Investigation of Steady State Two-Phase Short Circuit Modes Of Phase-Shifting Autotransformer with Hexagon Scheme and with Adjusting Autotransformer by Bosneaga V., Suslov V.

“…The purpose of work is to investigate two - phase short-circuiting modes of new autotransformer FACT’s - type device and is intended for power systems flexible connection. …”
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Enhanced metal ion adsorption using ZnO-MXene nanocomposites with machine learning-based performance prediction by Abhishek Kagalkar, Swapnil Dharaskar, Nitin Chaudhari, Vinay Vakharia, Rama Rao Karri

“…Furthermore, adsorption performance was well predicted by machine learning models such as Random Forest (RF) and Support Vector Machine (SVM), with RF showing the highest accuracy. …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…In this work, an integrated model that makes the classification stage results one of the feature inputs for the concentration regression stage was employed, successfully reducing the RMSE of the concentration regression results. …”
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Comparing the Potential of Near- and Mid-Infrared Spectroscopy in Determining the Freshness of Strawberry Powder from Freshly Available and Stored Strawberry by Da Wang, Wenwen Wei, Yanhua Lai, Xiangzheng Yang, Shaojia Li, Lianwen Jia, Di Wu

“…Furthermore, partial least squares regression and least squares support vector machines (LS-SVM) models were established based on NIR, MIR, and combination of NIR and MIR data with full variables or optimal variables of strawberry powder to predict the storage days of strawberries that produced the powder. …”
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A Subjective Expressions Extracting Method for Social Opinion Mining by Mingyong Yin, Haizhou Wang, Xingshu Chen, Hong Yan, Rui Tang

“…Our work can provide hint for further research on opinion expression extraction.…”
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Symmetry and minimal Hamiltonian of nonsymmorphic collinear antiferromagnet MnTe by Koichiro Takahashi, Hong-Fei Huang, Jie-Xiang Yu, Jiadong Zang

“…Abstract α-MnTe, an A-type collinear antiferromagnet, has recently attracted significant attention due to its pronounced spin splitting despite having net zero magnetization, a phenomenon unique for a new class of magnetism dubbed altermagnetism. In this work, we develop a minimal effective Hamiltonian for MnTe based on realistic orbitals near the Fermi level at both the Γ and A points based on group representation theory, first-principles calculations, and tight-binding modeling. …”
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Novel delayed binary time-series pattern based machine learning techniques for stock market forecasting by Zeqiye Zhan, Song-Kyoo Kim

“…The results suggest a paradigm shift in stock market prediction practices, highlighting the potential of integrating delayed time-series analysis with existing techniques to achieve improved robust outcomes. This work lays the groundwork for further exploration into diverse datasets and adaptive modeling strategies in financial forecasting.…”
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La borréliose de Lyme : un risque sanitaire émergent dans les forêts franciliennes ? by Christelle Méha, Vincent Godard, Bernard Moulin, Hedi Haddad

“…Lyme borreliosis is the most prevalent and widespread vector-borne disease in temperate zones of the northern hemisphere. …”
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Structure Design and Optimization of Self-locking Under-actuated Gripper by Shuting He, Yi Shen, Xianling Dai, Beibei Qiu, Xianfeng Pan, Mingxin Yuan

“…According to the principle of virtual work and the vector closed equation of the linkage mechanism， a static modeling under the adaptive gripping state of the gripper is constructed. …”
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Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“…In this work, Random Forest Regressor (RFR), Multi-Layer Perceptron Regressor(MLPR), and Support Vector Regression (SVR) models were employed to predict the magnitude of greater than 6 mb earthquakes that occurred in the year 2015 in the central Himalaya. …”
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Deep learning for melt pool depth contour prediction from surface thermal images via vision transformers by Francis Ogoke, Peter Pak, Alexander Myers, Guadalupe Quirarte, Jack Beuth, Jonathan Malen, Amir Barati Farimani

“…Specifically, a ResNet model embeds the spatial information contained within the thermal images to a latent vector, while a Transformer model correlates the sequence of embedded vectors to extract temporal information. …”
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Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection by Mohammad Abrar, Abdu Salam, Ahmed Albugmi, Fahad Al-otaibi, Farhan Amin, Isabel de la Torre, Thania Candelaria Chio Montero, Perla Araceli Arroyo Gala

