RU-OLD: A Comprehensive Analysis of Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and Transformer Models by Muhammad Zain, Nisar Hussain, Amna Qasim, Gull Mehak, Fiaz Ahmad, Grigori Sidorov, Alexander Gelbukh

“…Extracted features use TF-IDF and Count Vectorizer for unigrams, bigrams, and trigrams. Of all the ML models—Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Naïve Bayes (NB)—the best performance was achieved by the same SVM. …”
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Forecasting inflation based on the consumer price index, taking into account the impact of seasonal factors by A. K. Sapova

“…The article is dedicated to development of quality short-term forecast of consumer inflation level, with the impact of seasonal factor. Two classes of models (vector autoregression and time series models) are considered. …”
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The development of the generative adversarial supporting vector machine for molecular property generation by Qing Lu

“…However, it has a large hyper-parameter space, which makes it difficult for training. In this work, we propose a new generative model by introducing the supporting vector machine into the GAN architecture. …”
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Using the Acoustic Velocity Vector to Assess the Condition of Buried Water Pipes by Joanna Watts, Michael-David Johnson, Kirill Horoshenkov

“…Traditionally, acoustic methods for leak inspection are based on the measurement of the acceleration of the external pipe wall or of the acoustic pressure in the pipe. This work presents an alternative inspection methodology based on measuring the acoustic velocity vector in the fluid filling the pipe. …”
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Probing light scalars and vector-like quarks at the high-luminosity LHC by U. S. Qureshi, A. Gurrola, A. Flórez, C. Rodriguez

“…The model contains a light scalar boson $$\phi '$$ ϕ ′ and a heavy vector-like quark $$\chi _\textrm{u}$$ χ u that can be probed at CERN’s large hadron collider (LHC). …”
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Face Mask Wearing Detection Using Support Vector Machine (SVM) by Muhammad Nur Yasir Utomo, Fajrin Violita

“…Thus, this research proposes a face mask-wearing detection using a soft-margin Support Vector Machine (SVM). There are three main stages: feature selection and preprocessing, model training, and evaluation. …”
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Performance Comparison of Genomic Best Linear Unbiased Prediction and Four Machine Learning Models for Estimating Genomic Breeding Values in Working Dogs by Joseph A. Thorsrud, Katy M. Evans, Kyle C. Quigley, Krishnamoorthy Srikanth, Heather J. Huson

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Deep Reinforcement Learning for Vectored Thruster Autonomous Underwater Vehicle Control by Tao Liu, Yuli Hu, Hui Xu

“…In this paper, we propose a controller based on deep reinforcement learning (DRL) in a simulation environment for studying the control performance of the vectored thruster AUV. RL is an important method of artificial intelligence that can learn behavior through trial-and-error interactions with the environment, so it does not need to provide an accurate AUV control model that is very hard to establish. …”
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Psychological and Pedagogical Bases for Determining the Future of Vocational Education: Vectors of Development by Yu. P. Zinchenko, E. M. Dorozhkin, E. F. Zeer

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Relevance Vector Machines for Enhanced BER Probability in DMT-Based Systems by Ashraf A. Tahat, Nikolaos P. Galatsanos

“…A new channel estimation method for discrete multitone (DMT) communication system based on sparse Bayesian learning relevance vector machine (RVM) method is presented. The Bayesian frame work is used to obtain sparse solutions for regression tasks with linear models. …”
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Enhancing the potency of in vivo lentiviral vector mediated gene therapy to hepatocytes by Cesare Canepari, Michela Milani, Chiara Simoni, Francesco Starinieri, Monica Volpin, Anna Fabiano, Mauro Biffi, Fabio Russo, Rossana Norata, Martina Rocchi, Chiara Brombin, Federica Cugnata, Eugenio Montini, Francesca Sanvito, Markus Grompe, Alessio Cantore

“…Abstract In vivo gene therapy to the liver using lentiviral vectors (LV) may represent a one-and-done therapeutic approach for monogenic diseases. …”
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Transformation of Geospatial Modelling of Soil Erosion Susceptibility Using Machine Learning by Muhammad Ramdhan Olii, Sartan Nento, Nurhayati Doda, Rizky Selly Nazarina Olii, Haris Djafar, Ririn Pakaya

“…This study assesses the use of Machine Learning (ML) methods—Support Vector Machines (SVM) and Generalized Linear Models (GLM)—to model Soil Erosion Susceptibility (SES) in the Saddang Watershed, Indonesia. …”
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The usage of power system multi-model forecasting aided state estimation for cyber attack detection by I. A. Lukicheva, A. L. Kulikov

“…The multimodal state estimator consisted of three single state estimators, which produced single estimates using different forecasting models. In this paper only linear forecasting models were considered, such as autoregression model, vector autoregression model and Holt’s exponen tial smoothing. …”
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MODELLING OF MODES OF A THREE-PHASE CHAIN WITH CROSS-SECTION ASYMMETRY by Gennadij P. Karabashev

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Design of a Prediction Model to Predict Students’ Performance Using Educational Data Mining and Machine Learning by Jayasree R, Sheela Selvakumari

“…The performance of the proposed model is compared with the Support Vector Machine and Random Decision algorithms and evaluated by four significant performance metrics, namely, sensitivity, specificity, accuracy, and the F-measure. …”
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Real-time monitoring and optimization of machine learning intelligent control system in power data modeling technology by Qiong Wang, Zuohu Chen, Yongbo Zhou, Zhiyuan Liu, Zhenguo Peng

“…The experimental results show that the accuracy of the paper's model in both the training and testing sets is higher than that of the convolutional neural network, decision tree, and support vector machine models in the comparative experiments, reaching 93 % and 94 %, respectively. …”
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Dataset and machine learning-based computer-aided tools for modeling working sorption isotherms in dried parchment and green coffee beansMendeley Data by Gentil A. Collazos-Escobar, Andrés F. Bahamón-Monje, Nelson Gutiérrez-Guzmán

“…Thereby, the MATLAB scripts implement an automated routine for the calibration and optimization of the Support Vector Machine (SVM) and Random Forest (RF) techniques, enabling the modeling of working sorption isotherms for each coffee type (considering only aw and temperature) and in a multivariate approach (incorporating aw, temperature, and coffee type) to predict the equilibrium moisture content (Xe). …”
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MATHEMATICAL SIMULATION OF SENSORLESS VECTOR CONTROL INDUCTION MOTOR UNDER PARAMETRIC PERTURBATIONS by D. S. Odnolko

“…Developed a mathematical simulation model of the system of indirect sensorless vector control induction motor. …”
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Support Vector Machine and Granular Computing Based Time Series Volatility Prediction by Yuan Yang, Xu Ma

“…At the same time, the granulation idea of grain computing is introduced into time-series analysis, and the original high-dimensional time series is granulated into low-dimensional grain time series by information granulation of time series, and the constructed information grains can portray and reflect the structural characteristics of the original time-series data, to realize efficient dimensionality reduction and lay the foundation for the subsequent data mining work. Finally, the grains of the decision tree are analyzed, and different support vector machine classifiers corresponding to each grain are designed to construct a global multiclassification model.…”
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Evaluation of Decision Tree and Support Vector Machine Classifiers in Comparison for Flood Prediction by Suha Abdullah

“…The goal of this study was to find out how well the Support Vector Machine (SVM) and Decision Tree classifiers work at predicting flooding based on different environmental and infrastructure factors. …”
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