Signal-piloted processing and machine learning based efficient power quality disturbances recognition. by Saeed Mian Qaisar

“…It can result in a huge amount of unnecessary information being collected, processed, and transmitted. Consequently, needless processing activities, power consumption and latency can occur. …”
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Research and implementation of a full-process academic early warning and tracking evaluation system by Li Qipeng, Zeng Songwei

“…This paper uses Particle Swarm Optimization (PSO) to optimize Support Vector Machine (SVM), and combines Web and mini-program technology to implement a whole-process academic warning tracking and evaluation system, which effectively improves the accuracy and timeliness of warnings, filling in the gaps of traditional academic warning systems. …”
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Real-Time Detection and Process Status Integration System for High-Pressure Gas Leakage by Nian-Ze Hu, Hao-Lun Huang, Chun-Min Tsai, Yen-Yu Wu, You-Xin Lin, Chih-Chen Lin, Po-Han Lu

“…To promptly recover gas during leakage incidents, the efficiency of the gas filling process was improved by reducing resource wastage. …”
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Machine Learning-based for Automatic Detection of Corn-Plant Diseases Using Image Processing by Geofrey Prudence Baitu, Y. Benal Öztekin, Omsalma Alsadig Adam Gadalla, Khaled Adil Dawood Idress

“…The highest accuracy scores were obtained with support vector machine and artificial neural networks, respectively.…”
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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft by Yanhui Guo, Yanpeng Chen, Peibo Li, Xinfu Chi, Yize Sun

“…In order to solve the optimization problem, 108 sets of process experiments were designed, and then the experimental data were used to train a Back Propagation Neural Network (BPNN), a Least Squares Support Vector Machine (LSSVM), and Random Forest (RF) to obtain the best prediction model for the process parameters. …”
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Implementing and evaluating the quality 4.0 PMQ framework for process monitoring in automotive manufacturing by Fathy Alkhatib, Mohamed Allam, Vikas Swarnakar, Juman Alsadi, Maher Maalouf

“…The study relied on various ML algorithms, such as Decision Trees (DT), Random Forest (RF), Gradient Boosting Machine (GBM), Logistic Regression (LR), Support Vector Machine (SVM), and Artificial Neural Networks (ANN), to classify and predict defects in engine valves during manufacturing processes. …”
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Automated detection and identification of white-backed planthoppers in paddy fields using image processing by Qing YAO, Guo-te CHEN, Zheng WANG, Chao ZHANG, Bao-jun YANG, Jian TANG

“…A new three-layer detection method was proposed to detect and identify white-backed planthoppers (WBPHs, Sogatella furcifera (Horváth)) and their developmental stages using image processing. In the first two detection layers, we used an AdaBoost classifier that was trained on a histogram of oriented gradient (HOG) features and a support vector machine (SVM) classifier that was trained on Gabor and Local Binary Pattern (LBP) features to detect WBPHs and remove impurities. …”
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Spectral feature modeling with graph signal processing for brain connectivity in autism spectrum disorder by Ayesha Jabbar, Huang Jianjun, Muhammad Kashif Jabbar, Khalil ur Rehman, Anas Bilal

“…These are classified using a Support Vector Machine (SVM) with a radial basis function (RBF) kernel. …”
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Decision-making power enhances investors’ neural processing of persuasive message in partnership investment by Jianbiao Li, Peikun Chen, Jingjing Pan, Chengkang Zhu

“…Furthermore, using a support vector machine (SVM) algorithm, the INS could accurately predict receivers’ adoption of persuasive messages when they held dominant decision-making power. …”
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Machine learning-based process quality control of screen-printed titanium dioxide electrodes by Anesu Nyabadza, Lola Azoulay-Younes, Mercedes Vazquez, Dermot Brabazon

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Extraction of phenotypic parameters of litchi based on image processing and three-dimensional point cloud by Haibo CHEN, Xinglan XIANG, Kangye GONG, Zhengxin LI, Shunhao HUANG, Chunxi LI, Xiaofeng CAI, Shan ZENG

