Advancements and Challenges in Microgrid Technology: A Comprehensive Review of Control Strategies, Emerging Technologies, and Future Directions by Ark Dev, Vineet Kumar, Gaurav Khare, Jayant Giri, Mohammad Amir, Furkan Ahmad, Prince Jain, Sumant Anand

“…This review focuses on existing control methods, particularly those addressing frequency and voltage stability, energy management, threat mitigation and explores a spectrum of engineering and nonengineering challenges within MG systems, proposing viable solutions. …”
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Fatigue and Distracted Driving Recognition Method Based on Multimodal Information Fusion by Deyong Guan, Qi Wang, Ke Wang, Xinyu Song

“…Finally, SHAP (SHapley Additive exPlanations) interpretable machine learning was employed to analyze the model results in depth. …”
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Analysis of methods for removing the fragments of instruments from the root canal system by A. V. Mitronin, K. A. Archakov, D. A. Ostanina, Yu. A. Mitronin

“…After analyzing the literature review an idea was obtained about the methods and indications for therapeutic and surgical methods of removing broken files from the root canal system. …”
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Understanding the Impact of Street Environments on Traffic Crash Risk from the Perspective of Aging People: An Interpretable Machine Learning Approach by Ketong Shen, Jian Liu, Xintao Liu

“…Interpretable machine learning methods are then employed to identify key environmental contributors and to compare their spatial contribution patterns across age groups. …”
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Construction of a prognostic model for endometrial cancer related to programmed cell death using WGCNA and machine learning algorithms by Weicheng Pan, Jinlian Cheng, Shanshan Lin, Qianxi Li, Yuanyuan Liang, Huiying Li, Xianxian Nong, Huizhen Nong

“…To isolate core prognostic PCD-DEGs, methods including consistency clustering analysis, weighted gene co-expression network analysis (WGCNA), univariate Cox regression analysis, and five machine learning techniques for dimensionality reduction were utilized. …”
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Magmatic trees: a method to compare processes between igneous systems by Christy B. Till

“…There are numerous potential applications of the method, which include, a) motivating process-driven hypotheses, b) examining the frequency of particular magmatic processes within and among volcanic systems, c) building mantle and crustal magmatic processes into event trees for hazard assessment, and d) teaching petrologic methods. …”
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Physical Layer Spoof Detection and Authentication for IoT Devices Using Deep Learning Methods by Da Huang, Akram Al-Hourani

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An integrated method of selecting environmental covariates for predictive soil depth mapping by Yuan-yuan LU, Feng LIU, Yu-guo ZHAO, Xiao-dong SONG, Gan-lin ZHANG

“…Finally, three optimal combinations were integrated to produce a final combination based on the importance and occurrence frequency of each environmental covariate. We tested this method for soil depth mapping in the upper reaches of the Heihe River Basin in Northwest China. …”
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Eye Collateral Channel Characteristic Analysis and Identification Model Construction of Mild Cognitive Impairment by WU Tiecheng, CAO Lei, YIN Lianhua, HE Youze, LIU Zhizhen, YANG Minguang, XU Ying, WU Jinsong

“…ObjectiveTo investigate the eye collateral channel characteristics of mild cognitive impairment (MCI) population, and to build an MCI identification model based on machine learning algorithms to provide an objective basis for early recognition of MCI.MethodsA total of 316 subjects from 5 communities in Fuzhou City, Fujian Province and the Health Management Center of the Second People's Hospital Affiliated to Fujian University of Traditional Chinese Medicine were recruited from April to December 2022. …”
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Automatic vibration fault detection of coal mine explosion-proof electrical equipment based on One-Class Support Vector Machine by ZHENG Tiehua, WANG Fei, ZHAO Gelan, DU Chunhui

“…As a result, the boundary between normal and fault signals becomes unclear, reducing the accuracy of traditional fault detection methods. To address this issue, an automatic vibration fault detection method for coal mine explosion-proof electrical equipment was proposed based on One-Class Support Vector Machine (OCSVM). …”
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Improved Feature-Selection Method Considering the Imbalance Problem in Text Categorization by Jieming Yang, Zhaoyang Qu, Zhiying Liu

