Research on Book Recommendation Integrating Book Category Features and User Attribute Information by Yan Chen, Eric Blancaflor, Mideth Abisado

“…Aiming at the problem of poor recommendation effect caused by data sparsity in traditional collaborative filtering algorithm in book recommendation, this study proposes a personalized recommendation model (BCF-UAI) that combines book category features and user attribute information, aiming to improve the accuracy and generalization ability of the recommendation system. …”
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Hunting Stability Enhancement of a Train Bogie Employing Inerter-Based Suspension Mechanism by Yong Wang, Chenyang Hong, Haodong Meng

“…The structural parameter analysis of inerter-based suspension mechanism is conducted, and the structural parameters are optimized using the nondominated sorting whale optimization algorithm (NSWOA). …”
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Two-stage resilience enhancement method for integrated electricity-gas systems through linepack and mobile compressors by Chao Qin, Yongxue Wang, Shuaihu Ye

“…The proposed method is reformulated into a mixed-integer second-order cone programming model using second-order cone relaxation. The progressive hedging algorithm is employed to further improve the solution efficiency. …”
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A New Hybrid Reinforcement Learning with Artificial Potential Field Method for UAV Target Search by Fang Jin, Zhihao Ye, Mengxue Li, Han Xiao, Weiliang Zeng, Long Wen

“…Specifically, the SAC-APF hybrid framework achieves a 161% improvement in success rate compared to the baseline SAC model, increasing from 0.282 to 0.736 in obstacle scenarios.…”
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Protein docking by the underestimation of free energy funnels in the space of encounter complexes. by Yang Shen, Ioannis Ch Paschalidis, Pirooz Vakili, Sandor Vajda

“…This algorithm explores the free energy surface spanned by encounter complexes that correspond to local free energy minima and shows similarity to the model of macromolecular association that proceeds through a series of collisions. …”
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Secret key generation for reconfigurable intelligent surface‐assisted MISO multi‐user system by Kexin Liu, Mingliang Li, Kaizhi Huang, Zheng Wan, Qinlong Li, Xiaoli Sun, Xiaoming Xu, Liang Jin

“…Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. …”
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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

“…SHAP analysis identified bowel peristalsis, C-reactive protein, albumin, bowel thickness, and procalcitonin as the most influential predictors. Decision curve analysis demonstrated a positive relative net benefit of the USPN model compared to the US and serological models in the validation set.ConclusionA machine learning model integrating ultrasound and serological markers significantly improves the prediction of NEC in neonates compared to single-modality approaches. …”
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Integrated Cloud-Twin Synchronization for Supply Chain 5.0 by Divya Sasi Latha, Tartat Mokkhamakkul

“…This study introduces a cloud-based twin optimization model for Supply Chain 5.0, validated through genetic algorithm (GA) simulations. …”
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Image acquisition technology for unmanned aerial vehicles based on YOLO - Illustrated by the case of wind turbine blade inspection by Zhenjun Dai

“…For this purpose, the study aims to optimize the You Only Look Once (YOLO) processing algorithm for drone images to improve the detection efficiency. …”
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5G-oriented information sharing mechanism within D2D clusters by Shaomin WANG, Bin ZHOU

“…Device-to-Device（D2D）communication is an important technology in 5G network.It helps to improve the transmission efficiency of data dissemination services.However,due to the extra signaling overhead caused by D2D communications,currently most of enhanced-multicast solutions cannot solve the contradiction between high-efficient data transmission and low-efficient signaling procedure,so as to reduce the overall performance gain.An intra-cluster D2D information sharing algorithm based on matrix analysis which includes centralized and distributed modes was proposed.The proposed algorithm could significantly reduce D2D retransmission times in clusters by adaptively selecting the optimal transmitters and data packets for D2D multicast retransmission,achieving the aim of reducing signaling overhead and transmission delay.…”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…Enhancing data quality, refining feature selection, and using advanced modeling techniques are crucial for improving predictive capabilities. …”
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Predicting Employee Turnover Using Machine Learning Techniques by Adil Benabou, Fatima Touhami, My Abdelouahed Sabri

“…This study aims to identify the most effective machine learning model for predicting employee attrition, thereby providing organizations with a reliable tool to anticipate turnover and implement proactive retention strategies.Objective: This study aims to address the challenge of employee attrition by applying machine learning techniques to provide predictive insights that can improve retention strategies.Methods: Nine machine learning algorithms are applied to a dataset of 1,470 employee records. …”
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A Method for Enhancing the Traffic Situation Awareness of Vessel Traffic Service Operators by Identifying High Risk Ships in Complex Navigation Conditions by Lei Zhang, Jiahao Ge, Floris Goerlandt, Lei Du, Tuowei Chen, Tingting Gu, Langxiong Gan, Xiaobin Li

“…First, the K-means clustering algorithm is improved using the Whale Optimization Algorithm (WOA) to adaptively cluster ships within a waterway, segmenting the traffic in the area into multiple ship clusters. …”
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UAV-Assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis by Ruslan Zhagypar, Nour Kouzayha, Hesham ElSawy, Hayssam Dahrouj, Tareq Y. Al-Naffouri

“…While applicable to terrestrial base stations (BSs), the proposed algorithm relies on UAVs for local model aggregation thanks to their ability to enhance wireless channels with lower latency and improved coverage. …”
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Composing problem solvers for simulation experimentation: a case study on steady state estimation. by Stefan Leye, Roland Ewald, Adelinde M Uhrmacher

“…To support those users, we propose a general scheme to aggregate such algorithms to so-called synthetic problem solvers, which exploit algorithm differences to improve overall performance. …”
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A Study on Path Planning for Curved Surface UV Printing Robots Based on Reinforcement Learning by Jie Liu, Xianxin Lin, Chengqiang Huang, Zelong Cai, Zhenyong Liu, Minsheng Chen, Zhicong Li

“…Experimental results show that the proposed method outperforms traditional path planning methods, as well as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Verification of the method for classifying the technical state of a turboshaft engine fuel regulator in the space of operational process parameters under factory test conditions by Ihor Ohanian, Sergiy Yepifanov

“…Recommendations for further improvement of the method include using expert systems and developing effective model identification algorithms. …”
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Intra-day dispatch method via deep reinforcement learning based on pre-training and expert knowledge by Yanbo Chen, Qintao Du, Huayu Dong, Tao Huang, Jiahao Ma, Zitao Xu, Zhihao Wang

“…In recent years, due to high self-learning and self-optimization ability, reinforcement learning has emerged in the field of economic dispatch, which can solve model-free dynamic programming problems that cannot be effectively solved by traditional optimization methods. …”
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Personalised context-aware re-ranking in recommender system by Xiangyong Liu, Guojun Wang, Md Zakirul Alam Bhuiyan

“…However, contextual factors significantly affect user behaviour, especially in the Internet of Things (IoT), which brings difficulties to modelling user preferences. In this paper, we propose a personalised context-aware re-ranking algorithm (p-CAR) in IoT. …”
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A Knowledge Graph-Based Framework for Smart Home Device Action Recommendation and Demand Response by Wenzhi Chen, Hongjian Sun, Minglei You, Jing Jiang, Marco Rivera

“…Firstly, a household device action recommendation algorithm is proposed that improves the knowledge graph attention algorithm to make accurate household appliance recommendations. …”
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