Secure beamforming design for IRS-assisted SWIPT Internet of things system by Zhengyu ZHU, Jinlei XU, Gangcan SUN, Ning WANG, Wanming HAO

“…In order to meet the new requirements of intelligent signal processing deployment and physical layer security for green interconnection of things, a design method of secure beamforming was proposed to solve the problem of the shortage of sustainable energy supply in the information and energy transmission at the same time Internet of things (IoT) system assisted by intelligent reflecting surface (IRS).Considering the constraints of secrecy rate, transmit power and IRS reflection phase shift, the optimization problem was modeled as a non-convex quadratic programming problem with quadratic constraints, aiming at maximizing the acquisition power of energy collector, and jointly optimizing the base station transmit beamforming matrix, jammer covariance matrix and IRS phase shift.The non-convex quadratic problem was transformed into an equivalent convex problem by using the relaxation variable, semidefinite relaxation method, auxiliary variable and sequence parameter convex approximation method, and an alternative iterative optimization algorithm was proposed to obtain the feasible solution of the original problem.Simulation results show that the proposed algorithm can converge quickly and improve performance effectively compared with the benchmark scheme.…”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…We propose a dual-stream neural network architecture that simultaneously models students’ knowledge states and cognitive load levels to optimize learning trajectories. …”
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Sound-Based Unsupervised Fault Diagnosis of Industrial Equipment Considering Environmental Noise by Jeong-Geun Lee, Kwang Sik Kim, Jang Hyun Lee

“…In particular, by adapting the model learned in the source domain to the target domain and considering the domain differences based on signal-to-noise ratio, high diagnostic accuracy was maintained regardless of the noise levels. …”
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Application of time series database technology in coal mine safety monitoring system by Hongliang ZHANG

“…A dynamic time sharding storage strategy is proposed for 2 Hz high-frequency data streams, combined with an improved run length encoding compression algorithm (RLE-X), to achieve a stable write throughput of ≥ 1 000 data streams per second and a storage space compression rate of over 85%. …”
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Stepwise Corrected Attention Registration Network for Preoperative and Follow-Up Magnetic Resonance Imaging of Glioma Patients by Yuefei Feng, Yao Zheng, Dong Huang, Jie Wei, Tianci Liu, Yinyan Wang, Yang Liu

“…This methodology leverages preoperative and follow-up MRI scans as fixed images and moving images, respectively, and employs a multi-level registration strategy that establishes a precise and holistic correspondence between images, from coarse to fine. Furthermore, our model introduces a corrected attention module into the multi-level registration network that can generate an attention map at the local level through the deformation fields of the upper-level registration network and pathological areas of preoperative images segmented by a mature algorithm in BraTS, serving to strengthen the registration accuracy of non-correspondence areas. …”
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Soybean–Corn Seedling Crop Row Detection for Agricultural Autonomous Navigation Based on GD-YOLOv10n-Seg by Tao Sun, Feixiang Le, Chen Cai, Yongkui Jin, Xinyu Xue, Longfei Cui

“…The experimental results showed that the improved model performed better in MPA and MIoU, and the model size was reduced by 18.3%. …”
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Ensemble Methods for Parameter Estimation of WRF‐Hydro by Arezoo RafieeiNasab, Michael N. Fienen, Nina Omani, Ishita Srivastava, Aubrey L. Dugger

“…Results show a large improvement in the model performance. In summary, our study demonstrates the efficacy of employing iES alongside differential weighting of observations, highlighting its potential to enhance hydrological model parameter estimation.…”
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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…Leveraging deep learning, this research accurately identifies features of abnormal behavior from the HAJJv2 dataset, specifically curated and annotated for the Hajj context. Optimization of the YOLOv9 algorithm for this scenario demonstrated superior performance metrics (mean Average Precision (mAP@0.5), Recall, and Precision) when compared with its predecessors (YOLOv4, YOLOv5, YOLOv7, and YOLOv8), highlighting significant improvements in detection accuracy and real-time applicability. …”
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Hybrid feedback control of PMSG-based WECS with multilevel flying-capacitor inverter enhanced by fractional order extremum seeking by Younes El Khlif, Abdelmounime El Magri, Rachid Lajouad, Omar Bouattane