“…We evaluated the improved versions of nine well-known feature-selection methods (Information Gain, Chi statistic, Document Frequency, Orthogonal Centroid Feature Selection, DIA association factor, Comprehensive Measurement Feature Selection, Deviation from Poisson Feature Selection, improved Gini index, and Mutual Information) using naïve Bayes and support vector machines on three benchmark document collections (20-Newsgroups, Reuters-21578, and WebKB). …”
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Numerical Study on Sharp Defect Evaluation Using Higher Order Modes Cluster (HOMC) Guided Waves and Machine Learning Models by Jing Xiao, Fangsen Cui

“…Both conventional fitting methods and machine learning (ML) models are used to estimate the depth of sharp defects reaching up to half the plate thickness. …”
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Forest cover and canopy health mapping in Australian subalpine landscape: supervised machine learning models for Sentinel-2 and Landsat images by Weerach Charerntantanakul, Marta Yebra, Hilary Rose Dawson, Adrienne Beth Nicotra, Saul Alan Cunningham, Matthew Theodore Brookhouse

“…This study aimed to develop a method to map distribution of subalpine woodlands and assess their canopy health using Sentinel-2 and Landsat series multispectral satellite imagery. …”
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Heartbeat Stars Recognition Based on Recurrent Neural Networks: Method and Validation by Min-Yu Li, Sheng-Bang Qian, Li-Ying Zhu, Wen-Ping Liao, Lin-Feng Chang, Er-Gang Zhao, Xiang-Dong Shi, Fu-Xing Li, Qi-Bin Sun, Ping Li

“…First, the orbital frequencies are calculated automatically according to the Fourier spectra of the light curves. …”
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Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle by Shing-Hong Liu, Alok Kumar Sharma, Bo-Yan Wu, Xin Zhu, Chun-Ju Chang, Jia-Jung Wang

“…However, the present methods involve measuring surface electromyograms (sEMGs) to analyze muscle activities. …”
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Hate Speech Detection and Online Public Opinion Regulation Using Support Vector Machine Algorithm: Application and Impact on Social Media by Siyuan Li, Zhi Li

“…Word embeddings are generated using Word2Vec’s Skip-gram model, combined with TF-IDF (Term Frequency–Inverse Document Frequency) weighting to capture contextual semantics. …”
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ARKAIV: Predicting Data Exfiltration Using Supervised Machine Learning Based on Tactics Mapping From Threat Reports and Event Logs by Arif Rahman Hakim, Kalamullah Ramli, Muhammad Salman, Bernardi Pranggono, Esti Rahmawati Agustina

“…As data breaches continue to increase in both frequency and severity, they pose escalating risks to organizations and society. …”
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CONTRIBUTION OF GENETIC MARKERS AND PRODUCTION FACTORS IN THE DEVELOPMENT OF ARTERIAL HYPERTENSION IN MEN IN AN ORGANIzED WORKERS COHORT OF MACHINE-BUILDING PLANT by A. A. Kiseleva, М. V. Klimushina, S. A. Tyupaeva, N. A. Eliseeva, S. A. Smetnev, А. D. Deev, А. N. Britov, А. N. Meshkov, О. М. Drapkina

“…In men, who had direct contact with PF at machine-building plant, GRS consisting of 11 SNPs was an independent factor influencing the presence of AH. …”
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Comparative study of different machine learning models in landslide susceptibility assessment: A case study of Conghua District, Guangzhou, China by Ao Zhang, Xin-wen Zhao, Xing-yuezi Zhao, Xiao-zhan Zheng, Min Zeng, Xuan Huang, Pan Wu, Tuo Jiang, Shi-chang Wang, Jun He, Yi-yong Li

“…The evaluation factors were selected by using correlation analysis and variance expansion factor method. Applying four machine learning methods namely Logistic Regression (LR), Random Forest (RF), Support Vector Machines (SVM), and Extreme Gradient Boosting (XGB), landslide models were constructed. …”
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Machine Learning‐Based Identification of Children With Intermittent Exotropia Using Multiple Resting‐State Functional Magnetic Resonance Imaging Features by Mengdi Zhou, Huixin Li, Xiaoxia Qu, Lirong Zhang, Xueying He, Xiwen Wang, Jie Hong, Jing Fu, Zhaohui Liu

“…Abstract Objective To investigate the performance of machine learning (ML) methods based on resting‐state functional magnetic resonance imaging (rs‐fMRI) parameters in distinguishing children with intermittent exotropia (IXT) from healthy controls (HCs). …”
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