Breast Tumor Diagnosis Based on Molecular Learning Vector Quantization Neural Networks by Chun Huang, Jiaying Shao, Baolei Peng, Qingshuang Guo, Panlong Li, Junwei Sun, Yanfeng Wang

“…Here, a molecular learning vector quantization neural network (LVQNN) model based on DNA strand displacement (DSD) technology for breast tumor diagnosis is developed. …”
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Bicistronic Vector Expression of Recombinant Jararhagin-C and Its Effects on Endothelial Cells by Karla Fernanda Ferraz, Lhiri Hanna De Lucca Caetano, Daniele Pereira Orefice, Paula Andreia Lucas Calabria, Maisa Splendore Della-Casa, Luciana Aparecida Freitas-de-Sousa, Emidio Beraldo-Neto, Sabri Saeed Sanabani, Geraldo Santana Magalhães, Patricia Bianca Clissa

“…The aim of this work was to obtain the recombinant form of JarC and to test its biological activity. …”
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C-parameter version of robust bounded one-class support vector classification by Junyou Ye, Zhixia Yang, Yongxing Hu, Zheng Zhang

“…Abstract $$\nu$$ -one-class support vector classification ( $$\nu$$ -OCSVC) has garnered significant attention for its remarkable performance in handling single-class classification and anomaly detection. …”
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Performance Evaluation of Support Vector Machine and Stacked Autoencoder for Hyperspectral Image Analysis by Brahim Jabir, Bendaoud Nadif, Isabel De la Torre Diez, Helena Garay, Irene Delgado Noya

“…We wanted to understand which approach works better under different real-world conditions that researchers and practitioners face. …”
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A Novel Sea Surface Temperature Prediction Model Using DBN-SVR and Spatiotemporal Secondary Calibration by Yibo Liu, Zichen Zhao, Zhe Zhang, Yi Yang

“…The model combines the nonlinear feature extraction of a deep belief network (DBN) with the high-precision regression of support vector regression (SVR), enhanced by spatiotemporal secondary calibration (SSC) to better capture SST variation patterns. …”
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An ensemble deep learning model for author identification through multiple features by Yuan Zhang

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Improving adequacy of mechanical-mathematical model of rotor dynamics on the balancing machine by Oleg A. Polushkin, Oleg O. Polushkin, I. Masmoud Fofana

“…As a result of the investigations, first, the necessity of applying vector influence coefficient values of the rotor model unbalance in each of the correction planes on the vibrations of the rotor poles on the balancer is proved. …”
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A Comprehensive Investigation into the Accuracy of Soft Computing Tools for Downscaling Precipitation Data Extracted from Climate Models by Shalaka Shah, Shreenivas Londhe

“…This study will provide the audience with an understanding of the capabilities of soft tools such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Model Trees (MT), and Multi-Gene Genetic Programming (MGGP) as a statistical downscaling tool. …”
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Collider imprint of vector-like leptons in light of anomalous magnetic moment and neutrino data by Parham Dehghani, Mariana Frank, Benjamin Fuks

“…Our work hence sheds light on the potential implications of vector-like leptons in resolving discrepancies inherent to the Standard Model, while also offering insights into experimental avenues for further exploration.…”
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ALGORITHMIC AND PROGRAM IMPLEMENTATION OF THE PLAGIARISM DEFINITION IN LEARNING MANAGEMENT SYSTEMS by Y. B. Popova, A. V. Goloburda

“…To achieve this goal, it is necessary to solve a range of problems related to the choice of a method for determining plagiarism, its algorithmization and software implementation. The work deals with the methods of shingles, super-shingles, signature methods, vector models of text representation, as well as cluster analysis of text information. …”
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Entanglement detection with quantum support vector machine (QSVM) on near-term quantum devices by Mahmoud Mahdian, Zahra Mousavi

“…This study presents the implementation of quantum support vector machines (QSVMs) on IBM quantum devices to identify and classify entangled states. …”
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Multi-Vector Diversification Concept for Russian Oil and Gas Company: Prerequisistes, Trends, Opportunities by K. V. Simonov, A. O. Buriachenko

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Efficient Support Vector Regression for Wideband DOA Estimation Using a Genetic Algorithm by Yonghong Zhao, Gang Zheng, Junlong Wang, Jisong Liu, Shuxin Dong, Jing Xin

“…High-precision direction of arrival (DOA) of wideband signals is a very important technology in the field of radar and communication. In this work, we propose an efficient support vector regression (SVR) architecture via a genetic algorithm (GA) for wideband DOA estimation, which exhibits high estimation performance and generalization performance. …”
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Enhanced Deep Autoencoder-Based Reinforcement Learning Model with Improved Flamingo Search Policy Selection for Attack Classification by Dharani Kanta Roy, Hemanta Kumar Kalita

“…The presented model is simulated in the Python platform and evaluated using the UNSW-NB15, CICIDS2017, and NSL-KDD datasets. …”
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NOVA: A Retrieval-Augmented Generation Assistant in Spanish for Parallel Computing Education with Large Language Models by Gabriel A. León-Paredes, Luis A. Alba-Narváez, Kelly D. Paltin-Guzmán

“…This work presents the development of NOVA, an educational virtual assistant designed for the Parallel Computing course, built using a Retrieval-Augmented Generation (RAG) architecture combined with Large Language Models (LLMs). …”
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Hybridizing Grid Search and Support Vector Regression to Predict the Compressive Strength of Fly Ash Concrete by Fei Tang, Yanqi Wu, Yisong Zhou

“…To this end, hybrid machine learning combines the SVR model and grid search (GS), namely, the GS-SVR model was proposed to predict the compressive strength of concrete and sensitivity analysis in this work. …”
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Synthesis Based on Linearization of Vector Speed Control of an Induction Motor without a Speed Sensor by O. F. Opeiko

“…The aim of the work was parametric synthesis of vector sensorless (i. e. without speed sensor) control of an electric drive with an induction motor. …”
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Artificial Flora Algorithm-Based Feature Selection With Support Vector Machine for Cardiovascular Disease Classification by M. M. Asha, G. Ramya

“…Accurately categorizing medical information is crucial for determining effective cardiac treatment options, especially as the volume of data grows and feature selection becomes increasingly challenging. This work proposes a model to identify the presence of Cardiovascular Disease based on various patient features, aiming to enhance prediction accuracy through a powerful feature selection method. …”
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Application and Analysis of Random Forest and Support Vector Classification in Risk Prediction of Childhood Obesity and Hyperuricemia by Wang Y, Shi S, Wei X, Wu Y, Shi Y, Cai J

“…Future studies will explore the integration of metabolomic data and ensemble approaches to further enhance model performance and clinical applicability.Keywords: childhood obesity, hyperuricemia, machine learning, random forest, support vector classification, SHAP…”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

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