“…Additionally, a fractional-order extremum seeking control (FOESC) algorithm for Maximum Power Point Tracking (MPPT) is introduced, which optimizes power capture by adjusting turbine speed from the DC side without requiring a detailed system model (model-free approach). …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…In order to further enhance the model's generalization performance, an image diagnosis algorithm was introduced before signal recognition, which generates warnings for complex conditions, such as overexposure and backlighting. …”
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Secure Latency-Aware Task Offloading Using Federated Learning and Zero Trust in Edge Computing for IoMT by Waleed Almuseelem

“…Moreover, this algorithm determines the optimal offloading strategy based on the global model while considering trustworthiness, the heterogeneous nature of tasks, resource availability, and latency. …”
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Predicting Trip Duration and Distance in Bike-Sharing Systems Using Dynamic Time Warping by Ahmed Ali, Ahmad Salah, Mahmoud Bekhit, Ahmed Fathalla

“…These two contributions of the proposed approach complement existing prediction models for rentals and returns, providing a comprehensive solution for BSS optimization. …”
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Research on Electric Spot Trading of Electric Vehicles Based on Block Chain by ZHANG Zhening, ZHANG Xinyu, GONG Gangjun

“…Finally,by designing intelligent contract, the optimization process of trading scheme was validated by a genetic algorithm.The simulation results show that through the efficient operation of the smart contract of block chain, the formulation of the optimal trading scheme to meet the objectives of multiple participants is achieved, which can provide a reference for improving the safety, reliability and efficient coordination of the electric vehicle charging market.…”
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Distributed Photovoltaic Distribution Voltage Prediction Based on eXtreme Gradient Boosting and Time Convolutional Networks by Fang Yuan, Yong Lu, Zhi Xie, Shenxiang Dai

“…Then, the model is improved and optimized using residual module with bottle sea sheath algorithm. …”
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Research on ionospheric parameters prediction based on deep learning by Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG

“…For ionospheric parameter prediction, the short-term and daily mean value prediction of ionospheric parameters was established by long short-term memory (LSTM) predictive neural network modeling.Two methods of point-by-point prediction and sequence prediction were utilized.Furthermore, in order to predict the hourly and daily changes of ionospheric parameters, the proposed scheme was optimized by multidimensional prediction and empirical mode decomposition (EMD) algorithm.Finally, the feasibility of the proposed optimization algorithm in improving the prediction accuracy of ionospheric parameters is verified.…”
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Research on RF Intensity Temperature Sensing based on 1D-CNN by DING Meiqi, GUI Lin, WANG Ziyi, SHANG Disen, QIAN Min, LI Qiankun

“…The model is trained with the training set data and validated with the test set data to optimize the model parameters for optimal performance. …”
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P-Band PolInSAR Sub-Canopy Terrain Retrieval in Tropical Forests Using Forest Height-to-Unpenetrated Depth Mapping by Chuanjun Wu, Jiali Hou, Peng Shen, Sai Wang, Gang Chen, Lu Zhang

“…A nonlinear iterative optimization algorithm is then employed to estimate forest height, from which a fundamental mapping between forest height and unpenetrated depth is established. …”
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Air-ground collaborative multi-source orbital integrated detection system: Combining 3D imaging and intrusion recognition. by Mengyuan Yan, Xingyu Yang, Wei Gao, Lifan Rong, Shengbo Li, Yuan Xiong

“…The system employs a lightweight rail inspection vehicle equipped with dual LiDARs and an Astro camera, synchronized with an unmanned aerial vehicle (UAV) carrying industrial-grade LiDAR. We propose an improved LiDAR odometry and mapping with sliding window (LOAM-SLAM) algorithm enables real-time dynamic mapping, while an optimized iterative closest point (ICP) algorithm achieves high-precision point cloud registration and colorization. …”
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The Air Transportation System as a Subsystem of Modern Communication Space: Analysis Based on Transfer Entropy Graphs by Sagit Valeev, Natalya Kondratyeva

“…New technologies in aviation improve the flight performance of airliners and reduce the costs of transporting passengers. …”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…This study investigates the application effectiveness of deep learning-based object detection technology in forest fire smoke recognition by using the YOLOv11x algorithm to develop an efficient fire detection model. …”
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