Online Behavior Analysis-Based Student Profile for Intelligent E-Learning by Kun Liang, Yiying Zhang, Yeshen He, Yilin Zhou, Wei Tan, Xiaoxia Li

“…According to the E-Learning resources and learner behaviors, we also present the intelligent guide model to guide both E-Learning platform and learners to improve learning things. …”
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Early Prediction of Cardio Vascular Disease (CVD) from Diabetic Retinopathy using improvised deep Belief Network (I-DBN) with Optimum feature selection technique by T. K. Revathi, B. Sathiyabhama, S Kaliraj, Vidhushavarshini Sureshkumar

“…We used Principal Component Analysis (PCA) and Particle Swarm Optimization (PSO) algorithm for feature extraction and selection respectively. …”
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Digital Twin and Data-Driven Remaining Useful Life Prediction of Gearbox by Quanbo Lu, Mei Li, Xiaojuan Huang

“…This theoretical RUL is then integrated with actual RUL data derived from experimental observations using a SegRNN model. To further improve prediction accuracy, the paper employs the Central Particle Swarm Optimization algorithm to merge both theoretical and actual RUL values. …”
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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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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…The first scenario used the original dataset, the second used a merged version of the dataset, and the last scenario used a hierarchical architecture model. Additionally, a custom ranking algorithm was designed to identify the most suitable recipients. …”
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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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Travel Time Prediction of Urban Agglomeration Significance Channel: A Case Study on the Cross-Hangzhou Bay Channel by Wang Yu, Hu Xiaowei, Cui Shu, Rao Zonghao

“…The case study on the Hangzhou Bay Bridge and Jiashao Bridge demonstrates that the proposed model significantly improves prediction accuracy compared to traditional methods. …”
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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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A METHOD FOR SOLVING THE CANONICAL PROBLEM OF TRANSPORT LOGISTICS IN CONDITIONS OF UNCERTAINTY by Lev Raskin, Yurii Parfeniuk, Larysa Sukhomlyn, Mykhailo Kravtsov, Leonid Surkov

“…Development of an accurate algorithm for solving this problem according to the probabilistic criterion in the assumption of the random nature of transportation costs has been done. …”
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Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Traditional deep learning (DL) models and decision tree (DT)-based algorithms have been widely employed for this purpose. …”
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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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