Early detection of emerging SARS-CoV-2 Variants from wastewater through genome sequencing and machine learning by Xiaowei Zhuang, Van Vo, Michael A. Moshi, Ketan Dhede, Nabih Ghani, Shahraiz Akbar, Ching-Lan Chang, Angelia K. Young, Erin Buttery, William Bendik, Hong Zhang, Salman Afzal, Duane Moser, Dietmar Cordes, Cassius Lockett, Daniel Gerrity, Horng-Yuan Kan, Edwin C. Oh

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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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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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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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Risk Analysis on FGH Terminal Using Importance Index and Bowtie Analysis Methods by Mirga Maulana Rachmadhani, Mardhiah Gani, Aprisa Rian Histiarini, Oki Febiyani Amalia Tuankotta

“…Risk analysis using the Importance Index (IMPI) method is carried out to assess risks by calculating the Frequency Index and Severity Index values, identifying the causes and consequences of risks that are classified as significant, analyzing the causes and impacts of risks and preventive actions and recovery actions from existing risks, and then will be described in a bowtie diagram. …”
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Performance Evaluation of Neighbors-Based Learning Methods for Network Intrusion Detection System by Ngoc Thien Nguyen

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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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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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Advances in Infant Cry Paralinguistic Classification—Methods, Implementation, and Applications: Systematic Review by Geofrey Owino, Bernard Shibwabo

“…ResultsNotable advancements in infant cry classification methods were realized, particularly from 2019 onward, using machine learning, deep learning, and hybrid approaches. …”
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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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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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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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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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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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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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The occurrence of and risk factors for depressive symptomatology in myocarditis survivors: a cross-sectional survey-based study using machine learning by Jean Marrero-Polanco, Laura Suarez Pardo, Shehzad K. Niazi, Daniel G. Smith, Cynthia J. Stoppel, Candace Moose, Arjun P. Athreya, Arjun P. Athreya, Leslie T. Cooper, Leslie T. Cooper, William V. Bobo

“…BackgroundThe frequency and impact of depressive symptoms in myocarditis survivors are poorly understood.ObjectivesWe conducted a cross-sectional study to identify risk factors and the relative importance of each for predicting clinically significant depressive symptomatology in myocarditis survivors.MethodsParticipants completed an electronic survey assessing sociodemographic, general health, and myocarditis-related variables, as well as self-reported cardiac symptoms and personal and family mental health history. …”
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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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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

“…Consistent with this vulnerability, increased fire frequency and widespread insect-induced dieback has been reported across the subalpine woodlands of southeastern Australia. …”
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Fault Diagnosis Method for Open-circuit Faults in NPC Three-level Inverter based on WKCNN by Guozheng Zhang, Menghui Li, Xin Gu, Wei Chen

“…Experimental results under various operating conditions demonstrate that this approach maintains robust diagnostic accuracy across multiple fault scenarios, with comparative analysis further confirming its advantages in diagnostic efficiency and performance over traditional machine learning and other deep learning methods.…”
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