Internet of Things Assisted Plant Disease Detection and Crop Management Using Deep Learning for Sustainable Agriculture by Eman A. Al-Shahari, Ghadah Aldehim, Mohammed Aljebreen, Jehad Saad Alqurni, Ahmed S. Salama, Sitelbanat Abdelbagi

“…Furthermore, the classification algorithm is implemented by using the recurrent spiking neural network (RSNN) model. …”
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To accurately predict lymph node metastasis in patients with mass-forming intrahepatic cholangiocarcinoma by using CT radiomics features of tumor habitat subregions by Pengyu Chen, Zhenwei Yang, Peigang Ning, Hao Yuan, Zuochao Qi, Qingshan Li, Bo Meng, Xianzhou Zhang, Haibo Yu

“…This model is expected to provide personalized decision support to clinicians and help to optimize treatment plans and improve patient outcomes.…”
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Notice of Violation of IEEE Publication Principles: Dynamic Embedding and Scheduling of Service Function Chains for Future SDN/NFV-Enabled Networks by Haotong Cao, Hongbo Zhu, Longxiang Yang

“…Subsequently, to remove the NP-hardness of the MILP model, a dynamic VNF embedding and scheduling algorithm is proposed. …”
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IoT Based Health Monitoring with Diet, Exercise and Calories recommendation Using Machine Learning by Muhammad Hassaan Naveed, Omar Bin Samin, Muhammad Bilal, Mustehsum Waseem

“…The study’s method ology includes utilizing a comprehensive dataset from Kaggle, separated into sets for testing and training, to develop and evaluate machine learning models. The Random Forest model demonstrated superior performance in precision, recall, F1-score, and R2 score metrics, making it the optimal choice for the recommender system. …”
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High‐Precision Prediction of Ionospheric TEC in the China Region Based on CMONOC High‐Resolution Data and an Auxiliary Attention Temporal Convolutional Network by Jianghe Chen, Pan Xiong, Haochen Wu, Xiaoran Zhang, Xuemin Zhang, Rongzi Chai, Ting Zhang, Kaixin Wang, Chaoyu Wang

“…At the data level, a non‐integrated spherical harmonic model and Differential Code Bias correction method are employed to significantly reduce interpolation errors and improve model accuracy. …”
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An Approach for Detecting Faulty Lines in a Small-Current, Grounded System Using Learning Spiking Neural P Systems with NLMS by Yangheng Hu, Yijin Wu, Qiang Yang, Yang Liu, Shunli Wang, Jianping Dong, Xiaohua Zeng, Dapeng Zhang

“…An adaptive learning mechanism was introduced to optimize the convergence and precision of the detection model. …”
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Research on Cognitive Radio Non-orthogonal Multiple Access System in 5G Communications Oriented to Ubiquitous Power Internet of Things by Rui SHE, Ningchi ZHANG, Yanru WANG, Dandan GUO, Wenjie MA, Hui LIU, Jie ZHANG

“…The closed expressions of spectrum access probability and throughput are derived; in order to further increase the accuracy of the classification results, an improved K-means algorithm is proposed. The alternate iterative algorithm is implemented to jointly optimize the detection time, node power and the number of user clusters such that the system throughput can be maximized eventually. …”
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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

“…In contrast, under larger and more complex problem instances, the proposed algorithm can achieve up to a 50% performance improvement over the benchmarks. …”
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Dose prediction of CyberKnife Monte Carlo plan for lung cancer patients based on deep learning: robust learning of variable beam configurations by Yuchao Miao, Jiwei Li, Ruigang Ge, Chuanbin Xie, Yaoying Liu, Gaolong Zhang, Mingchang Miao, Shouping Xu

“…We achieved approximately 99% for the PTV and generally more than 95% for the organs at risk (OARs) referred to the clinical planning dose in the gamma passing rates (3 mm/3%). Relative to the Mask model, the AB model exhibited more than 90% improvement in small voxels (p < 0.001). …”
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A Novel Nonlinear Adaptive Control Method for Longitudinal Speed Control for Four-Independent-Wheel Autonomous Vehicles by Jinhua Zhang, Zhenghao Chen, Jinshi Yu

