Optimization of sports injury treatment through artificial intelligence: Methods for effective prevention, diagnosis and rehabilitation by Kimi Milić Marko, Sinanović Šćepan, Jestrović Vladimir

“…The research methodology includes big data analysis, image processing, machine learning, and customized algorithms for prediction and rehabilitation monitoring. …”
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Modal Regression Estimation by Local Linear Approach in High-Dimensional Data Case by Fatimah A. Almulhim, Mohammed B. Alamari, Ali Laksaci, Zoulikha Kaid

“…Simulations and real-data applications demonstrate the algorithm’s effectiveness, showing its advantage over existing methods in high-dimensional prediction tasks.…”
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Optimal 5G Network Sub-Slicing Orchestration in a Fully Virtualised Smart Company Using Machine Learning by Abimbola Efunogbon, Enjie Liu, Renxie Qiu, Taiwo Efunogbon

“…The framework leverages the LazyPredict module to automatically select optimal supervised learning algorithms based on real-time network conditions and historical data. …”
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Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT by Zhanglei Yan, Yuwei Wu, Wenbo Zhao, Shao Zhang, Xu Li

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A Novel Fault Diagnosis Method for Rolling Bearing Based on Improved Sparse Regularization via Convex Optimization by Dongjie Zhong, Cancan Yi, Han Xiao, Houzhuang Zhang, Anding Wu

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Clinical effectiveness of routine first‐trimester combined screening for pre‐eclampsia in Spain with the addition of placental growth factor by Pablo Garcia‐Manau, Erika Bonacina, Berta Serrano, Sara Caamiña, Marta Ricart, Eva Lopez‐Quesada, Àngels Vives, Monica Lopez, Elena Pintado, Anna Maroto, Sara Catalan, Marta Dalmau, Ester Del Barco, Alina Hernandez, Marta Miserachs, Marta San Jose, Mireia Armengol‐Alsina, Elena Carreras, Manel Mendoza

“…A greater treatment adherence resulted in a significant reduction in adverse outcomes. Conclusions Routine first‐trimester screening for pre‐eclampsia with placental growth factor leads to a reduction in preterm pre‐eclampsia and other pregnancy complications. …”
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A rolling bearing fault diagnosis method based on GADF-CWT-GCNN by ZHANG Xiaoli, LUO Xin, LI Min, LIANG Wang, WANG Fangzhen

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Deriving Overlapped Cloud Motion Vectors Based on Geostationary Satellite and Its Application on Monitoring Typhoon Mulan by Cuiping Liu, Wei Han, Feng Zhang, Jiaqi Jin, Qiong Wu, Wenwen Li, Chloe Yuchao Gao

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Fine-scale carbon stocks mapping in the mangrove forests of Tumaco, Colombia using machine learning and remote sensing approaches by Laura Lozano-Arias, Bryan Ernesto Gallego-Pérez, John Josephraj Selvaraj

“…Additionally, spectral indices significantly enhanced the model’s ability to predict aboveground biomass.…”
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Dynamic analysis of malicious behavior propagation based on feature selection in software network by Huajian Xue, Huajian Xue, Yali Wang, Qiguang Tang

“…The method is divided into three stages: First, variable-length N-gram algorithms are utilized to extract subsequences of varying lengths from the sample APl call sequences as continuous dynamic features. …”
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Crowd anomaly estimation and detection: A review by A. Hussein, M.W. Raed, A. Al-Shaikhi, M. Mohandes, B. Liu

“…We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. …”
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Deep-Learning and Dynamic Time Warping-Based Approaches for the Diagnosis of Reactor Systems by Hoejun Jeong, Jihyun Kim, Doyun Jung, Jangwoo Kwon

“…The experiment results demonstrate that the size and position of clamping force degradation can be accurately predicted. It is expected that this research will contribute to enhancing the precision and efficiency of internal structure monitoring in nuclear power plants.…”
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Early Detection of Parkinson’s Disease Using AI Techniques and Image Analysis by Marilena Ianculescu, Corina Petean, Virginia Sandulescu, Adriana Alexandru, Ana-Mihaela Vasilevschi

“…Methods: The best approach is selected to be integrated in a neurodegenerative disease management platform called NeuroPredict. The most innovative aspects of the presented approaches are related to the employed feature extraction techniques that convert hand-drawn spirals into a frequency spectra, so that frequency features may be extracted and utilized as inputs for various classification algorithms. …”
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Optimizing Energy Supply for Full Electric Vehicles in Smart Cities: A Comprehensive Mobility Network Model by Victor Fernandez, Virgilio Pérez, Rosa Roig

“…This study presents a comprehensive mobility network model designed to predict and optimize the energy supply for FEVs within smart cities. …”
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Circulating MicroRNAs as Novel Biomarkers in Risk Assessment and Prognosis of Coronary Artery Disease by Chiara Vavassori, Eleonora Cipriani, Gualtiero Ivanoe Colombo

“…Nevertheless, available cardiovascular risk prediction algorithms still miss a significant portion of individuals at-risk. …”
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METHODOLOGY OF PRACTICE-ORIENTED RESEARCH ACTIVITIES OF STUDENTS DURING PEDAGOGICAL INTERNSHIP: BUILDING NATIONAL IDENTITY IN MULTICULTURAL ENVIRONMENT by Tatyana L. Oskolova

“…Proposed investigation is based on formal requirements of national education including analysis of specific educational activities in ethnically and culturally diverse society.Methods. …”
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Restoring Force Model of an Energy-Dissipation Joint in Hybrid Frames: Simplified Skeleton Curve and Hysteretic Rules by Yanhua Wang, Yan Feng, Dongsheng Huang, Zirui Huang, Zhongfan Chen

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Robust time series analysis for forecasting photovoltaic energy yield by Sapundzhi Fatima, Chikalov Aleksandar, Georgiev Slavi, Georgiev Ivan, Todorov Venelin

“…This study introduces an approach to forecasting the power output of a photovoltaic (PV) system by employing an ARIMA-based algorithm. Two distinct ARIMA models were designed – one generated via SPSS and one selected by the researchers. …”
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A framework based on mechanistic modelling and machine learning for soil moisture estimation by Sabri Kanzari, Sana Ben Mariem, Samir Ghannem, Safouane Mouelhi, Hiba Ghazouani, Bechir Ben Nouna

“…These values were used as inputs to the Hydrus 1D model to generate soil water content profiles over a 27-year period. 109 profiles were calculated using machine learning algorithms (regression trees; random forest; support vector machine) to predict soil moisture content from daily values of rainfall and evaporation. …”
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Hexapod robot motion planning investigation under the influence of multi-dimensional terrain features by Chen Chen, Chen Chen, Junbo Lin, Junbo Lin, Bo You, Bo You, Jiayu Li, Jiayu Li, Biao Gao, Biao Gao

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