Gated recurrent deep learning approaches to revolutionizing English language learning for personalized instruction and effective instruction by Bo Sun

“…The study investigates the revolutionary possibilities of Gated Recurrent Neural Networks (GRNN) to improve ELL-tailored training. The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. …”
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“Bias Correction Method” for Regional Correction Experiment of Warm Season Rainstorm in Zhejiang by Chengyan Mao, Xin Pan, Haowen Li, Weibiao Li, Haoya Liu

“…The corrected forecasts are subsequently evaluated against the original model outputs. The key findings include: (1) Zhejiang Province is optimally divided into four regions characterized by similar precipitation patterns, which exhibit distinct regional features closely linked to the province’s topography and geomorphology. …”
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Hierarchically Federated Learning in Wireless Networks: D2D Consensus and Inter-Cell Aggregation by Jie Zhang, Li Chen, Yunfei Chen, Xiaohui Chen, Guo Wei

“…Based on the convergence analysis, we characterize the network topology of each cell, the communication interval of intra-cell consensus and inter-cell aggregation on the training performance. To further improve the performance of HDFL, we optimize the computation capacity selection and bandwidth allocation to minimize the training latency and energy overhead. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Compared with the CRF model, LSTM-CRF model,GRU-CRF model, BiLSTM-CRF model, CNN-CRF model, and Bert-CRF model, the F1-score values of the proposed model are improved by 27.42%, 18.78%, 23.62%, 13.25%, 14.88%, and 14.46%. …”
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Research on entity recognition and alignment of APT attack based on Bert and BiLSTM-CRF by Xiuzhang YANG, Guojun PENG, Zichuan LI, Yangqi LYU, Side LIU, Chenguang LI

“…Compared with the CRF model, LSTM-CRF model,GRU-CRF model, BiLSTM-CRF model, CNN-CRF model, and Bert-CRF model, the F1-score values of the proposed model are improved by 27.42%, 18.78%, 23.62%, 13.25%, 14.88%, and 14.46%. …”
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Evolutionary game-based cooperative strategy for effective capacity of multiple-input-multiple-output communications by Jianhua Liu, Jiadi Yu, Minglu Li, Luqun Li, Dazhi Li, Shigen Shen

“…Numerical results show that the proposed algorithm can effectively improve the quality of service for mobile two-dimensional multiple-input-multiple-output communication networks.…”
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Module Partition of Mechatronic Products Based on Core Part Hierarchical Clustering and Non-Core Part Association Analysis by Shuai Wang, Yi-Fei Song, Guang-Yu Zou, Jia-Xiang Man

“…Then, based on the core parts, the corresponding product design structural matrix (DSM) model is established. Secondly, the hierarchical clustering algorithm is used to obtain the module division scheme of different levels of mechatronic products, and the optimal modular scheme is obtained through an evaluation of modularity and a rationality analysis of module structure. …”
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Research on anode inlet pressure control strategy of PEMFC through hardware-in-the-loop test by Jing Zhang, Zhongkao Tan, Chengzhi Fan, Jingying Tan, Guoan Luo, Weiye Lu, Zhiqiang Liang, Cong Xu, Yixuan He, Xiaodong Wang, Zhongmin Wan

“…Through the HIL test, it is verified that the NLADRC algorithm is also applicable to the FCU. The model and control method proposed in this paper can be used to optimize the control of the hydrogen supply system and improve the dynamic performance of PEMFC.…”
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Urban Freight Management with Stochastic Time-Dependent Travel Times and Application to Large-Scale Transportation Networks by Shichao Sun, Zhengyu Duan, Dongyuan Yang

“…Based on that, the proposed STD-VRP model can be converted into solving a normal time-dependent VRP (TD-VRP), and algorithms for such TD-VRPs can also be introduced to obtain the solution. …”
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Identification of green leafhoppers (cicadellidae) in vineyards through an automatic image acquisition system from yellow sticky traps associated with deep-learning by Proença Maria da Conceição, Rebelo Maria Teresa, Valent Riccardo, Mateus Rebeca, Gaspar Pedro Diniz, Lopes Carlos Manuel, Franco José Carlos

“…The model’s architecture was optimized to handle variations in lighting conditions, angles, and orientations commonly found in field settings. …”
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A plug and play fuzzy mask extraction module for single image deraining by Mingdi Hu, Yao Song, Songxin Zhang, Zejian Xie, Bingyi Jing

“…Comprehensive experiments show that combining the rain removal network with our proposed model not only improves the rain removal effect of the algorithm, but also gives clearer background details of the image. …”
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A XGBoost-Based Prediction Method for Meat Sheep Transport Stress Using Wearable Photoelectric Sensors and Infrared Thermometry by Ruiqin Ma, Runqing Chen, Buwen Liang, Xinxing Li

“…The results show that SVC and GBDT algorithms are more effective and the overall model classification accuracy reached 86.44% and 91.53%. …”
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Electromagnetic Transient Parallel Simulation of Large-Scale New Energy Grid Connection Based on PSCAD/EMTDC by Bin CAO, Liqiang WANG, Yongfei ZHAO, Xiuqi ZHANG

“…The simulation results show that the cluster parallel technology can effectively improve the simulation efficiency of the new energy grid-connected electromagnetic transient model. …”
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Method of continuous generation grinding tooth surface modification based on electronic gearbox superimposed high-order motion by HAN Jiang, RUI Xiaoyu, TIAN Xiaoqing, YOU Tongfei, LI Guanghui, XIA Lian

“…Using the normal deviation between the standard involute gear surface and the actual machined gear surface grid points as the evaluation criterion, the Levenberg-Marquardt algorithm was used to optimize the polynomial coefficients of the motion functions of each feed axis of the grinding wheel. …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. Hyperparameter optimization made using the Differential Evolution (DE) method improved the performance of models. …”
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Selective Cleaning Enhances Machine Learning Accuracy for Drug Repurposing: Multiscale Discovery of MDM2 Inhibitors by Mohammad Firdaus Akmal, Ming Wah Wong

“…The optimized model was integrated with structure-based virtual screening via molecular docking to prioritize repurposing candidate compounds. …”
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Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We compare our algorithm with existing algorithms and demonstrate the improved EE UAV relaying communication for our model.…”
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INFLUENCE OF MAIN GEAR RATIO ON CAR FUEL EFFICIENCY IN THE DRIVE CYCLE by S. A. Gorozhankin, N. V. Savenkov, V. V. Ponyakin

“…The article presents the improvement efficiency of fuel and economic properties of the vehicle in WLTC driving cycle by means of the main gear ratio changing. …”
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Artificial intelligence based classification and prediction of medical imaging using a novel framework of inverted and self-attention deep neural network architecture by Junaid Aftab, Muhammad Attique Khan, Sobia Arshad, Shams ur Rehman, Dina Abdulaziz AlHammadi, Yunyoung Nam

“…The extracted features are fused using a modified serial fusion with a strong correlation approach. An optimization algorithm- slap swarm controlled standard Error mean (SScSEM) has been employed, and the best features that passed to the shallow wide neural network (SWNN) classifier for the final classification have been selected. …”
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