Cluster analysis of social determinants of health and HIV/AIDS knowledge among Peruvian youths using Kohonen’s self-organized maps: a data-exploration study based on a Demographic... by Alejandro Aybar-Flores, Alvaro Talavera, Elizabeth Espinoza-Portilla

“…Epidemiological studies employing unsupervised learning techniques are essential for shaping public health policies. …”
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Biomarkers associated with cell-in-cell structure in kidney renal clear cell carcinoma based on transcriptome sequencing by Zehua Wang, Zhongxiao Zhang

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Computational histology reveals that concomitant application of insect repellent with sunscreen impairs UV protection in an ex vivo human skin model by Sophie Charrasse, Titouan Poquillon, Charlotte Saint-Omer, Audrey Schunemann, Mylène Weill, Victor Racine, Abdel Aouacheria

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CodonTransformer: a multispecies codon optimizer using context-aware neural networks by Adibvafa Fallahpour, Vincent Gureghian, Guillaume J. Filion, Ariel B. Lindner, Amir Pandi

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Collocation ranking: frequency vs semantics by Nikola Ljubešić, Nataša Logar, Iztok Kosem

“…In the experiment, two methods were used: for the quantitative part of the evaluation, we used supervised machine learning with the area-under-the-curve (AUC) ROC score and support-vector machines (SVMs) algorithm, and in the qualitative part the ranking results of the two methods were evaluated by lexicographers. …”
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TradeWise: Towards Context-Aware Stock Market Predictions with Sentiment and Political Insights by Andreas Marpaung, David Masterson

“…This enriched dataset is employed to train four different machine learning algorithms: a Hybrid, a Random Forest Model (RFM), a Support Vector Machine (SVM), and a K-Nearest Neighbors (KNN) model. …”
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GraphVelo allows for accurate inference of multimodal velocities and molecular mechanisms for single cells by Yuhao Chen, Yan Zhang, Jiaqi Gan, Ke Ni, Ming Chen, Ivet Bahar, Jianhua Xing

“…Here, we present GraphVelo, a graph-based machine learning procedure that uses as input the RNA velocities inferred from existing methods and infers velocity vectors lying in the tangent space of the low-dimensional manifold formed by the single cell data. …”
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Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers by Gonzalo A. Ruz, Pamela Araya-Díaz

“…Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization. …”
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A systematic review of dengue outbreak prediction models: Current scenario and future directions. by Xing Yu Leung, Rakibul M Islam, Mohammadmehdi Adhami, Dragan Ilic, Lara McDonald, Shanika Palawaththa, Basia Diug, Saif U Munshi, Md Nazmul Karim

“…Dengue is among the fastest-spreading vector-borne infectious disease, with outbreaks often overwhelm the health system and result in huge morbidity and mortality in its endemic populations in the absence of an efficient warning system. …”
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Response Relationship Between Runoff and Meteorological Drought and Flood Characteristics in Jialing River Basin by LI Wen-hui, ZHANG Yang, CAO Hui, XING Long, REN Yu-feng, ZHAI Shao-jun, MA Yi-ming, LI Wen-da

“…The findings indicate that emerging machine learning models, such as support vector machines and random forests, can effectively simulate the complex mechanisms through which meteorological drought and flood events affect runoff in the river basin. …”
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Improving prediction of solar radiation using Cheetah Optimizer and Random Forest. by Ibrahim Al-Shourbaji, Pramod H Kachare, Abdoh Jabbari, Raimund Kirner, Digambar Puri, Mostafa Mehanawi, Abdalla Alameen

“…Evaluation metrics encompassing Mean Absolute Error (MAE), Mean Squared Error (MSE), and coefficient of determination (R2) are employed to validate its performance. Quantitative analysis demonstrates that the CO-RF model surpasses other techniques, Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Network, and standalone Random Forest (RF), both in the training and testing phases of SR prediction. …”
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Newton’s Second Law Teaching Strategies—Identifying Opportunities for Educational Innovation by Victor Ricardo Parra-Zeltzer, Jaime Huincahue, Diana Abril

“…Furthermore, it was identified that Newton’s law is primarily represented in scalar form, with limited inclusion of vector approaches, which highlights the need to discuss didactic alternatives that consider both approaches.…”
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Computational linguistics and natural language processing techniques for semantic field extraction in Arabic online news by Maulana Ihsan Ahmad, Moh. Kanif Anwari

“…It provides a comprehensive approach to processing and analyzing large volumes of Arabic news data by integrating semantic field analysis, NLP, and computational linguistics. Using quantitative methods, Arabic news articles were collected and processed with Python, a popular programming language in data analysis, and applied various NLP techniques and machine learning models to accurately extract semantic fields. …”
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INVESTIGATION OF THE SUBJECT-SPATIAL ENVIRONMENT OF THE SCHOOL BY THE METHOD OF SEMANTIC DIFFERENTIAL by I. A. Vinogradova, E. V. Ivanova, O. V. Nesterova

“…Physical and psychological parameters of the school space have a significant impact on the motivation of a learning process and its results. Specificity of the school environment, its atmosphere and surroundings determine the meaning and nature of learning, a vector and activity of development and self-development of participants in the educational process, and determine their actions in it. …”
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Integration of Remote Sensing and GIS for Urban Sprawl Monitoring in European Cities by Stavros Kalogiannidis, Konstantinos Spinthiropoulos, Dimitrios Kalfas, Fotios Chatzitheodoridis, Fani Tziampazi

“…Supervised classification techniques, namely, Random Forest and Support Vector Machines, and spatial metrics including Shannon’s Entropy, Patch Density, Urban Compactness Ratio, and Buffer analysis were used to assess the level of sprawl. …”
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Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm by Sandeep Samantaray, Abinash Sahoo, Falguni Baliarsingh

“…In this context, machine learning (ML) methods offer a new and promising approach for accurately forecasting long-term changes in the groundwater level (GWL) without computational effort of developing a comprehensive flow model. …”
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Inversion Model for Total Nitrogen in Rhizosphere Soil of Silage Corn Based on UAV Multispectral Imagery by Hongyan Yang, Jixuan Yan, Guang Li, Weiwei Ma, Xiangdong Yao, Jie Li, Qihong Da, Xuchun Li, Kejing Cheng

“…Although UAV-based multispectral remote sensing technology has shown potential in agricultural monitoring, research on its quantitative assessment of soil TN content remains limited. …”
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AutoTA: A Dynamic Intent-Based Virtual Teaching Assistant for Students Using Open Source LLMs by Rajashree Dahal, Greg Murray, Robin Chataut, Mohamed Hefeida, Anurag K. Srivastava, Prashnna K. Gyawali

“…Our results show that the framework accurately classifies intent and provides appropriate guidance, measured through quantitative and qualitative metrics. These findings highlight the potential of the proposed framework to enhance personalized learning and improve student engagement. …”
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Technological Advancements and Economic Growth as Key Drivers of Renewable Energy Production in Saudi Arabia: An ARDL and VECM Analysis by Faten Derouez

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Convolutional Neural Networks for Automatic Identification of Individuals at Terrestrial Terminals by Darwin Yarango-Farro, Alex Mondragon-Fernandez, Heber I. Mejia-Cabrera, Juan Arcila-Diaz

“…The research was conducted under a quantitative approach and a quasi-experimental design. …”
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