Weighted determination algoritm of boundary pixels by D. V. Zaerko, V. A. Lipnitski

“…While working with digital noise reduction techniques, which are based on theory of convolution matrix and used convolution operation, it necessary to use algorithms to bypass boundary pixels in the image pixel matrix. …”
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Developing an advanced safety device for bridge-type cranes by A. N. Nazarov, S. D. Ivanov

“…The description of these algorithms in relation to cranes equipped with frequency control system is given. …”
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Comparison of machine learning methods for estimating case fatality ratios: An Ebola outbreak simulation study. by Alpha Forna, Ilaria Dorigatti, Pierre Nouvellet, Christl A Donnelly

“…<h4>Background</h4>Machine learning (ML) algorithms are now increasingly used in infectious disease epidemiology. …”
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Multi-level data fusion enables collaborative dynamics analysis in team sports using wearable sensor networks by Zi Zhuo Wang, Xiaoyu Xia, Qiaonan Chen

“…The developed collaborative dynamics indicator system revealed that temporal coordination parameters strongly correlate with team performance (r = 0.73), while four key metrics predict match outcomes with 73.6% accuracy. This methodology provides coaches and analysts with objective tools for quantifying previously subjective aspects of team coordination.…”
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An Enhanced Machine Learning Framework for Type 2 Diabetes Classification Using Imbalanced Data with Missing Values by Kumarmangal Roy, Muneer Ahmad, Kinza Waqar, Kirthanaah Priyaah, Jamel Nebhen, Sultan S Alshamrani, Muhammad Ahsan Raza, Ihsan Ali

“…This research proposes developing a predictive model that can achieve a high classification accuracy of type 2 diabetes. …”
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An In-Depth Tutorial on BJTU-RAO Bogie Datasets for Fault Diagnosis by Yong Qin, Yiran Wang, Zhaojun Steven Li, Biao Wang, Ao Ding, Chengcheng Wang, Yuanjing Qin, Yang Wang

“…Train fault diagnosis, predictive maintenance, and algorithms evaluation become crucial to ensure operational safety. …”
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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“…In terms of disease prediction, one study had an area under the curve of 0.790 for cataract surgery risk prediction. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…Specifically, the proposed MAPPO-based scheduling achieved a total electricity cost reduction of 14.68% compared to the No-ESS case and achieved 3.56% greater cost savings than other baseline reinforcement learning algorithms.…”
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GPU Accelerated Trilateral Filter for MR Image Restoration by Suthir Sriram, Nivethitha Vijayaraj, T. Srilekha, M. Praveena, Thangavel Murugan

“…MRI serves as a non-invasive imaging tool to diagnose brain diseases yet the noise produced during its acquisition phase degrades image quality so that diagnosis accuracy suffers. Reduction of noise becomes essential for both clinical diagnostic procedures and computer-assisted medical analysis practices which require tissue classification and registration and segmentation algorithms. …”
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Advancements in epilepsy classification: Current trends and future directions by Rajani Rai B, Karunakara Rai B, Mamatha A S, Kavitha Sooda

“…The paper concludes with the discussion on potential future research directions, especially in areas of multimodal data integration and real-time seizure prediction, and emphasizes the potential for AI-driven personalized epilepsy treatment techniques.…”
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AI may enable robots to make a clinical impact in total knee arthroplasty, where navigation has not! by Michael T. Hirschmann, Rüdiger vonEisenhart‐Rothe, Heiko Graichen, Stefano Zaffagnini

“…Through the utilization of real‐time data and prediction algorithms, artificial intelligence‐guided robots have the potential to overcome the limits of conventional approaches, thereby establishing a new benchmark for TKA.…”
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Prevalence estimates of trafficking in persons using statistical definitions: a cross-sectional high-risk community survey in Cape Town, South Africa by Rumi Kato Price, Annah K Bender, Floriana H Milazzo, Edna G. Rich, Nicolette V. Roman, Sheldon X Zhang, Erica L Koegler

“…Several screener items were shown less predictive of the PRIF statistical definition criteria than others.Conclusions Prevalence estimates of probable TIP were higher than those reported elsewhere. …”
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Applied of Classification Technique in Data Mining For Credit Scoring by Heriyanto Heriyanto, Ika Kurniawati, Fachri Amsury, Muhammad Rizki Fahdia, Irwansyah Saputra, Nanang Ruhyana, Asrul

“…The best prediction results are nave Bayes with an accuracy of 95.95 % and an AUC of 0.974. …”
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Applications of Machine Learning Technologies for Feedstock Yield Estimation of Ethanol Production by Hyeongjun Lim, Sojung Kim

“…As a result, this study will help researchers and engineers predict feedstock yields using various machine learning techniques, and contribute to efficient and stable biofuel production and supply chain design based on accurate predictions of feedstocks.…”
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Machine learning-based prognostic modeling integrating PANoptosis in head and neck squamous cell carcinoma by Chen Li, Jiajing Lu, Jialin Zhu, Tao Zhou, Qijie Shen, Bikun Huang, Qingsong Li

“…Conclusions The PANoptosis-based prognostic model offers strong predictive value for HNSCC and has potential applications in personalized treatment approaches. …”
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Delivering data: A real-world dataset for last-mile delivery optimizationZenodo by Anna Vrani, Savvas D. Apostolidis, Athanasios Ch. Kapoutsis, Elias B. Kosmatopoulos

“…The collected matrices were processed and structured for direct use in VRP algorithms.The dataset offers substantial reuse potential by serving as a benchmark for evaluating VRP algorithms, enabling the comparison of optimization methods based on real-world logistics problems. …”
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Machine Learning-Based X-Ray Projection Interpolation for Improved 4D-CBCT Reconstruction by Jayroop Ramesh, Donthi Sankalpa, Rohan Mitra, Salam Dhou

“…Moreover, a novel regression predictive modeling approach is also proposed to achieve the same objective. …”
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A Wind Power Density Forecasting Model Based on RF-DBO-VMD Feature Selection and BiGRU Optimized by the Attention Mechanism by Bixiong Luo, Peng Zuo, Lijun Zhu, Wei Hua

“…First, critical physical features relevant to WPD are identified using random forest (RF), effectively eliminating data redundancy and enhancing prediction efficiency. Second, the variational mode decomposition (VMD) parameters are optimized via the dung beetle optimizer (DBO) algorithm to extract independent intrinsic mode functions (IMFs), which, alongside the original data, serve as temporal feature inputs. …”
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Multistation Wind Speed Forecasting Based on Dynamic Spatiotemporal Graph Convolutional Networks by Jianhong Gan, Runqing Kang, Xun Deng, Chentao Mao, Zhibin Li, Peiyang Wei, Chunjiang Wu, Tongli He

“…Finally, the particle swarm optimization algorithm is used for hyperparameter optimization to improve the prediction accuracy. …”
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Applications of Convolutional Neural Network for Classification of Land Cover and Groundwater Potentiality Zones by Asnakew Mulualem Tegegne

“…This study aims to recognize the proficiency of deep learning algorithms, i.e., CNN, for spatial assessment of groundwater potential zones and land cover. …”
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