Fourier Analysis of CMFD Method in Cylindrical Geometry by WEN Yuchen, HAO Chen, WANG Yizhen

“…The coarse mesh finite difference (CMFD) method has been widely adopted as an acceleration algorithm for neutron transport calculations, effectively reducing computational costs and improving convergence. …”

Integration of YOLOv9 Segmentation and Monocular Depth Estimation in Thermal Imaging for Prediction of Estrus in Sows Based on Pixel Intensity Analysis by Iyad Almadani, Aaron L. Robinson, Mohammed Abuhussein

“…Many researchers focus on improving reproductive health in sows and ensuring successful breeding by accurately identifying the optimal time of ovulation through estrus detection. …”
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Knowledge Discovery Using Clustering Methods in Medical Database: A Case Study for Reflux Disease by Fatma Rıdaouı, Yunus Doğan

“…In the tests, it was observed that the most successful algorithm in terms of the structure of the data was KMeans, and a set of remarkable 27 rules according to the optimal Sum of Square Error value was obtained.…”
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Prioritising explainable AI-driven recommendations with knowledge graphs and reinforcement learning by Neeraj Tiwary, Shahrul Azman Mohd Noah, Fariza Fauzi

“…A core innovation within XAIRec is the Product Prioritisation Score (PPS) algorithm, which ranks recommendations based on their user-specific relevance. …”
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Global air quality index prediction using integrated spatial observation data and geographics machine learning by Tania Septi Anggraini, Hitoshi Irie, Anjar Dimara Sakti, Ketut Wikantika

“…The GML considers geographical characteristics in the analysis by calculating the optimal bandwidth area in its algorithm. The study employs nine scenarios to identify which parameters significantly contribute to the model and determine the best parameter combinations. …”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashir, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…Feature selection is performed on such datasets to identify the optimal feature subset. The major goal of feature selection is to improve the accuracy by identifying a minimal feature subset. …”
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Lightweight deep learning system for automated bone age assessment in Chinese children: enhancing clinical efficiency and diagnostic accuracy by Pang Hai, Zhang Bin, Liu Kesheng, Li Cong, Xu Fei

“…This framework holds transformative potential for pediatric endocrinology and orthopedics by standardizing BAA, improving diagnostic equity, and optimizing resource use. …”
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An Enhanced Approach for Remaining Useful Life Prediction of Bearings Using Incomplete Lifecycle Data by Xunmeng An, Chao Zhang, Caiye Liu, Wentao Zhao

“…Accurately predicting the remaining useful life (RUL) of rolling bearings is crucial for ensuring optimal equipment operation and timely maintenance. …”
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Cost-Effective Multitask Active Learning in Wearable Sensor Systems by Asiful Arefeen, Hassan Ghasemzadeh

“…Multitask learning models provide benefits by reducing model complexity and improving accuracy by concurrently learning multiple tasks with shared representations. …”
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Integrating artificial intelligence into thermodynamics: A new paradigm for sustainable future by Marwan Al-Raeei

“…In addition, we examine the application of AI-driven optimization techniques, such as genetic algorithms and reinforcement learning, which have proven essential for improving energy efficiency and reliability across various industries. …”
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Time-Triggered Task Offloading Scheduling in TSN-Based Edge Computing Power Networks by Hongrui Nie, Yang Wu, Weifeng Zhu, Jinzuo Zhong, Hang Yang, Yu Zhou

“…Subsequently, we establish the correlation between tasks using Directed Acyclic Graph (DAG) and design a matching and load balancing-based task offloading algorithm (MLB-TOA). Moreover, we propose an efficient routing algorithm for task generation streams (TGS-RA) and an incremental task generation stream injection time planning algorithm (TGS-ITP) in time-sensitive networking. …”
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QoS Routing in Telecommunications Networks by N. I. Listopad, O. A. Lavshuk

“…With the transition to new generation networks, the issues of improving routing algorithms and protocols seem to be especially relevant. …”
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Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In addition, training on this benchmark dataset proposes an improved feeding intensity evaluation network, which achieves a good balance in prediction accuracy and parameter memory and offers the possibility of subsequent deployment of the model on mobile. …”
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A Novel Underwater Wireless Optical Communication Optical Receiver Decision Unit Strategy Based on a Convolutional Neural Network by Intesar F. El Ramley, Nada M. Bedaiwi, Yas Al-Hadeethi, Abeer Z. Barasheed, Saleha Al-Zhrani, Mingguang Chen

“…Our new CNN algorithm utilises the eye diagram (ED) image processing technique. …”
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A willingness-aware user recruitment strategy based on the task attributes in mobile crowdsensing by Yang Liu, Yong Li, Wei Cheng, Weiguang Wang, Junhua Yang

“…Finally, we use the greedy method to optimize the user recruitment for each task to select the most suitable users for the tasks. …”
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A novel seismic inversion method based on multiple attributes and machine learning for hydrocarbon reservoir prediction in Bohai Bay Basin, Eastern China by Zongbin Liu, Jianmin Zhu, Bo Tian, Rui Zhang, Yongheng Fu, Yuan Liu, Lixin Wang

“…GA helps CNNs to get an optimal solution in a fast speed. The results reveal that the model's sand thickness predictions closely match the actual measurements at wells, with a new horizontal well's alignment with the predicted output reaching an accuracy of 85.1%. …”
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Design of and Experiment with a Dual-Arm Apple Harvesting Robot System by Wenlei Huang, Zhonghua Miao, Tao Wu, Zhengwei Guo, Wenkai Han, Tao Li

“…Finally, to improve collaboration efficiency, a multi-arm task planning method based on a genetic algorithm is used to optimize the target harvesting sequence for each arm. …”
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Swin‐YOLOX for autonomous and accurate drone visual landing by Rongbin Chen, Ying Xu, Mohamad Sabri bin Sinal, Dongsheng Zhong, Xinru Li, Bo Li, Yadong Guo, Qingjia Luo

“…And finally, the RBN data batch normalization method is used to improve the performance of the model in extracting effective features from the data. …”
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A Matheuristic Approach Based on Variable Neighborhood Search for the Static Repositioning Problem in Station-Based Bike-Sharing Systems by Julio Mario Daza-Escorcia, David Álvarez-Martínez

“…To solve this problem, we propose a <i>matheuristic</i> based on a <i>variable neighborhood search</i> combined with several improving algorithms, including an <i>integer linear programming model</i> to optimize loading instructions. …”
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InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…To overcome these issues, we propose InvMOE, a novel fault detection algorithm with two core components: (1) invariant representation learning, which captures task-relevant features and mitigates background noise interference, and (2) multi-task training using a mixture of experts (MOE) framework to adaptively optimize feature learning across tasks and address label sparsity. …”
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