“…According to the obtained litchi point cloud, the point cloud curvature and normal vector were calculated, and the mechanical damage area of litchi was identified. …”
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Immune status changes in patients with phlegmon in the maxillofacial region relation with purulent process prevalence by N. G. Barannik, S. D. Varzhapetyan, A. V. Sidoryako, Yu. S. Karabinova

“…Serum was dispensed at 0.3 ml. in plastic tubes, frozen and stored before use at minus 20°C. cytokines concentration was determined with commercial test systems OOO "cytokine" "Vector-Best" (St. Petersburg). The results were recorded according to absorbance measured in a spectrophotometer – analyzer Sunrise (Austria) at 450 nm. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…In this paper, a hybrid classifier incorporating Long Short-Term Memory (LSTM), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) is proposed and applied to diagnose congenital heart disease in children. …”
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Schmallenberg disease: literature review and epizootic situation in the world and in Russia by O. A. Burova, O. I. Zakharova, N. N. Toropova, E. A. Liskova, I. V. Yashin, A. A. Blokhin

“…In 2012-2013, the infection spread to the most part of Northwestern Europe. Insect vectors were the main mechanism for the spread of the disease. …”
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Impact of Thermal Variation on Egg Hatching and the Life Cycle of <i>Aedes</i> (<i>Protomacleaya</i>) <i>terrens</i> (Diptera: Culicidae) in a Laboratory Environment by Rayane Dias, Manuella Pereira Cerqueira Leite, Guilherme Sanches Corrêa-do-Nascimento, Gabriel Silva Santos, Cecilia Ferreira de Mello, Nathália Menezes de Almeida, Jeronimo Alencar

“…Evaluating the development process of mosquito species under the influence of temperature is essential for understanding their ecology and geographical distribution, as well as assessing their potential as vectors of pathogens. …”
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Study of the axial-vector and tensor resonant contributions to the $$D \rightarrow VP\ell ^+\nu _\ell $$ D → V P ℓ + ν ℓ decays based on SU(3) flavor analysis by Yi Qiao, Yue-Xin Liu, Yuan-Guo Xu, Ru-Min Wang

“…The branching ratios of the $$D \rightarrow M \ell ^+ \nu _\ell $$ D → M ℓ + ν ℓ , $$M \rightarrow VP$$ M → V P , and $$D\rightarrow M(M\rightarrow VP)\ell ^+\nu _\ell $$ D → M ( M → V P ) ℓ + ν ℓ decays are then predicted. We find that some processes receive both tensor and axial-vector resonant contributions, while other processes receive only axial-vector resonant contributions. …”
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On the ambiguity of mechanical power by V. D. Pavlov

“…Mechanical vibrations are widespread in the production processes. The drives of machines and mechanisms are mainly electromechanical, so mechanical reactive power is transformed into electrical reactive power of the network, impairing the quality of electricity. …”
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Research on blindsight technology for object recognition and attitude determination based on tactile pressure analysis by Chen Li, Li HuiJun, Song Aiguo

“…It then proposes a dimensionality reduction analysis method for vector force arrays, identifying the boundary force characteristics of the contact surface to decompose the 3D contact surface into separate force planes and reducing the angle dimension in the vector array to a two-dimensional scalar array that only includes the magnitude of the force, thus laying the data foundation for introducing convolutional neural networks (CNNs). …”
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The choice of the number of processing channels in the radiomonitoring equipment on the basis of adaptive multibeam antenna arrays by S. V. Kozlov

“…Using mathematical modeling the angle-frequency characteristics of the beams and the accuracy of direction finding of the useful signal in an adaptive multibeam antenna arrays (AMLAR) with spatial compensation of noise and sum-difference processing are investigated. It's shown that the required number of generated spatial channels for AMLAR is approximately twice as large as in MLAR without adaptive processing. …”
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From Prompt To Response: Understanding Chatgpt Language Processing Framework To Improve Efl Teaching by Nawel Bengrait

“…The present study analyzes ChatGPT language processing framework, centered on key components of prompting, tokenization, vectorization, transformer mechanism, and semantic analysis. …”
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