Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation by Amirreza Kandiri, Ramin Ghiasi, Maria Nogal, Rui Teixeira

“…Results show that OA2DD improves the convergence curve and reduces the number of selected features by up to 50 %, leading to a 56 % reduction in computational costs. …”
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Handover Strategy for LEO Satellite Networks Using Bipartite Graph and Hysteresis Margin by Sahar Eydian, Maryam Hosseini, Gunes Karabulut Kurt

“…The proposed approach utilizes the Kuhn-Munkres (KM) algorithm to achieve optimal matching with maximum weight, thereby ensuring efficient load distribution and high-quality communication. …”
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Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Future research directions of UWB radar personnel localization technology for mine rescue operations are proposed: ① optimizing the UWB radar localization system by constructing cross-modal information fusion models and developing highly adaptive signal processing methods to enhance the system's adaptability to post-mining disaster environments; ② improving the applicability of combined static and dynamic target localization by developing hybrid localization algorithms that integrate Bayesian networks or deep belief networks to fuse static and dynamic target features and establishing state-switching-based comprehensive models; ③ improving UWB radar echo processing algorithms, combining adaptive beamforming technology, Multiple Input Multiple Output (MIMO) technology, and optimized K-means++ or entropy-based hierarchical analysis algorithms, effectively distinguishing multi-target position information, and validating their adaptability and reliability in complex environments through extensive simulation experiments.…”
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Advancing Agricultural Machinery Maintenance: Deep Learning-Enabled Motor Fault Diagnosis by Xusong Bai, Qian Chen, Xiangjin Song, Weihang Hong

“…This article further discusses future research directions, such as optimizing DL models for real-time processing, improving robustness under varying agricultural conditions, and developing user-friendly interfaces for farmers and technicians. …”
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Collaborative multiview time series modeling for vehicle maintenance demand prediction by Fanghua Chen, Deguang Shang, Gang Zhou, Ke Ye, Fujie Ren, Guofang Wu

“…Abstract Accurate prediction of vehicle maintenance demands is crucial for sustaining vehicle use, optimizing performance, and minimizing ownership costs. …”
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Computing Non-Dominated Flexible Skylines in Vertically Distributed Datasets with No Random Access by Davide Martinenghi

“…However, the latter kind of access is sometimes too costly to be feasible, and algorithms need to be designed for the so-called “no random access” (NRA) scenario. …”
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The authors would like to thank the staff of the Organisation of Transportation and Transport Management Department by B. S. Trofimov, I. S. Trofimova

“…To plan the work of a lorry, taking into account changes in its design, it is required to use improved methods for optimizing the planning of the work of a freight motor transport enterprise, which is the relationship of activities for the transportation of goods, maintenance and current repair. …”
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Enhancing phase change thermal energy storage material properties prediction with digital technologies by Minghao Yu, Jing Liu, Cheng Chen, Mingyue Li

“…IntroductionIn the field of materials science, the prediction of material properties plays a critical role in designing new materials and optimizing existing ones. Traditional experimental approaches, while effective, are resource-intensive and time-consuming, often requiring extensive trial-and-error methods. …”
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Novel method for robust bilateral filtering point cloud denoising by Huan Yang, Wei Wang, Yue Wang, Peng Wang

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Automated Body Condition Scoring in Dairy Cows Using 2D Imaging and Deep Learning by Reagan Lewis, Teun Kostermans, Jan Wilhelm Brovold, Talha Laique, Marko Ocepek

“…The study recommends improvements in algorithmic feature extraction, dataset expansion, and multi-view integration to enhance accuracy. …”
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The impact of artificial intelligence on the economic productivity of enterprises by Šović Milena, Brkić Ivana

“…It also analyses the challenges of implementing AI technology, such as ethical concerns, data privacy, and integration costs. The research findings provide insight into best practices and guidelines for the optimal use of AI in the business sector, with the aim of improving business performance and ensuring long-term business sustainability.…”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…As a result, various ground-based measurement techniques have been developed to sample BVOC emissions at multiple scales, from the leaf level to regional and global scales.However, current BVOC measurements are often limited in space and time, as generating a fine-grained map of BVOC emissions over a large region is costly and time-consuming. Consequently, many existing BVOC emission maps may not be fully suitable for reliable atmospheric, climate, and forecasting model simulations.My research aims to explore and assess the use of novel AI-based algorithms to improve the spatiotemporal modeling of BVOC emissions. …”
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Analysis of Energy Sustainability and Problems of Technological Process of Primary Aluminum Production by Yury Valeryevich Ilyushin, Egor Andreevich Boronko

“…In this work, a methodological analysis of modern theoretical and numerical methods for studying MHDS was carried out, and approaches to optimizing magnetic fields and control algorithms aimed at stabilizing the process and reducing energy costs were considered. …”
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Integrating machine learning and reliability analysis: A novel approach to predicting heavy metal removal efficiency using biochar by Mohammad Sadegh Barkhordari, Chongchong Qi

“…This research introduces an advanced machine learning (ML) framework, utilizing deep forest (DF) algorithms, to predict and optimize the efficiency HM removal through biochar applications. …”
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Predicting anemia management in dialysis patients using open-source machine learning libraries by Takahiro Inoue, Norio Hanafusa, Yuki Kawaguchi, Ken Tsuchiya

“…Machine learning (ML) has shown potential in optimizing anemia management by predicting Hb levels and reducing ESA usage, though clinical implementation remains limited. …”
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Enhancing Reliability in Redundant Homogeneous Sensor Arrays with Self-X and Multidimensional Mapping by Elena Gerken, Andreas König

“…Mechanical defects and sensor failures can substantially undermine the reliability of low-cost sensors, especially in applications where measurement inaccuracies or malfunctions may lead to critical outcomes, including system control disruptions, emergency scenarios, or safety hazards. …”
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Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…We also present a method to optimize kernels based on a complete binary tree in arbitrary triangular meshes, improving performance. …”
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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

“…Although the deep learning-based fish feeding intensity assessment model has higher recognition accuracy and better robustness, the conventional differentiation of feeding intensity usually relies on manual experience to divide the feeding intensity dataset, which is subjective and uncertain, and the annotation is observed by the aquaculture experienced personnel to increase the labor and time cost. In order to solve these problems, this study constructs a benchmark dataset of the feeding intensity of pearl gentian groupers in a factory circulating water environment, which is divided into feeding fish groups and fish aggregation areas by training Unet semantic segmentation network and compares standard clustering algorithms through clustering evaluation indexes to maximally select the optimal clustering method and the number of clusters that are suitable for this paper's dataset. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. The YOLO (You Only Look Once) neural network has significantly improved fruit detection through image processing and has automated several related tasks. …”
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AI-Driven Advancements in Orthodontics for Precision and Patient Outcomes by David B. Olawade, Navami Leena, Eghosasere Egbon, Jeniya Rai, Aysha P. E. K. Mohammed, Bankole I. Oladapo, Stergios Boussios

“…While AI offers tremendous potential, challenges remain in areas such as data privacy, algorithmic bias, and the cost of adopting AI technologies. …”
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