Pole-Phase Modulation of Symmetrical 6-Phase Induction Motor Drive for Electric Vehicle With 1:2 Speed Control by S. V. Umredkar, R. Keshri, V. B. Borghate, M. M. Renge

“…This study focuses on acceleration control over the 4-pole/1500 rpm and 2-pole/ 3000 rpm modes to achieve fast acceleration with high-torque and high-speed with low-torque required for the initial start and cruising respectively. Mathematical modeling based on the space vector theory to control S6TPPM IMDrive is presented. …”
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A Data Storage, Analysis, and Project Administration Engine (TMFdw) for Small- to Medium-Size Interdisciplinary Ecological Research Programs with Full Raster Data Capabilities by Paulina Grigusova, Christian Beilschmidt, Maik Dobbermann, Johannes Drönner, Michael Mattig, Pablo Sanchez, Nina Farwig, Jörg Bendix

“…While the system was mainly developed for abiotic and biotic tabular data in the beginning, the new research program demands full capabilities to work with area-wide and high-resolution big models and remote sensing raster data. …”
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Mathematical modeling of velocity and accelerations fields of image motion in the optical equipment of the Earth remote sensing satellite by S. Yu. Gorchakov

“…The paper considers a satellite with an optoelectronic payload designed to take pictures of the Earth’s surface. The work sets out to develop a mathematical model for determining the dependencies between the state vector of the satellite, the state vector of the point being imaged on the Earth’s surface, and the distribution fields of the velocity vectors and accelerations of the motion of the image along the focal plane of the optoelectronic payload.Methods. …”
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The importance of age dependent mortality and the extrinsic incubation period in models of mosquito-borne disease transmission and control. by Steve E Bellan

“…Nearly all mathematical models of vector-borne diseases have assumed that vectors die at constant rates. …”
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A Data-Driven Framework for Accelerated Modeling of Stacking Fault Energy from Density of States Spectra by Md Tohidul Islam, Scott R. Broderick

“…The second part of this work focuses on the predictive modeling of SFE, where a machine learning model trained on UMAP-reduced features achieved high accuracy (R² = 0.86, MAE = 15.46 mJ/m²). …”
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Driver identification in advanced transportation systems using osprey and salp swarm optimized random forest model by Akshat Gaurav, Brij B. Gupta, Razaz Waheeb Attar, Ahmed Alhomoud, Varsha Arya, Kwok Tai Chui

“…The proposed model achieves an accuracy of 92%, a precision of 91%, a recall of 93%, and an F1-score of 92%, significantly outperforming traditional machine learning models such as XGBoost, CatBoost, and Support Vector Machines. …”
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A text classification method based on a convolutional and bidirectional long short-term memory model by Hai Huan, Zelin Guo, Tingting Cai, Zichen He

“…First, the text is vectorised using the Glove model in the embedding layer. Then, the vector text is sent to the Multiscale Convolutional Neural Network (MCNN) and the Bidirectional Long Short-Term Memory network (Bi-LSTM) respectively. …”
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Machine Learning-Based Modelling and Predictive Maintenance of Turning Operation under Cooling/Lubrication for Manufacturing Systems by Gurpreet Singh, Jothi Prabha Appadurai, Varatharaju Perumal, K. Kavita, T. Ch Anil Kumar, DVSSSV Prasad, A. Azhagu Jaisudhan Pazhani, K. Umamaheswari

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Modeling suction of unsaturated granular soil treated with biochar in plant microbial fuel cell bioelectricity system by K. C. Onyelowe, Ahmed M. Ebid, Rosa Belén Ramos Jiménez, Viroon Kamchoom, M. Vishnupriyan, Krishna Prakash Arunachalam

“…Additionally, different machine learning models such as the “Gradient Boosting (GB)”, “CN2 Rule Induction (CN2)”, “Naive Bayes (NB)”, “Support vector machine (SVM), “Stochastic Gradient Descent (SGD)”, “K-Nearest Neighbors (KNN)”, “Tree Decision (Tree)”, “Random Forest (RF)”, and “Response Surface Methodology” (RSM), have been developed to predict SWCC based on soil suction, electric current, electrical potential, volumetric water content, temperature, and bulk density. …”
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Enhancing Software Sustainability: Leveraging Large Language Models to Evaluate Security Requirements Fulfillment in Requirements Engineering by Ahmad F. Subahi

