Space-time coding scheme for the paired weak user in MIMO-NOMA systems by Mingyan GONG, Zhen YANG

“…In view of the paired weak user’s poor outage performance in multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) systems,Alamouti code was adopted to encode for the weak user in order to improve its outage performance by means of diversity,and the closed-form expression of the strong user’s ergodic capacity as well as the boundary-form expressions of the weak user’s ergodic capacity and outage probability was derived in the proposed model.Moreover,a power allocation algorithm for optimizing the system’s throughput was proposed.Finally,the numerical results show the accuracy of the derived expressions,the efficacy of the proposed algorithm,and that the weak user’s outage performance in the proposed coding scheme is far superior to that in the current coding scheme only adopting vertical Bell lab layered space-time (V-BLAST) code.…”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Existing research mainly focuses on monitoring and early warning technologies or algorithm optimization for individual disasters, lacking a coordinated mechanism for multi-disaster monitoring and early warning, as well as disaster avoidance path planning under emergency response. …”
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Accurate Extraction of Rural Residential Buildings in Alpine Mountainous Areas by Combining Shadow Processing with FF-SwinT by Guize Luan, Jinxuan Luo, Zuyu Gao, Fei Zhao

“…Precise extraction of rural settlements in alpine regions is critical for geographic data production, rural development, and spatial optimization. However, existing deep learning models are hindered by insufficient datasets and suboptimal algorithm structures, resulting in blurred boundaries and inadequate extraction accuracy. …”
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DAG-based swarm learning: A secure asynchronous learning framework for Internet of Vehicles by Xiaoge Huang, Hongbo Yin, Qianbin Chen, Yu Zeng, Jianfeng Yao

“…In this paper, we propose a Directed Acyclic Graph (DAG) based Swarm Learning (DSL), which integrates edge computing, FL, and blockchain technologies to provide secure data sharing and model training in IoVs. To deal with the high mobility of vehicles, the dynamic vehicle association algorithm is introduced, which could optimize the connections between vehicles and road side units to improve the training efficiency. …”
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Evaluation for Sortie Generation Capacity of the Carrier Aircraft Based on the Variable Structure RBF Neural Network with the Fast Learning Rate by Tiantian Luan, Mingxiao Sun, Guoqing Xia, Daidai Chen

“…However, the structure and the convergence rate of the radial basis function (RBF) neural network need to be improved. This paper proposes a new variable structure radial basis function (VS-RBF) with a fast learning rate, in order to solve the problem of structural optimization design and parameter learning algorithm for the radial basis function neural network. …”
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Chromaticity-Adaptive Generalized Spatial Modulation for MIMO VLC With Multi-Color LEDs by Ye Xiao, Yi-Jun Zhu

“…Therefore, the design algorithm of CA-GSM is derived with the optimal QLED selection pattern. …”
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A Hotspot Prediction Scheme Based on Ensemble Learning With Adaptive Beamforming for Virtual Small Cell in 5G Networks by Aws Majeed Ghalib Alawadi, Hadi Seyedarabi, Reza Afrouzian, Javad Musevi Niya

“…Effectively managing network congestion in 5G systems is crucial for ensuring seamless connectivity and optimal resource utilization. In this study, an operational scheme based on hotspot prediction for Virtual Small Cell (VSC) is presented, which aims to improve coverage, reduce delay and improve energy efficiency in 5G networks for congested locations. …”
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GSD-YOLO: A Lightweight Decoupled Wheat Scab Spore Detection Network Based on Yolov7-Tiny by Dongyan Zhang, Wenfeng Tao, Tao Cheng, Xingen Zhou, Gensheng Hu, Hongbo Qiao, Wei Guo, Ziheng Wang, Chunyan Gu

“…The experimental results show that the mAP of the proposed algorithm reaches 98.0%, which is 3.9 percentage points higher than that of the original model. …”
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Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…The results show that the combination of convolutional neural network to extract fault features and parameters to optimize the classification model structure of support vector machine can not only improve the diagnostic accuracy, but also have strong generalization performance.…”
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Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…We first propose a novel block-successive convex approximation algorithm based on a regularized model-fitting objective where the normal flows are modeled as low-rank tensors and anomalies as sparse. …”
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Efficiency Design of Traction Inverters Based on Deep Learning and TRIZ by LIAGN Kaiwei, JIAO Bi, LIU Yongjiang, LING Zhenjun, SU Li, XIE Haibo

