Design of Interactive Vocal Guidance and Artistic Psychological Intervention System Based on Emotion Recognition by Wenwen Mo, Yuan Yuan

“…This paper uses the vocal music emotion recognition algorithm to first train the interactive recognition network, in which the input is a row vector composed of different vocal music characteristics, and finally recognizes the vocal music of different emotional categories, which solves the problem of low data coupling in the artistic psychological intervention system. …”
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The use of metaverses as a tool for shaping the image of an educational institution for technological leadership in the educational field by S. V. Panasenko, D. V. Fedyunin, M. V. Mostovoy, S. E. Suvorova

“…Based on the results of the study, conclusions are made about the need to build a balanced educational policy of higher educational institutions in Russia to implement a vector for technological leadership with the use of the capabilities of virtual spaces of metaverses and the development of preventive measures to avoid the risks and dangers associated with this process. …”
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Groundwater fluoride modeling using an artificial neural network: a review by Neeta Kumari, Gaurav Kumar, Saahil Hembrom

“…Inputs are selected through statistical analysis. The modeling process is carried out using the “nntool” in MATLAB software. …”
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Electric Submersible Pump Fault Diagnosis Based on Laplacian Eigenmaps and Weighted Extreme Learning Machine by XU Zekun, FU Jun, GAO Xiaoyong, ZHANG Yu, LI Qiang, TAN Chaodong

“…The results show that the classification average accuracy, maximum accuracy, and G-mean of the algorithm proposed in this paper are improved by more than 10% on average compared with those of the support vector machine, decision tree, backpropagation (BP) algorithm, extreme learning machine, and weighted extreme learning machine, thus confirming the effectiveness of the proposed method.…”
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On Characteristics of Symbolic Execution in the Problem of Assessing the Quality of Obfuscating Transformations by Petr D. Borisov, Yury V. Kosolapov

“…It seems that such a justification can be made using machine learning methods, based on feature vectors that describe both static and dynamic characteristics of programs. …”
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Anxiety Detection Using Consumer Heart Rate Sensors by Soraya Sinche, Jefferson Acán, Pablo Hidalgo

“…Their features were extracted, processed, and analyzed for anxiety detection. The classification performance was evaluated using decision trees, a support vector machine (SVM), and meta-classifiers to accurately distinguish between “stressed” and “non-stressed” states. …”
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Artificial Intelligence for data modeling in triboelectric nanogenerators by Chenjia Li, Ali Matin Nazar

“…Over 20 experimental implementations are analyzed, combining AI models such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) networks with TENGs across multiple operational modes including contact-separation, lateral sliding, and freestanding configurations. …”
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An improved multiclass classification of acute lymphocytic leukemia using enhanced glowworm swarm optimization by Saranya N, Kalamani M

“…Popular classifiers -Decision tree, Random Forest, Multi-Layer Perceptron, Naive Bayes and Linear, Polynomial, Radial basis function, sigmoid kernels of Support Vector Machine were used for multiclass classification. …”
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Computer Vision-Based Drowsiness Detection Using Handcrafted Feature Extraction for Edge Computing Devices by Valerius Owen, Nico Surantha

“…These are integrated with traditional machine learning models, such as Support Vector Machines, Random Forests, and XGBoost. These models were chosen for their ability to process detailed information from facial landmarks, head poses, PERCLOS, and POM. …”
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Confidence-Aware Ship Classification Using Contour Features in SAR Images by Al Adil Al Hinai, Raffaella Guida

“…The features were tested using a support vector machine (SVM) on the OpenSARShip and FUSAR-Ship datasets, demonstrating improved results compared to existing handcrafted features in the literature. …”
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Moving Object Localization Using Optical Flow for Pedestrian Detection from a Moving Vehicle by Joko Hariyono, Van-Dung Hoang, Kang-Hyun Jo

“…In order to recognize the object, the HOG features are extracted on the candidate region and classified using linear support vector machine (SVM). The HOG feature vectors are used as input of linear SVM to classify the given input into pedestrian/nonpedestrian. …”
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Twitter User Account Classification to Gain Insights into Communication Dynamics and Public Awareness During Tampa Bay's Red Tide Events by Andrey Skripnikov, Tania Roy, Fehmi Neffati, Melvin Adkins, Marcus Beck

“…Having used several text classification algorithms and feature preprocessing approaches, Support Vector Machine with Bidirectional Encoder Representations from Transformers (BERT) yielded the best cross-validation performance in both accuracy (90%) and versatility (unweighted F1 score of 0.67). …”
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Gearbox Fault Diagnosis Based on Adaptive Variational Mode Decomposition–Stationary Wavelet Transform and Ensemble Refined Composite Multiscale Fluctuation Dispersion Entropy by Xiang Wang, Yang Du, Xiaoting Ji

“…Ultimately, the outcomes of the faults diagnoses are derived through the utilization of a Support Vector Machine with a Sparrow Search Algorithm (SSA-SVM), with the actual faults data collection and analysis conducted on an experimental platform for gearbox fault diagnosis. …”
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Anomaly classification in IIoT edge devices by Danny Alexandro Múnera-Ramírez, Diana Patricia Tobón-Vallejo, Martha Lucía Rodríguez-López

“…A k-nearest neighbors (KNN), random forest (RF), support vector machine (SVM), and Multilayer Perceptron (MLP) algorithms were trained. …”
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Emergencies of zoonotic diseases, drivers, and the role of artificial intelligence in tracking the epidemic and pandemics by Akmal Zubair, Rawaha Mukhtar, Hanbal Ahmed, Muhammad Ali

“…The goal of this study is to shed light on the elements that contribute to the appearance and reappearance of zoonotic diseases, as well as the role that artificial intelligence particularly some of the most significant machine learning techniques, such as support vector machine (SVM), logistic regression (LR), Bayesian network, Artificial Neural Networks, Fuzzy Clustering, Poisson Point Process and Deep Denoising Autoencoder to the fight against the various infectious diseases. …”
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Advancements in remote sensing technologies for accurate monitoring and management of surface water resources in Africa: an overview, limitations, and future directions by Maria Sigopi, Cletah Shoko, Timothy Dube

“…Additionally, machine learning (ML) algorithms, including support vector machines (SVM), Random Forest (RF), deep learning and emerging methodologies like recurrent tranformer networks, have been explored. …”
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Development of Ai-Based Crop Quality Grading Systems using Image Recognition by Dusi Prerna, Sharma Pooja

“…It also integrate Convolutional Neural Networks (CNN), Transfer Learning, Support Vector Machines (SVM) and Random Forest algorithms to label crop images into pre defined categories. …”
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Predictive Maintenance in IoT-Monitored Systems for Fault Prevention by Enrico Zero, Mohamed Sallak, Roberto Sacile

“…To address this issue, we propose a novel clustering-based process that identifies potential machinery faults. …”
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The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

“…Moreover, the superiority of the model is verified by comparing with the commonly used algorithms such as Support Vector Machine (SVM) and Convolutional Neural Network (CNN). …”
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Data Augmentation For Sorani Kurdish News Headline Classification Using Back-Translation And Deep Learning Model by Soran Badawi

“…The proposed BiLSTM model is trained on the augmented data and compared with baseline models SVM (Support-Vector-Machines) and Naïve Bayes an trained on the original data. …”
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