indicators of SAIFI and SAIDI is given and the choice of the optimal place for network partitioning is substantiated. …”
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A Data Item Selection Mechanism for Mobile Opportunistic Networks by Lei You, Jianbo Li, Changjiang Wei, Jixing Xu, Chenqu Dai

“…The nonexistence of an end-to-end path poses great challenges to directly adapting the traditional routing algorithms for Internet and mobile ad hoc networks (MANETs) to mobile opportunistic networks (MONs). …”
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A Dimmable OFDM Scheme With Dynamic Subcarrier Activation for VLC by Congcong Wang, Yang Yang, Julian Cheng, Caili Guo, Chunyan Feng

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Routing-Aware Clustering Algorithms for Two-Tiered Sensor Networks by Ataul Bari, Fangyun Luo, Arunita Jaekel, Subir Bandyopadhyay

“…The results indicate that our approaches, on average, can produce results that are close to the optimal solutions and consistently outperform existing heuristics.…”
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Robust Multihop Localization for Wireless Sensor Networks with Unreliable Beacons by Renjian Feng, Xiaolei Guo, Ning Yu, Jiangwen Wan

“…Finally, the normal nodes employ the weighted Taylor-series least squares solver to estimate the optimal values of their coordinates. Extensive simulation results in isotropic and anisotropic networks show the robustness and effectiveness of our algorithm.…”
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Energy-Balanced Routing for Maximizing Network Lifetime in WirelessHART by Sheng Zhang, Ao Yan, Tianming Ma

“…Simulation results show that the proposed algorithm can extend network lifetime by a factor of 2 relative to the maximum residual energy selection algorithm and prolong the network lifetime by a factor of 7 relative to the minimum transmission power routing algorithm, but the average energy consumption per route will increase by 2 dBm compared with the minimum transmission power routing algorithm.…”
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Wireless Sensor Networks Energy Effectively Distributed Target Detection by Xiaogang Qi, Peng Wei, Lifang Liu, Mande Xie, Guoyong Cai

“…According to the simulation results, the probability of the single node target detection is compared with that of the multisensor collaborative target detection, and the influence of the weight coefficient on average node energy consumption is analyzed. Furthermore, we provide the optimal data sampling period of target detection data.…”
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Learning uplinks and downlinks transmissions in RF-charging IoT networks by Yiwei Li, Yu Mu, Gaoyuan Zhang, Weiguang Wang

“…Abstract This paper considers uplink and downlink transmissions in a network with radio frequency-powered Internet of Things sensing devices. …”
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Fast Nonparametric Inference of Network Backbones for Weighted Graph Sparsification by Alec Kirkley

“…Here we develop a completely nonparametric framework for inferring the backbone of a weighted network that overcomes these limitations and automatically selects the optimal set of edges to retain using the minimum description length principle. …”
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Crowd-based collaboration caching mechanism in smart identifier network by Haifeng LI, Wei QUAN, Nan CHENG, Hongke ZHANG, Xuemin SHEN

“…Smart identifier network (SINET) is an innovative network architecture.Through dynamic collaboration of service resource,function groups and physical components,the network scalability,resource utilization and service quality were effectively improved by SINET,and an effective solution for the development of industrial Internet of things(IoT) could be provided.To promote content delivery in resource-constrained IoT,caching function was introduced in network components by SINET,and the bandwidth waste caused by traffic redundancy in resource-constrained node could be reduced.Therefore,how to efficiently cache content became an important research topic.Based on SINET architecture,a crowd-based collaboration cache (C2Cache) mechanism was proposed in this scheme.According to the actual network topology,the caching function group was dynamically created and optimized by C2Cache,and a function group as crowd minimum unit to execute the maximum benefit cache (MBC) algorithm was defined to maximize the caching space efficiency.With the self-developed emulation system,named EmuStack,the performance of C2Cache was evaluated.The experimental results show that,comparing with LCE,Random,Prob Cache,LCD and Greedy caching mechanisms,the cache hit rate can be improved effectively,then the average access time can be reduced significantly by C2Cache.In the simulated network scenario,the performance increases 15% to 30%.…”
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