“…Future work will explore hybrid approaches to enhance scalability and accuracy.…”
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Computational intelligence analysis on drug solubility using thermodynamics and interaction mechanism via models comparison and validation by Ahmad J. Obaidullah, Wael A. Mahdi

“…Four models—Gaussian Process Regression (GPR), Support Vector Regression (SVR), Bayesian Ridge Regression (BRR), and Kernel Ridge Regression (KRR)—are evaluated. …”
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Mathematical Modeling of Full Tooth Surface of Spiral Bevel Gear based on the Digital Closed Loop Manufacturing by Huang Denghong

“…Based on the machining principle of spiral bevel gears and according to the relative position and relative motion relationship between the gear blank and the cutting tool,considering the cutter tilt modification and roll ratio modification motion,and using the method of vector operation,the mathematical model of working tooth surface and the fillet is established. …”
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Adaptive ensemble techniques leveraging BERT based models for multilingual hate speech detection in Korean and english by Seohyun Yoo, Eunbae Jeon, Joonseo Hyeon, Jaehyuk Cho

“…Parallel Model Fusion (PMF) requires the results of BERT-based models and a final estimator called meta-learner. …”
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Feature Variable Selection Based on VIS-NIR Spectra and Soil Moisture Content Prediction Model Construction by Nan Zhou, Jin Hong, Bo Song, Shichao Wu, Yichen Wei, Tao Wang

“…To forecast the moisture content of loess on the soil surface, models like partial least squares regression (PLSR), support vector machine (SVM), and random forest (RF) were created. …”
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Characterizing the Impact of Physical Activity on Patients with Type 1 Diabetes Using Statistical and Machine Learning Models by David Chushig-Muzo, Hugo Calero-Díaz, Himar Fabelo, Eirik Årsand, Peter Ruben van Dijk, Cristina Soguero-Ruiz

“…Second, we evaluate the effectiveness of machine learning (ML) models, including logistic regression, K-nearest neighbors, and support vector machine, to automatically detect PA in T1D individuals using glucose measurements. …”
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ATTRIBUTION OF MEDIA TEXTS BASED ON A TRAINED NATURAL LANGUAGE MODEL AND LINGUISTIC ASSESSMENT OF IDENTIFICATION QUALITY by Vladimir A. Klyachin, Ekaterina V. Khizhnyakova

“…The goal of our work is to build a model of the language of media messages, assess the quality and identify detection errors caused by the linguistic characteristics of texts. …”
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Implementation of a Conditional Latent Diffusion-Based Generative Model to Synthetically Create Unlabeled Histopathological Images by Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, Ahmad Kamal Nasution, Muhammad Alqaaf, Md. Altaf-Ul-Amin, Shigehiko Kanaya

“…In this work, we investigate the application of a conditional latent diffusion model in the healthcare domain. …”
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Research on Multi-Factor Coastal Waterway Depth Prediction and Application Based on Attention-Enhanced LSTM Model by LING Ganzhan, HAN Yu, WANG Jiawei, JIE Weiwei, TANG Ruikai, HU Jiakai, LIU Xiang, LIANG Guangyue, CAO Lu, LIANG Ming

“…In addition, when compared to a single feature vector model, the three-feature vector combination (daily rainfall, tidal flow speed, and tidal water level) resulted in an MAE error of no more than 0.14m and an R² coefficient of no less than 0.99, substantially improving the model's accuracy and stability for predicting waterway depth under complex coastal hydrological conditions. …”
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Machine Learning-Based Prediction Model for Multidrug-Resistant Organisms Infections: Performance Evaluation and Interpretability Analysis by Zhao W, Sun P, Li W, Shang L

“…SHAP analysis provided both global and local interpretability.Results: Among 825 eligible cases (375 MDRO infections), the Random Forest model exhibited the highest performance (AUC = 0.83, accuracy = 76.7%). …”
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A Neural-Symbolic Approach to Extract Trust Patterns in IoT Scenarios by Fabrizio Messina, Domenico Rosaci, Giuseppe M. L. Sarnè

“…Nevertheless, this scalar approach within the IoT context holds a few limitations that emphasize the need for models that can capture complex trust relationships beyond vector-based representations. …”
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