“…In addition, the integration of CAOA and RST effectively addresses the challenges of high-dimensional EEG data, helps optimize the feature selection process, and increases accuracy. In future work, we suggest incorporating large-size datasets that include more diverse patient groups and refining the model with advanced machine-learning models and techniques.…”
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Incommensurate Antiferromagnetism in UTe_{2} under Pressure by W. Knafo, T. Thebault, S. Raymond, P. Manuel, D. D. Khalyavin, F. Orlandi, E. Ressouche, K. Beauvois, G. Lapertot, K. Kaneko, D. Aoki, D. Braithwaite, G. Knebel

“…These elements support that UTe_{2} is a nearly antiferromagnet at ambient pressure. Our work appeals for theories modeling the evolution of the magnetic interactions and electronic properties, driving a correlated paramagnetic regime at ambient pressure to a long-range antiferromagnetic order under pressure. …”
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DDoS attack detection in intelligent transport systems using adaptive neuro-fuzzy inference system by G. Usha, H. Karthikeyan, Kumar Gautam, Nikhil Pachauri

“…The learning approach of artificial neural networks and the fuzzy logic model is integrated into the Fuzzy System. Based on the experimental results, the proposed model achieved 94.3% accuracy, outperforming traditional classifiers such as Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Convolutional Neural Network. …”
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Bioinformatics analysis of innovative multi-epitope vaccine utilizing MAGE-A, MAM-A, and Gal-3 for breast cancer management by Faranak Aali, Abbas Doosti, Mostafa Shakhsi-Niaei

“…The optimal estimated a three-dimensional model was enhanced and verified to get a superior 3D model. …”
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Near Infrared Spectroscopy Based on Supervised Pattern Recognition Methods for Rapid Identification of Adulterated Edible Gelatin by Hao Zhang, Haifeng Sun, Ling Wang, Shun Wang, Wei Zhang, Jiandong Hu

“…Further, linear discriminant analysis (LDA), soft independent modelling of class analogy (SIMCA), backpropagation neural network (BPNN), and support vector machine (SVM) were introduced to establish discrimination models for identifying the adulterated gelatin gels, which gave a total correct recognition rate of 97.44%, 100%, 97.44%, and 100%, respectively. …”
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Efficient Task Scheduling in Cloud Computing: A Multiobjective Strategy Using Horse Herd–Squirrel Search Algorithm by V. Parthasaradi, A. Karunamurthy, C. H. Hussaian Basha, S. Senthilkumar

“…The major aim of the research work is to reduce the cost and the execution time as well as to improve the resource utilization of the task scheduling problem using the improved support vector machine (ISVM) and the optimization concept. …”
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Presenting an Innovative Method Based on Ensemble Learning for a Credit Approval System by Eshonkulov Uchkun, Elmurodov Tulkin, Ravshanov Zavqiddin, Каramanov Asqar

“…As a result, MBF showed noteworthy F-Score, accuracy, sensitivity, and specificity values of 91.93%, 86.95%, 97.51%, and 97.51%, respectively, in comparison to the other models that were chosen. Notably, the major innovation of this work lies in the exceptional accuracy and computational efficiency demonstrated by the proposed method, which significantly enhances the performance of data classification processes within credit approval systems by enabling faster decision-making and more reliable credit risk assessments.…”
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Enhancing Multi-Disease Prediction with Machine Learning: A Comparative Analysis and Hyperparameter Optimization Approach by Mariam Kili Bechir, Ferhat Atasoy

“…Therefore, the presented work aimed to evaluate the success of several supervised ML models with hyperparameter optimization (HPO) for predicting multiple diseases such as diabetes, heart disease, Parkinson's disease, and breast cancer. …”
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Identification and Validation of Ferroptosis Related Genes in Ischemic Stroke and Its Effect on the Peripheral Immune Landscape by Chen Y, Zhu Y, Huang C, Qu Y, Zhu Y

“…Yan Chen,1,* Yanmei Zhu,1,* Cong Huang,2 Youyang Qu,1 Yulan Zhu1 1Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150080, People’s Republic of China; 2Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150080, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yulan Zhu, Department of Neurology, The Second Affiliated Hospital of Harbin Medical University, No. 246, Xuefu Road, Nangang District, Harbin, Heilongjiang, 150081, People’s Republic of China, Email ylz1111@outlook.comBackground: This research utilized a combination of gene databases associated with ferroptosis and online gene expression data from ischemic stroke samples to pinpoint ferroptosis-related genes (FRGs) in ischemic stroke cases.Methods: By employing Random Forest (RF) and Support Vector Machine (SVM) models based on these genes, an overlap of genes from both models was identified as “Hub” genes. …”
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