“…In addition, this paper designs human-computer interaction software based on TRIZ-CRNN to improve the operation intelligence of computer aided innovation system and optimize the application feasibility of TRIZ-CRNN algorithm.…”
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Development of High Accuracy Classifier for the Speaker Recognition System by Raghad Tariq Al-Hassani, Dogu Cagdas Atilla, Çağatay Aydin

“…In order to enhance noise immunity, we proposed a single hidden layer feed-forward neural network (FFNN) tuned by an optimized particle swarm optimization (OPSO) algorithm. …”
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gfpop: An R Package for Univariate Graph-Constrained Change-Point Detection by Vincent Runge, Toby Dylan Hocking, Gaetano Romano, Fatemeh Afghah, Paul Fearnhead, Guillem Rigaill

“…Hocking et al. (2020) described a graph framework to encode many examples of such prior information and a generic algorithm to infer the optimal model parameters, but implemented the algorithm for just a single scenario. …”
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Evaluation and Analysis of Land Input-Output Comprehensive Benefit Based on Fuzzy Mathematics and Analytic Hierarchy Process by Xincheng Zhu, Yan Zhang, Yunzhi Hou, Minda Jiang

“…Then, based on the theory of fuzzy mathematics, the improved particle swarm optimization (PSO) algorithm is used to identify the fuzzy density value of the evaluation index. …”
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Prediction of Carbonate Reservoir Porosity Based on CNN-BiLSTM-Transformer by Yingqiang Qi, Shuiliang Luo, Song Tang, Jifu Ruan, Da Gao, Qianqian Liu, Sheng Li

“…Experimental results show that the porosity prediction model based on the CNN-BiLSTM-Transformer algorithm achieves lower average relative error and better prediction performance. …”
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Obstacle Avoidance Control of Autonomous Undersea Vehicle Based on DVFH+ in Ocean Current Environment by Zhongben ZHU, Jiahao ZHANG, Yifan XUE, Hongde QIN

“…Additionally, by considering the drift angle compensation in the real ocean current environment, the obstacle avoidance algorithm was optimized to improve its robustness and adaptability. …”
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Rock Fracture Monitoring Based on High-Precision Microseismic Event Location Using 3D Multiscale Waveform Inversion by Yi Wang, Xueyi Shang, Kang Peng, Rui Gao

“…Based on this initial location, the multiscale waveform inversion strategy (from coarse to fine grids) and the L-BFGS iteration optimization algorithm were separately jointly selected to improve wavefield modeling speed efficiency and iterative convergence rate. …”
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Two-Sided Matching on Comprehensive Transportation Network Emergency Vehicles’ Allocation by Kunwei Xie, Heying Xu, Hongxia Lv

“…Firstly, based on the needs of both parties involved in the matching, the satisfaction evaluation systems are constructed; with the goal of maximizing the weighted satisfaction of the affected areas and vehicles, the optimization model of the materials and emergency vehicles matching is established; then, an improved National Intern Matching Program (NIMP) algorithm is designed to solve the model, which is based on the k: 1 experimental pairing and updating ideas, and can take into account the capacity and destination constraints of vehicles in the matching process. …”
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An efficient approach for broadband sound absorption using periodic multi-layer solid inclusions in acoustic coatings. by Xiaogang Li, Peng Liu, Xilong Zhang, Xiaoyang Zhu, Hongbo Zhang

“…The optimized structure, featuring subwavelength thicknesses, has significantly improved its sound absorption performance across a wide frequency range spanning from 1780 Hz to 8890 Hz, covering over two octaves. …”
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Electric vehicle charging load prediction method based on multi-objective modal decomposition and NAHL neural network by GUO Xinzhe, WANG Yeqin, WANG Chao, WU Mingjiang, YANG Yan, ZHANG Chu

“…The improved NSGAII-LDSBX algorithm is used to optimize the parameters of VMD, decompose the signal into several subsequences, and reconstruct the subsequences through fuzzy entropy (FE). …”
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