Diagnostic Applications of AI in Sports: A Comprehensive Review of Injury Risk Prediction Methods by Carmina Liana Musat, Claudiu Mereuta, Aurel Nechita, Dana Tutunaru, Andreea Elena Voipan, Daniel Voipan, Elena Mereuta, Tudor Vladimir Gurau, Gabriela Gurău, Luiza Camelia Nechita

“…This review also addresses critical issues such as data quality, ethical concerns, privacy, and the need for transparency in AI applications. By shifting the focus from reactive to proactive injury management, AI technologies contribute to enhanced athlete safety, optimized performance, and reduced human error in medical decisions. …”
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Application of machine learning techniques to predict the compressive strength of steel fiber reinforced concrete by Ala’a R. Al-Shamasneh, Arsalan Mahmoodzadeh, Faten Khalid Karim, Taoufik Saidani, Abdulaziz Alghamdi, Jasim Alnahas, Mohammed Sulaiman

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Lightweight AES Design for IoT Applications: Optimizations in FPGA and ASIC With DFA Countermeasure Strategies by Salman Ahmed, Nabihah Ahmad, Nasir Ali Shah, Ghulam E. Mustafa Abro, Ardhi Wijayanto, Abdinasir Hirsi, Abdul Rehman Altaf

“…In addition, the study reviews DFA countermeasures that highlight fault detection methods, error detection levels, protection positions, and associated design overheads such as area, frequency, and throughput penalties, with special consideration for resource-constrained IoT devices. …”
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Thermal analysis and experimental design of PVDF-trfe-based pyroelectric sensors for infrared applications by Mohamed Behloul, Essaid Bousbiat, Dalila Yamani, Riyadh Bouddou, Nour Eddine Derguini, Ayodeji Olalekan Salau, Djamel Kendil, Sarra Adiche

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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…The theoretical proof demonstrates that these algorithms exhibit an optimal rate of convergence for functions with continuous and bounded first derivatives and for functions with continuous and bounded second derivatives, respectively, both in terms of probability and mean square error. For the purposes of numerical study, these approaches were successfully applied to a particular problem. …”
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Estimation of soil temperature for agricultural applications in South Africa using machine-learning methods by Lindumusa Myeni, Tlotlisang Nkhase, Ramontsheng Rapolaki, Zaid Bello, Mokhele E. Moeletsi

“…The results showed that soil temperature at various depths can be reasonably estimated by different generic machine-learning models, with average Nash–Sutcliffe efficiency values ranging from 0.74 for decision tree to 0.87 for random forest models and root mean square error values of less than 2.79 °C for all models. …”
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Application of a Dynamic Exposure Population Toxicokinetic Model for Perfluorooctane Sulfonic Acid (PFOS) and Extension to Perfluorodecanoic Acid (PFDA) at a North American Beef Ca... by Barbara A. Astmann, Antti T. Mikkonen, Thomas L. Simones, Meghan Flanagan, Duncan Pfaehler, Ivan Lenov, Andrew E. Smith

“…Historical application of wastewater treatment sludge (biosolids) has introduced per- and polyfluoroalkyl substances (PFAS) into agricultural systems and led to contamination of crops and livestock. …”
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Parameter calibration and application of GTN damage model for girth weld in X80 pipeline by Zhonghao CUI, Yanhe LIU, Haitao WANG, Yanlong LUO, Xinjun ZHANG, Shili LI, Shaokun ZHOU

“…A comparison of the four characteristic values of tensile stress, tensile strain, fracture stress, and fracture strain resulted in a maximum error not exceeding 10%. In the applicability verification for the model, the apparent toughness values of single edge notch tensile and single edge notch bending specimens were recorded at 0.399 3 and 0.324 2 respectively, corresponding to both final conversion rates of about 1.23. …”
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Application of Improved PSO-BP Neural Network in Cold Load Forecasting of Mall Air-Conditioning by JunQi Yu, WenQiang Jing, AnJun Zhao, YanHuan Ren, Meng Zhou

“…A combination of JMP, PSO-BP neural network, and Markov chain which aims at the low correlation between input and output data and the error of prediction model in the PSO-BP neural network prediction model is proposed. …”
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A Study on Canopy Volume Measurement Model for Fruit Tree Application Based on LiDAR Point Cloud by Na Guo, Ning Xu, Jianming Kang, Guohai Zhang, Qingshan Meng, Mengmeng Niu, Wenxuan Wu, Xingguo Zhang

“…These results demonstrate that the PLSR model exhibits strong generalization ability, minimal prediction bias, and low average prediction error, offering a valuable reference for precision control of canopy spraying in orchards.…”
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Aircraft Skin Damage Visual Testing System Using Lightweight Devices with YOLO: An Automated Real-Time Material Evaluation System by Kuo-Chien Liao, Jirayu Lau, Muhamad Hidayat

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Activity prediction of anti-cancer drug candidate ERα inhibitor by XIA Yulan, XIE Jiming, WANG Yajing, LU Mengyuan, WANG Jinrui, QIN Yaqin

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Forecasting Urban Rail Transit Vehicle Interior Noise and Its Applications in Railway Alignment Design by Yifeng Wang, Ping Wang, Zihan Li, Zhengxing Chen, Qing He

“…Then, for establishing the mapping relationship between the dynamic responses of the car body and interior noise, the collected dataset was fed to the RF. Parameter, error distribution, and feature importance analyses were conducted for evaluating and optimizing the performance of the RF. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

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Systematic Review of Usability Factors, Models, and Frameworks with Blockchain Integration for Secure Mobile Health (mHealth) Applications by Irum Feroz, Nadeem Ahmad

“…Findings from RQ2 highlighted gaps in usability models, such as the lack of age-specific guidance for multimodal interaction, error recovery, and data privacy. These results underscore the need to define a new usability framework and incorporate blockchain to meet the unique needs of older adults in mHealth applications, supporting both secure and accessible healthcare management.…”
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Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data by Mary Pleños

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AI-Driven Insect Detection, Real-Time Monitoring, and Population Forecasting in Greenhouses by Dimitrios Kapetas, Panagiotis Christakakis, Sofia Faliagka, Nikolaos Katsoulas, Eleftheria Maria Pechlivani

“…The ARIMAX model performed best with a Mean Square Error (MSE) of 75.61, corresponding to an average deviation of 8.61 insects per day between predicted and actual insect counts. …”
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Application of Machine Learning for Methanolysis of Waste Cooking Oil Using Kaolinite Geopolymer Heterogeneous Catalyst by Pascal Mwenge, Hilary Rutto, Tumisang Seodigeng

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Development of a Web-Based Decision Support System for Selecting the Optimal Duck Feed Using the Analytic Hierarchy Process (AHP) by Khaira Nazla, Enrico Vincentius Manurung, M Fauzan Hidayat, Debi Yandra Niska

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Bayesian model parameter learning in linear inverse problems: application in EEG focal source imaging by Alexandra Koulouri, Ville Rimpiläinen

“…An error subspace was spanned with the help of the eigenvectors of the approximation error covariance matrix which allowed, alongside the primary signal, simultaneous estimation of the induced error. …”
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