Computer Modelling of Yarn Winding on Conical Bobbins by Volodymyr Dvorzhak, Mykola Rubanka, Alla Rubanka, Oleh Polishchuk

“… The article presents the results of the computer modelling of yarn winding on conical bobbins based on the analytical method of constructing tubular-shaped surfaces as a partial case of channel surfaces using the vector algebra apparatus. …”
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Advanced Mineral Deposit Mapping via Deep Learning and SVM Integration With Remote Sensing Imaging Data by Nazir Jan, Nasru Minallah, Madiha Sher, Muhammad Wasim, Shahid Khan, Amal Al‐Rasheed, Hazrat Ali

“…Subsequently, we build a hybrid model combining deep CNN layers with a support vector machine (SVM). …”
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FUZZY MODELING OF VERBAL INFORMATION FOR PRODUCTION SYSTEMS by Anna Bakurova, Mariia Pasichnyk, Elina Tereschenko

“…A model based on an acyclic oriented graph is considered as a generalization.  …”
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Enhanced Kidney Stone Detection and Classification Using SVM and LBP Features by Hawkar K. Hama, Hamsa D. Majeed, Goran Saman Nariman

“…The Local Binary Pattern (LBP) technique, combined with the support vector machine (SVM) algorithm serves as the primary components of the proposed model. …”
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Hybrid IoT-CAD system: optimized feature selection based gated recurrent residual deep learning for cyber attack detection in IoT networks by Susheela Vishnoi, Sunil Kumar, Saikat Samanta

“…This hybrid model supports improved detection accuracy and resilience for protecting IoT networks from cyber threats. …”
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Predictive analytics in customer behavior: Anticipating trends and preferences by Hamed GhorbanTanhaei, Payam Boozary, Sogand Sheykhan, Maryam Rabiee, Farzam Rahmani, Iman Hosseini

“…In the current work, various machine learning algorithms such as Decision Tree (DT), Random Forest (RT), Logistic Regression (LR), Support Vector Machines (SVM), and gradient boosting are used to predict customer behavior. …”
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rhBNN+ Comprehensive Detections and Analyses of the Human Body Temperatures and Sounds by the Same Smart Mask by Bingcan Liao, Pin Sun, Shuyi Chen, Rihong Huang, Junyu Yang, Guofeng Li, Chengzhi Lv, Nan Zhu, Shui Guan, Hailong Liu, Rong Liu, Ali Mansouri, Changkai Sun

“…The SVM achieved 84.3% accuracy for sound data classification, while the Lion algorithm−optimized SVM achieved an even higher accuracy of 93.6%. Future work aims to establish a reliable data collection tool that will serve as the foundation for developing an intelligent human body analysis model called the real human body neural network (rhBNN+).…”
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Debiased Learning via Composed Conceptual Sensitivity Regularization by Sunghwan Joo, Taesup Moon

“…To train classifiers that are not biased towards spurious features, recent research has leveraged explainable AI (XAI) techniques to identify and modify model behavior. Specifically, Concept Activation Vectors (CAVs), which indicate the direction toward specific concepts in the embedding space, were used to measure and regularize the conceptual sensitivity of the classifier, thereby reducing its reliance on spurious features. …”
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Impact of computing platforms on classifier performance in heart disease prediction by Beenish Ayesha Akram, Muhammad Irfan, Amna Zafar, Sidra Khan, Rubina Shaheen

“…Prediction and classification, a supervised learning technique in machine learning, addresses various challenges related to finding useful patterns present in data. This work explores how different computing platforms influence the accuracy of classification results when employing the same models. …”
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Research on collision detection of robot outer surface based on six-dimensional force sensor by WANG Zhijun, WANG Yunyi, LI Zhanxian

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TSB-Forecast: A Short-Term Load Forecasting Model in Smart Cities for Integrating Time Series Embeddings and Large Language Models by Mohamed Mahmoud Hasan, Neamat El-Tazi, Ramadan Moawad, Amany H. B. Eissa

“…In smart cities, energy management systems are essential for efficient resource utilization, enhanced operational efficiency, and sustainability promotion. This work presents a novel load forecasting model, TSB-Forecast (Time Series BERT), a hybrid machine learning model aiming to improve short-term electrical demand forecasting by integrating structured and unstructured data. …”
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Domain-specific text embedding model for accelerator physics by Thorsten Hellert, João Montenegro, Marco Venturini, Andrea Pollastro

“…In this work, we introduce AccPhysBERT, a sentence embedding model fine-tuned specifically for accelerator physics. …”
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Applying ANFIS and LSSVM Models for the Estimation of Biochar Aromaticity by Ganggang Pan, Haoyan Dong, Maryam Karimi Nouroddin

“…To this end, two machine learning models, including adaptive neurofuzzy inference system (ANFIS) and least-squares support vector machine (LSSVM), were used to predict this constant form 98 dataset gathered from earlier reported sources. …”
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The structure of the local detector of the reprint model of the object in the image by A. A. Kulikov

“…Currently, methods for recognizing objects in images work poorly and use intellectually unsatisfactory methods. …”
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Web application firewall based on machine learning models by Muhammed Ersin Durmuşkaya, Selim Bayraklı

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Attitudes of Doctors and Nurses toward the Chronic Care Model by Rolando Bonal Ruiz, Meibis Poll Cabrera

“…<br /><strong>Results:</strong> the attitudinal results correspond with the actions assessed in each component of the model, being the most common barriers: the lack of awareness and training on the new approaches to care of these patients, work overload created by other programs such as the maternal-child and vector control programs, uncertainties on the effectiveness of patient education and ignorance of the practice guidelines. …”
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Models, systems, networks in economics, engineering, nature and society by A.A. Sapogov

“…This article proposes an approach to determining management priorities for processing and resolving streaming requests within IT projects based on the aggregation of a number of quality indicators. As part of the work, multi-vector quality characteristics were established that reflect the state of the process of accepting a service request for processing, presenting them in the form of vectors of values with criterion indicators. …”

PNN-based Rockburst Prediction Model and Its Applications by Yu Zhou, Tingling Wang

“…Some main control factors, such as rocks’ maximum tangential stress, rocks’ uniaxial compressive strength, rocks’ uniaxial tensile strength, and elastic energy index of rock are chosen as the characteristic vector of PNN. PNN model is obtained through training data sets of rock burst samples which come from underground rock project in domestic and abroad. …”
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On the Construction of Mathematical Models of the Membrane Theory of Convex Shells by E. V. Tyurikov

“…At the same time, shells with a piecewise smooth (ribbed) lateral surface were considered for the first time. The work objective was to find classes of shells for which it is possible to build meaningful mathematical models.Materials and Methods. …”
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Prediction model for the selection of patients with glioma to proton therapy by Jesper Folsted Kallehauge, Siri Grondahl, Camilla Skinnerup Byskov, Morten Høyer, Slavka Lukacova

“…The dataset was split into training (n = 37, period 2019–2022) and test (n = 12, period 2023) cohorts. Prediction models were built using logistic regression algorithms and support vector machines (SVMs) and evaluated using the area under the precision-recall curve (AUC-PR). …”
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