“…Based on the design of the upper controller, an innovative optimized longitudinal force distribution strategy and the construction of a tire reverse longitudinal slip model are proposed, followed by the design of a fuzzy PID controller as the lower slip ratio controller to achieve precise whole-vehicle longitudinal speed tracking and improve overall control performance. …”
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The ensemble transform Schmidt–Kalman filter: A novel method to compensate for observation uncertainty due to unresolved scales by Zackary Bell, Sarah L. Dance, Joanne A. Waller

“…Observation error due to unresolved scales occurs when there is a difference in scales observed and modeled. To obtain an optimal estimate through data assimilation, the error due to unresolved scales must be accounted for in the algorithm. …”
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Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage by Yongqiang Zhang, Haijie Pang, Jinlong Ma, Guilei Ma, Xiaoming Zhang, Menghua Man

“…Methods: Therefore, this research constructs two types of spiking neural network models with LIF model as nodes: VGG-SNN and FCNN-SNN, and combines pruning algorithm to simulate network connection damage during the training process. …”
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AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis by João Paulo Costa, José Torres Farinha, Mateus Mendes, Jorge O. Estima

“…The incorporation of LSTM networks and swarm intelligence algorithms led to a significant improvement in predictive capabilities, allowing for the early detection of degradation patterns and timely intervention. …”
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Artificial Neural Network Framework for Hybrid Control and Monitoring in Turning Operations by Bogdan Felician Abaza, Vlad Gheorghita

“…This paper proposes a hybrid control and monitoring framework designed to enhance turning operations by integrating artificial neural networks (ANNs) for predictive modeling and adaptive recalibration. The system leverages machine learning (ML) to improve machining efficiency, tool longevity, and energy consumption optimization. …”
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Research on Concrete Crack and Depression Detection Method Based on Multi-Level Defect Fusion Segmentation Network by Zhaochen Yao, Yanjuan Li, Hao Fu, Jun Tian, Yang Zhou, Chee-Loong Chin, Chau-Khun Ma

“…Joint detection loss and segmentation loss are used for task co-optimization. On our self-constructed concrete defect dataset, MDFNet significantly outperforms the baseline model. …”
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Free-form型机床切齿优化（二）——混合进化遗传算法 by 张艳红, 郭九生, 王小椿

“…The algorithm integrates the improved genetic algorithm and projection on parameter line, being able to search global optimal solution effectively. …”
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Small Modular Reactor based on NuScale with Thorium base by Diego M. E. Gonçalves, Marcelo Vilela da Silva, C. J. C. M. R. da Cunha, Giovanni L. Stefani

“…The team applied a Particle Swarm Optimization (PSO) algorithm to find the best seed-to-blanket volume ratio, thereby maximizing U-233 production and achieving a self-sustaining fuel cycle. …”
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AMNED: An Efficient Framework for Spiking Neuron Coding in AirComp Federated Learning by Juncheng Ji, Chan-Tong Lam, Ke Wang, Benjamin K. Ng

“…This paper advances ACFL technologies by proposing the Adaptive Memristor Neuron Encoding-Decoding (AMNED) framework for AirComp Federated Learning (ACFL), enabling efficient, privacy-preserving model aggregation optimized for resource-constrained wireless environments. …”
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Stroke Risk Classification Using the Ensemble Learning Method of XGBoost and Random Forest by Gullam Almuzadid, Egia Rosi Subhiyakto

“…This study proposes a stroke risk classification model using ensemble learning that combines Random Forest and XGBoost algorithms. …”
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Artificial intelligence assisted wearable flexible sensors for sports: research progress in technology integration and application by Jie Wu, Zhiqi Mo, Xing Gao, Wanru Xin, Weiquan Shi, Jaeyoung Park

“…This article provides a comprehensive review of the latest advancements in artificial intelligence-assisted wearable flexible sensors for motion detection, focusing on the operational mechanisms, performance enhancements, and algorithm optimization of convolutional neural networks (CNN), temporal data modeling, multimodal fusion technology, and natural language generation. …”
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