Modeling the distribution of the invasive snail Physella acuta in China: Implications for ecological and economic impact by Yingxuan Yin, Anyuan Xu, Xiaowen Pan, Qing He, Aoxun Wu, Linya Huang, Yinjuan Wu, Xuerong Li

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Numerical Simulations of Complex Helmholtz Equations Using Two-Block Splitting Iterative Schemes with Optimal Values of Parameters by Chein-Shan Liu, Chih-Wen Chang, Chia-Cheng Tsai

“…The primary novelty and major contribution of this paper lies in using the orthogonality condition of residual vectors to optimize the iterative process. The proposed method might fill a gap in the current literature, where existing iterative methods either lack explicit parameter optimization or struggle with high wave numbers and large damping constants in the complex Helmholtz equation. …”
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Comparison of various machine learning regression models based on Human age prediction by Dr.Manaf K Hussein

“…In this study, five widely used machine learning  regression models (Linear support vector regression (L-SVR), radial basis function support vector regression (RBF-SVR), relevance vector regression (RVR), Elastic Net and Gaussian process regression (GPR)) were trained and evaluated to predict brain age using volumes of brain regions data. …”
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Evaluating and Forecasting the Probability of Lightning Occurrence in Rasht City by Afsaneh Ghasemi, Jamil Amanollahi

“…After preprocessing and processing data, data mining models including Classification & Regression Tree (CART), Chi-squared Automatic Interaction Detector (CHAID), Induction of Decision Trees (C5) and neural networks Radial Basis Function (RBF), Multi Layer Perceptron (MLP) and Support Vector Machine (SVM) were used in Spss Modeler Ver 20 software. …”
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A state evaluation and fault diagnosis strategy for substation relay protection system integrating multiple intelligent algorithms by Jiajun Wang, Shiyi Jing, Yu Yao, Kunlun Wang, Bo Li

“…This study introduces a new diagnostic framework that combines improved particle swarm optimization, K‐means clustering algorithms, support vector machine (SVM), and learning vector quantization neural networks to provide a comprehensive fault diagnosis and prediction model for relay protection systems. …”
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Evaluation of Different Machine Learning Models for Predicting Soil Erosion in Tropical Sloping Lands of Northeast Vietnam by Tuan Vu Dinh, Nhat-Duc Hoang, Xuan-Linh Tran

“…This study evaluates possibility of predicting erosion status by machine learning models, including fuzzy k-nearest neighbor (FKNN), artificial neural network (ANN), support vector machine (SVM), least squares support vector machine (LSSVM), and relevance vector machine (RVM). …”
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Wide-angle deep ultraviolet antireflective multilayers via discrete-to-continuous optimization by Kim Jae-Hyun, Kim Dong In, Lee Sun Sook, An Ki-Seok, Yim Soonmin, Lee Eungkyu, Kim Sun-Kyung

“…For discrete optimization, a multilayer was encoded into a binary vector with multiple bits; a 10 nm thick MgF2 or LaF3 layer was assigned a binary digit of 0 or 1, respectively. …”
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Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning by Martynas Maciulevičius, Greta Rupšytė, Renaldas Raišutis, Blaž Cugmas, Mindaugas Tamošiūnas

“…For the differentiation between mastocytoma and sarcoma tumors, both support vector machine and random forest outperformed conventional linear discriminant analysis classifier. …”
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HISTORIOGRAPHY OF THE STUDY OF STATE PRACTICES AND THE JUDICIARY OF SOUTHERN UKRAINIAN TERRITORIES: GENERAL CHARACTERISTICS by Oleg Vuyiv, Maryna Bulkat

“…However, the approach to the analysis of the processes of development of the southern Ukrainian territories in the core branches of historical science has now been radically changed and deepened. …”
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Development of interest in training by creation emotional and comfortable educational environment by Olga M. Shentsova

“…The Russian education system is in continuous process of modernization today. Changes in the Russian society, policy and economy exert direct impact on this process. …”
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Unraveling the Role of Proteinopathies in Parasitic Infections by Mikołaj Hurła, Damian Pikor, Natalia Banaszek-Hurła, Alicja Drelichowska, Jolanta Dorszewska, Wojciech Kozubski, Elżbieta Kacprzak, Małgorzata Paul

“…Dissecting the molecular pathways underpinning these processes offers unprecedented opportunities for developing innovative therapies. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…(1) Background: Globally, the kidney donor shortage has made the allocation process critical for patients awaiting a kidney transplant. …”
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Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach by Qiulin Li, Jinchao He, Dewei Mu, Hao Liu, Shicheng Li

“…Dissolved oxygen (DO) is a vital water quality index influencing biological processes in aquatic environments. Accurate modeling of DO levels is crucial for maintaining ecosystem health and managing freshwater resources. …”
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Cellular and molecular aspects of degenerative disc disease and potential strategies of biological therapy by A. V. Novikova, N. G. Pravdyuk, N. A. Shostak

“…A key point in IVD dehydration is that catabolic processes predominate over anabolic ones due to changed gene expression in the corresponding biologically active molecules, disc angiogenesis and neoinnervation of the structures of the fibrous ring and pulpous nucleus. …”
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THE RENEWAL AND UPGRADE OF LEGAL REGULATION OF TELECOMMUNICATIONS IN THE EU by M. B. Kasenova

“…The choice of the strategic vector of the socio-economic development of modern states is focused on the “digital economy”, and telecommunications offer critical economic importance and commercial value. …”
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Machine Learning Models for Carbonation Depth Prediction in Reinforced Concrete Structures: A Comparative Study by Rafael Aredes Couto, Igor Augusto Guimarães Campos, Elvys Dias Reis, Daniel Hasan Dalip, Flávia Spitale Jacques Poggiali, Péter Ludvig

“…This study applied machine learning (ML) techniques—Random Forest (RF), Support Vector Regression (SVR), and Artificial Neural Networks (ANNs)—to predict carbonation depth using a synthetic dataset of 20,000 instances generated from the validated Possan equation. …”
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Artificial intelligence, chess and the risks of modern civilization by G. Sh. Pilavov

“…As the researchers of this issue have noted, artificial intelligence can be used as a tool to establish an autocratic regime (Wang Jianguang), or become a means for radical socio-political processes (G. I. Kolesnikova). In conclusion, proposals are put forward on the most effective methods of combating the possible use of artificial intelligence to radically change the vector of development of our civilization. …”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…A comparative analysis of six machine learning models—Logistic Regression, Support Vector Machines (SVM), Random Forest, and proposed EvacuNet—demonstrates that EvacuNet outperforms all other models, achieving an accuracy of 99.99%, precision of 1.00, recall of 1.00, and an AUC-ROC score close to 1.00. …”
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A Keyframe Extraction Method for Assembly Line Operation Videos Based on Optical Flow Estimation and ORB Features by Xiaoyu Gao, Hua Xiang, Tongxi Wang, Wei Zhan, Mengxue Xie, Lingxuan Zhang, Muyu Lin

“…Each video frame is first encoded into a feature vector using the ORB algorithm and a bag-of-visual-words model. …”
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Numerical Simulation of Perkins Instability in the Midlatitude F-Region Ionosphere: The Influence of Background Ionospheric Multi-Factors by Yi Liu, Ting Lan, Yufeng Zhou, Yunzhou Zhu, Zhiqiang Fan, Yewen Wu, Yuqiang Zhang, Xiang Wang

“…The electrodynamic coupling process has a greatly significant effect on the growth rate of Perkins instability compared to GW activity.…”
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