Research of the Combined Trajectory Planning of Descartes Space and Joint Space by Lai Xiao, Liu Yong, Luo Wenguo, Dai Yanxia, Zeng Han

“…Through the closed loop vector method,kinematics equation is established and the space trajectory is fitted based B spline function model,the motion curve of the joint space planning and the motion curve of Descartes space planning and the motion curve of combined space planning are obtained. …”
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PENGENALAN EKSPRESI RAUT WAJAH BERBASIS JARINGAN SARAF TIRUAN BACKPROPAGATION DENGAN METODE PRINCIPAL COMPONENT ANALYSIS by Harizahayu Harizahayu

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Analytical Estimation of Induced Voltage in Rotating Electrical Machines by Marius Meiswinkel, Amir Ebrahimi, Anjali Biju

“…However, even when using FEM software, this voltage estimation is a post-process calculation based on pre-calculated flux densities or vector potentials. …”
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Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM by Dongmei Zhu

“…Abstract This study aims to enhance computers’ ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. It proposes a metaphor recognition algorithm that combines a Convolutional Neural Network (CNN) with a Support Vector Machine (SVM). …”
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Research on the Prediction of Pipelines Corrosion Rate Based on GA-LSSVM by CHEN Yong-hong, SU Yong-sheng, HU Ping

“…Corrosion rate is an important characteristic parameter to reflect the corrosion dynamics process of pipeline.In order to accurately evaluate the long-term operation reliability and remaining life of pipeline, the prediction of corrosion rate is particularly important.Least squares support vector machine(LSSVM)is a method based on machine learning, which is often used in classification and prediction research.Since penalty parameters γ and kernel parameters σ2 are two important parameters of LSSVM, the value of these two parameters can only be obtained by experience in calculation, causing a great impact on the calculation results.In this paper, the genetic algorithm(GA)was used to optimize the parameters, the GA-LSSVM prediction model was built and the model was applied to the prediction of pipeline corrosion rate.Compared with the results of other prediction models, the results showed that the accuracy of GA-LSSVM model and prediction results were relatively higher, which could realize the prediction of pipeline corrosion rate.…”
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Citizen Science and Multimedia Didactic Resources: Knowledge of Mosquito-Borne Diseases in an Urban Area of Southwestern Colombia by Francisco Javier Bedoya-Rodríguez, Carlos Eduardo Guevara-Fletcher, Jonathan S. Pelegrin

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Title not available by Bouali, Fakhreddine, Fedala, Semchedine, André, Hugo, Felkaoui, Ahmed

“…These methods require the construction of a Feature Vector (FV) generally composed of indicators calculated from time sampled vibration signals. …”
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PLM-ATG: Identification of Autophagy Proteins by Integrating Protein Language Model Embeddings with PSSM-Based Features by Yangying Wang, Chunhua Wang

“…Since the autophagic process is tightly regulated by the coordination of autophagy-related proteins (ATGs), precise identification of these proteins is essential. …”
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Comparative Study of SVM, KNN, and Naïve Bayes for Sentiment Analysis of Religious Application Reviews by Heti Aprilianti, Khothibul Umam, Maya Rini Handayani

“…This study aims to evaluate and compare the performance of three machine learning algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (K-NN), and Naïve Bayes—for sentiment classification of user reviews on the NU Online application in the Google Play Store. …”
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Harnessing SVM for Sentiment Analysis: Insights from Gojek's Instagram Engagement by Muhammad Juan Savero, Ali Ibrahim, Yadi Utama, Endang Lestari

“…This research analyzes Gojek user sentiment on Instagram using Support Vector Machine (SVM). Data is obtained through web scraping, then processed through text cleaning, tokenization, common word removal, and stemming. …”
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Rolling Bearing Fault Diagnosis Method Based on Fusion of CNN and CSSVM by LI Yunfeng, LAN Xiaosheng, SHEN Hongchang, XU Tongle

