Customer Churn Prediction Approach Based on LLM Embeddings and Logistic Regression by Meryem Chajia, El Habib Nfaoui

“…Consequently, there has been a growing demand for advanced methods aimed at enhancing customer loyalty and satisfaction, as well as predicting churners. In our work, we focused on building a robust churn prediction model for the telecommunications industry based on large embeddings from large language models and logistic regression to accurately identify churners. …”
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A comparative study of hybrid adaptive neuro-fuzzy inference systems to predict the unconfined compressive strength of rocks by Wei Cao

“…Hybrid models included support vector regression (SVR) combined with the Seahorse Optimizer (SVSH) and SVR combined with the COOT optimization algorithm (SVCO). …”
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Automated Quality Control of Candle Jars via Anomaly Detection Using OCSVM and CNN-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

“…Two anomaly detection strategies are explored: (1) a baseline model using convolutional neural networks (CNNs) as an end-to-end classifier and (2) a hybrid approach where features extracted by CNNs are fed into One-Class classification (OCC) algorithms, including One-Class SVM (OCSVM), One-Class Isolation Forest (OCIF), One-Class Local Outlier Factor (OCLOF), One-Class Elliptic Envelope (OCEE), One-Class Autoencoder (OCAutoencoder), and Support Vector Data Description (SVDD). …”
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A Scoping Review of Preclinical Research on Monoclonal Antibody Development for Prophylaxis and Treatment of West Nile Virus Infections by Amanda E. Calvert, Kerri L. Miazgowicz, Bailey Atkinson, Audrey H. Long, Elisa Thrasher, Aaron C. Brault, Randall J. Nett

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Digital reconstruction of historic roof structures: developing a workflow for a highly automated analysis by Markus Pöchtrager, Gudrun Styhler-Aydın, Marina Döring-Williams, Norbert Pfeifer

“…Current methods for a modellingof roof constructions consist of several manual steps  including  the  time-consuming  dimensional modelling. The  continuous  development  of terrestrial laser  scanners increases  the  accuracy,  comfort  and  speed  of  the  surveying  work inroof constructions. …”
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Optimized Breast Cancer Classification Using PCA-LASSO Feature Selection and Ensemble Learning Strategies With Optuna Optimization by Prabhat Kumar Sahu, Taiyaba Fatma

“…The classifiers employed include Random Forest, Support Vector Machine (SVM), Gradient Boosting, and Logistic Regression, which were further refined using GridSearchCV, RandomizedSearchCV, and Optuna, with 3-fold cross-validation implemented to ensure robust evaluation of model performance. …”
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Three-Dimensional Rapid Orbit Transfer of Diffractive Sail with a Littrow Transmission Grating-Propelled Spacecraft by Alessandro A. Quarta

“…Accordingly, this paper extends and generalizes the results recently obtained by the author in the context of a simplified, two-dimensional, heliocentric mission scenario. In particular, this work illustrates an analytical model of the thrust vector that can be used to study the performance of a DSLT-based spacecraft in a three-dimensional optimization context. …”
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Mitigating the Concurrent Interference of Electrode Shift and Loosening in Myoelectric Pattern Recognition Using Siamese Autoencoder Network by Ge Gao, Xu Zhang, Xiang Chen, Zhang Chen

“…The objective of this work is to develop a novel myoelectric pattern recognition (MPR) method to mitigate the concurrent interference of electrode shift and loosening, thereby improving the practicality of MPR-based gestural interfaces towards intelligent control. …”
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Keywords, morpheme parsing and syntactic trees: features for text complexity assessment by Dmitry A. Morozov, Ivan A. Smal, Timur A. Garipov, Anna V. Glazkova

“…The use of an extensive set of syntactic features allowed, in most cases, to improve the quality of work of neural network models in comparison with the previously described set.…”
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Candidate antirheumatic genotherapeutic plasmid constructions have low immunogenicity by T. S. Nepomnyashchikh, T. V. Tregubchak, S. N. Yakubitskiy, O. S. Taranov, R. A. Maksyutov, S. N. Shchelkunov

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Sql injection detection using Naïve Bayes classifier: A probabilistic approach for web application security by Lu Zhexi

“…Using the Naive Bayes classifier, a probabilistic model specifically developed for text classification tasks, this work introduces a novel method for detecting SQL injection vulnerabilities.The process begins by collecting and organizing a comprehensive dataset, which includes both harmful and non-malicious SQL queries. …”
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Ultrastructural organization and reproduction of virions in Vero (E6) cells in influenza A/H1N1 pmd09 virus monoinfection and coinfection with SARS-CoV-2 (Delta and Omicron strains... by Ksenia F. Emtsova, Ekaterina V. Spiridonova, Vladimir V. Omigov, Anastasia A. Moiseeva, Elena I. Danilenko, Oleg S. Taranov

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An Adaptive Data-Driven Approach to Solve Real-World Vehicle Routing Problems in Logistics by Emir Žunić, Dženana Đonko, Emir Buza

“…A comparison of the acquired results has been made using the decision support system with predictive models: generalized linear models (GLMs) and support vector machine (SVM). …”
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Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach by K. Somasundaram, P. Alli Rajendran

“…The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. …”
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THE ANALISYS OF RAILWAY MULTI MOTORS ELECTRICAL DRIVE DYNAMIC by V. I. Khilmon, O. F. Opeiko, D. S. Odnolko

“…In this paper an analysis is presented for two inducton motors traction drive with frequency inverter, vector control, and speed sensors of each electrical drive. …”
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The Ground-State Calculations for Some Nuclei by Mesonic Potential of Nucleon-Nucleon Interaction by K. M. Hanna, S. H. M. Sewailem, R. Hussien, L. I. Abou-Salem, Asmaa G. Shalaby

“…We construct a one-boson exchange potential (OBEP) model, where each nucleon is treated as a Dirac particle and acts as a source of pseudoscalar, scalar, and vector fields. …”
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Feature Generation with Genetic Algorithms for Imagined Speech Electroencephalogram Signal Classification by Edgar Lara-Arellano, Andras Takacs, Saul Tovar-Arriaga, Juvenal Rodríguez-Reséndiz

“…EEG signal classification is difficult as the machine learning (ML) algorithm has to learn how to categorize the signal linked to the imagined word. This work proposes a novel method to generate a specific feature vector to achieve classification with superior accuracy results to those found in the state of the art. …”
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Using Machine Learning to Predict Linezolid-Associated Thrombocytopenia by Wei R, Li K, Wang H, Cai X, Liu N, An Z, Zhou H

“…Future work should validate the model in multicenter studies and explore its integration into clinical decision support systems.Keywords: linezolid, thrombocytopenia, machine learning, risk factors…”
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FEPP: Advancing Software Risk Prediction in Requirements Engineering Through Innovative Rule Extraction and Multi-Class Integration by Muhammad Binsawad, Bilal Khan

“…Thus, ForExPlusPlus (FEPP), a novel model for risk prediction in software requirements, is proposed in this work. …”
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Enhancing solar irradiance prediction precision: A stacked ensemble learning-based correction paradigm by Bo Tian, Ningbo Wang, Yuanxin Lin, Shuangquan Shao

“…The ensemble framework integrates 5 base models—multiple linear regression (MLR), artificial neural network (ANN), K-nearest neighbors (KNNs), random forest (RF), and support vector regression (SVR)—using stacking technology, with a meta-model applied for final prediction refinement. …”
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