Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

“…The hybrid schema of this work treats the deficiencies of the previous approaches, such as incorporating CNN-based effective feature extraction, Transformer networks for developing attention mechanisms, and finally the fine decision boundary of the support vector machine. Further, we refine this process via unsupervised clustering for the purpose of enhancing the visualisation of such a procedure. …”
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Improved SVM for Fault Diagnosis of Main Converter of Locomotive by 钟燕科

“…Making use of wavelet analysis to process the output voltage, the fault feature had been extracted and the feature vector had been constructed. …”
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Non-Vertical Well Trajectory Design Based on Multi-Objective Optimization by Xiaowei Li, Yu Li, Yang Wu, Zhaokai Hou, Haipeng Gu

“…The optimization and control of the wellbore trajectory is one of the important technologies to improve drilling efficiency, reduce drilling cost, and ensure drilling safety in the process of modern oil and gas exploration and development. …”
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Predicting Startup Success Using Machine Learning Approach by Icha Wahyu Kusuma Ningrum, Farid Ridho, Arie Wahyu Wijayanto

“…We carried out the classification using four methods: Random Forest, Support Vector Machines (SVM), Gradient Boosting, and K-Nearest Neighbor (KNN). …”
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An IoT-Enabled mHealth Sensing Approach for Remote Detection of Keratoconus Using Smartphone Technology by Behnam Askarian, Amin Askarian, Fatemehsadat Tabei, Jo Woon Chong

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Egg appearance quality detection based on CNN-SVM model by QI Ge, ZHAO Feng, LI Wanning

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Advancing Taxonomy with Machine Learning: A Hybrid Ensemble for Species and Genus Classification by Loris Nanni, Matteo De Gobbi, Roger De Almeida Matos Junior, Daniel Fusaro

“…In this paper, we propose a novel ensemble approach that integrates neural networks with support vector machines (SVM). Each animal is represented by an image and its DNA barcode. …”
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Handheld NIR Spectroscopy Combined with a Hybrid LDA-SVM Model for Fast Classification of Retail Milk by Francesco Maria Tangorra, Annalaura Lopez, Elena Ighina, Federica Bellagamba, Vittorio Maria Moretti

“…The EU market offers different types of milk, distinguished by origin, production method, processing technology, fat content, and other characteristics, which are often detailed on product labels. …”
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Research on the Sharing Control Method of Anemometer Based on Wind Direction Correlation Coefficient of Wind Turbine by WEN Kun, WAN Yubin, HU Kaikai, ZHANG Jiayou, CHEN Ya'nan, LI Kecheng

“…An anemometer sharing control method based on wind direction correlation coefficient is proposed in this paper according to the wind speed and direction sharing technology concept of wind turbine. Firstly, the wind vector average method is used to preprocess the wind direction sequence of adjacent fans to solve zero-crossing problem of wind direction sequence.Then, using regression analysis method based on Pearson correlation coefficient theory, the wind direction sequence of adjacent fans is further processed to form a list of wind direction correlation coefficients of defective fans and establish a shared fan group, which are used to predict the wind direction of defective fans. …”
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Improved Remote Photoplethysmography Using Machine Learning-Based Filter Bank by Jukyung Lee, Hyosung Joo, Jihwan Woo

“…The MLFB algorithm determines the optimal spectral band for extracting information on cardiovascular activity and reconstructing an rPPG signal using a support vector machine. The proposed approach was validated with an open dataset, achieving a 35.5% (i.e., resulting in a mean absolute error of 2.5 beats per minute) higher accuracy than those of conventional methods. …”
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Hyperdimensional computing in biomedical sciences: a brief review by Fabio Cumbo, Davide Chicco

“…Hyperdimensional computing (HDC, also known as vector-symbolic architectures—VSA) is an emerging computational paradigm that relies on dealing with vectors in a high-dimensional space to represent and combine every kind of information. …”
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The Use of Neural Networks in the Diagnosis of Heart Failure Via the Analysis of Medical Data by Valentino Blanco, Aitana Iglesias

“…The crux of effective management is in the process of decision-making, which is contingent upon the availability of information and effective communication. …”
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Simultaneous isolation and parallel analysis of genomic DNA and total RNA: A comprehensive approach by Jeremy Rouse, Han Wei, Abigail Annas, David Scott, Divya Bhagchandani, Clayton Beard

“…The efficiency of this process hinges on the vector copy number (VCN) and transgene expression. …”
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Bearing Response Prediction in Hydrothermal Aged Carbon Fiber Reinforced Epoxy Composite Joints Using Machine Learning Techniques by Mohit Kumar, Govind Vashishtha, Babita Dhiman, Sumika Chauhan

“…The machine learning technique, support vector regression is trained and evaluated to assess their accuracy and reliability in predicting bearing response. …”
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Comparison of Rating-based and Inset Lexicon-based Labeling in Sentiment Analysis using SVM (Case Study: GoBiz Application Reviews on Google Play Store) by Hiliah Firda, Pacu Putra, Nabila Rizky Oktadini, Putri Eka Sevtiyuni, Allsela Meiriza

“…It compares two labeling methods—Rating-Based and Inset Lexicon—and evaluates them using the Support Vector Machine (SVM) algorithm. The analysis process includes data selection, text preprocessing, data transformation using TF-IDF, SVM implementation with 10-fold cross-validation, and result visualization through word clouds. …”
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Computational hybrid analysis of drug diffusion in three-dimensional domain with the aid of mass transfer and machine learning techniques by Mohammed Alqarni, Ali Alqarni

“…These findings have implications for various applications such as environmental monitoring, pollutant dispersion modeling, and chemical process optimization.…”
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Fast estimation of patient‐specific organ doses from abdomen and head CT examinations without segmenting internal organs using machine learning models by Wencheng Shao, Liangyong Qu, Xin Lin, Ying Huang, Weihai Zhuo, Haikuan Liu

“…This study introduces a method that uses support vector regression (SVR) models trained on skin outline radiomic features to predict organ doses without organ segmentation, thus streamlining the process for clinical use. …”
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Microbiome of <i>Hyalomma dromedarii</i> (Ixodida: Ixodidae) Ticks: Variation in Community Structure with Regard to Sex and Host Habitat by Nighat Perveen, Alejandro Cabezas-Cruz, Daniil Iliashevich, Lianet Abuin-Denis, Olivier Andre Sparagano, Arve Lee Willingham

“…A total of 40 ticks (male (15), female (15), and nymph (10)) were selected from tick samples collected from camels and processed for genomic DNA and next-generation sequencing using the Illumina MiSeq platform. …”
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Bayesian-Optimized Multi-Task Gaussian Process Regression With Composite Kernels for Soybean Oil Futures Forecasting by Hui-Dong Yin, Yi-Yang Li

“…This study addresses the forecasting of soybean oil prices in China&#x2019;s wholesale markets by developing a Bayesian-optimized Multi-Task Gaussian Process Regression (MTGPR) framework. Traditional econometric models and machine learning approaches often struggle with non-stationary data and uncertainty quantification, while existing Gaussian process applications in agricultural markets remain underexplored. …”
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Advanced signal processing algorithm for fault classification and localization in VSC-HVDC based Offshore wind farm by Rehana Perveen

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