“…Finally, the extracted feature vectors were input into the support vector machine classification layer with optimized parameters by cuckoo search algorithm to realize the fault classification of rolling bearings. …”
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ALGORITHMIC AND PROGRAM IMPLEMENTATION OF THE PLAGIARISM DEFINITION IN LEARNING MANAGEMENT SYSTEMS by Y. B. Popova, A. V. Goloburda

“…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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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…Firstly, SqueezeNet enables efficient feature extraction from segmented fundus images with minimal computational complexity, ensuring that critical retinal features are captured effectively. The classification process, QCOA optimizes the Support Vector Machine (SVM) parameters and performs feature selection. …”
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Physiological Signals as Predictors of Mental Workload: Evaluating Single Classifier and Ensemble Learning Models by Nailul Izzah, Auditya Purwandini Sutarto, Ade Hendi, Maslakhatul Ainiyah, Muhammad Nubli bin Abdul Wahab

“… With a growing emphasis on cognitive processing in occupational tasks and the prevalence of wearable sensing devices, understanding and managing mental workload has broad implications for safety, efficiency, and well-being. …”
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Significance of vertical transmission of arboviruses in mosquito-borne disease epidemiology by Oliver Chinonso Mbaoma, Stephanie Margarete Thomas, Carl Beierkuhnlein

“…Vertical transmission (VT) which refers to a process where infected mosquitoes transmit viruses to their offsprings have been often overlooked in MBD epidemiology. …”
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Applications of remote sensing and GIS techniques for identifying of the plastic waste from space: Evidence from Khulna city corporation in Bangladesh by Md Nahid Ferdous, Mohammad Ismail Hossain, Mohammed Manik

“…A total of 60 samples have been taken in this study, out of which 80% (48) have been taken as training samples and the remaining 20% (12) have been taken as testing samples, and the entire process was done using ArcGIS 10.8. This analysis revealed that algorithms used in this study successfully identify plastic waste on land, and between two algorithms, support vector classification achieves the highest accuracy (93%). …”
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First Report on the Molecular Detection and Characterization of <i>Rickettsia felis</i> in Laelapidae (Acari: Mesostigmata) Mites in Malaysia by Hiryahafira Mohamad Tahir, Faraliana Che Lah Ernieenor, Suhaili Zainal Abidin, Vishalani Vishnu Narainasamy, Mariana Ahamad

“…These pathogens are typically transmitted by arthropod vectors, such as ticks, mesostigmatid mites, and fleas. …”
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Towards Automated Quality Control in Industrial Systems: Developing Markov Decision Process Model for Optimized Decision-Making by Katerina Mitkovska-Trendova, Robert Minovski, Verica Bakeva, Simeon Trendov, Dimitar Bogatinov

“…The research employs a mathematical model that integrates vector random processes, each representing critical factors such as machine condition, operator behaviour, tools, and materials. …”
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Identifying presence or absence of grizzly and polar bear cubs from the movements of adult females with machine learning by Erik M. Andersen, Justin G. Clapp, Milan A. Vinks, Todd C. Atwood, Daniel D. Bjornlie, Cecily M. Costello, David D. Gustine, Mark A. Haroldson, Lori L. Roberts, Karyn D. Rode, Frank T. van Manen, Ryan R. Wilson

“…Methods We trained support vector machines (SVMs) with eight variables derived from telemetry data of female grizzly (2000–2022) and polar bears (1985–2016) with or without cubs during seven periods with lengths ranging from 5 to 60 days starting at den departure. …”
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Automated Tomato Leaf Disease Detection Using Image Processing: An SVM-Based Approach with GLCM and SIFT Features by Rashid Khan, Nasir Ud Din, Asim Zaman, Bingding Huang

“…To support specialists in accurately identifying and managing these diseases, we propose an advanced automatic system for detecting and identifying tomato leaf diseases using sophisticated image processing techniques. Therefore, we proposed an approach that employs robust feature extraction methods, including the gray level co-occurrence matrix (GLCM) and scale-invariant feature transform (SIFT), coupled with a support vector machine (SVM) for adequate classification. …”
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