Methods for Anomalous Azimuth Estimate Censoring in Small Element Antenna Arrays by M. E. Shevchenko, V. N. Malyshev, D. O. Zadirako, D. N. Faizullina, N. S. Stenyukov, M. S. Shmyrin

Get full text

Discussing the Construction of a Budget Management System Combining Multimedia Technology and Financial Risk Management by Xiaoyi Jiang

“…This paper mainly studies and innovates the data mining process and the support vector machine model and designs the data preprocessing method in the data mining process to perform feature selection and optimize the parameters of the support vector machine model. …”
Get full text

Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…Compared with traditional support vector machine, BP neural network, KNN and naive Bayes, the improved support vector machine has a higher prediction accuracy, and the average error is only 2.7%. …”
Get full text

Cloud-Integrated Meteorological Parameter Prediction by Leveraging Multivariate Statistical Time Series and GANs by Archana Rout, Biswa Ranjan Senapati, Debahuti Mishra

“…Hence, the present work predicts six important meteorological parameters using the vector autoregression model (VAR), vector moving average model (VMA), vector autoregression moving average model (VARMA), and cointegrated vector autoregression model (CVAR). …”
Get full text

Predicting drug–gene relations via analogy tasks with word embeddings by Hiroaki Yamagiwa, Ryoma Hashimoto, Kiwamu Arakane, Ken Murakami, Shou Soeda, Momose Oyama, Yihua Zhu, Mariko Okada, Hidetoshi Shimodaira

“…Abstract Natural language processing is utilized in a wide range of fields, where words in text are typically transformed into feature vectors called embeddings. …”
Get full text

Sentiment Analysis of Short Texts Using SVMs and VSMs-Based Multiclass Semantic Classification by K. Suresh Kumar, A.S. Radha Mani, T. Ananth Kumar, Ahmad Jalili, Mehdi Gheisari, Yasir Malik, Hsing-Chung Chen, Ata Jahangir Moshayedi

“…In our approach, a hybrid machine learning model is proposed which uses Enhanced Vector Space Model (EVSM) along with Hybrid Support Vector Machine (HSVM) classifier. …”
Get full text

Few-shot English text classification method based on graph convolutional network and prompt learning by Yunfei Jin

“…On the other hand, a manual prompt template is used to obtain a class prediction semantic vector for the [MASK] position. In the process of classification prediction, the similarity between class prediction semantic vector and class representation vector is used as classification basis. …”
Get full text

Escalate Prognosis of Parkinson’s Disease Employing Wavelet Features and Artificial Intelligence from Vowel Phonation by Rumana Islam, Mohammed Tarique

“…The extracted audio features include baseline features, intensities, formant frequencies, bandwidths, vocal fold parameters, and Mel-frequency cepstral coefficients (MFCCs) to form a feature vector. Then, this feature vector is further enriched by including wavelet-based features to form the second feature vector. …”
Get full text

Monoclonal Antibodies in Light of Mpox Outbreak: Current Research, Therapeutic Targets, and Animal Models by Vladimir N. Nikitin, Iuliia A. Merkuleva, Dmitriy N. Shcherbakov

Get full text

Angiogenesis as a Survival Mechanism in Heartworm Disease: The Role of Fructose-Bisphosphate Aldolase and Actin from <i>Dirofilaria immitis</i> in an In Vitro Endothelial Model by Manuel Collado-Cuadrado, Claudia Alarcón-Torrecillas, Alfonso Balmori-de la Puente, Iván Rodríguez-Escolar, Elena Infante González-Mohino, Miguel Pericacho, Rodrigo Morchón

“…The aim of this work was to study the effect of two molecules of the <i>D. immitis</i> excretory/secretory antigen (DiES) on the angiogenic process, taking into account that this antigen is able to interact with this process and use it as a survival mechanism. …”
Get full text

Hybrid CNN-Ensemble Framework for Intelligent Optical Fiber Fault Detection and Diagnosis by Salem Titouni, Idris Messaoudene, Yassine Himeur, Omar Alnaseri, Farouk Chetouah, Boualem Hammache, Massinissa Belazzoug, Shadi Atalla, Wathiq Mansoor

“…This paper introduces a novel Hybrid CNN-Ensemble framework, combining convolutional neural networks (CNNs) for deep feature extraction with ensemble learning techniques including XGBoost, Support Vector Machines (SVM), and Random Forest (RF). The framework processes CNN-extracted features from OTDR traces, with predictions aggregated through a meta-classifier. …”
Get full text

Identification of PANoptosis-related genes as biomarkers in ischemic stroke by Anna Jiang, Hongjing Zhang, Xinglei Jia, Huangying Zhao, Hong Zhao, Zhengyu Lu

“…Gene ontology-biological process and the Kyoto Encyclopedia of Genes and Genomes were used to analyze the biological processes and possible pathways. …”
Get full text

Development of Smart Models to Accurately Predict Dynamic Viscosity of CO2-Saturated Polyethylene Glycol by Ayat Hussein Adhab, Morug Salih Mahdi, Bhavesh Kanabar, Anupam Yadav, Ranganathaswamy M K, Rishabh Thakur, Parveen Kumar, Braj Krishna, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…Precise estimation of viscosity of CO2-saturated PEG is crucial for several scientific and industrial applications, as viscosity directly impacts the material’s performance and feasibility in specific processes. This study, hence, introduces machine learning models utilizing K-nearest neighbors, decision tree, adaptive boosting, multilayer perceptron artificial neural network, convolutional neural network, support vector machine, random forest and ensemble learning algorithms to accurately forecast the dynamic viscosity of CO2-saturated PEG based on PEG molar mass, pressure, and temperature. …”
Get full text

The impact of aging on achilles tendon ossification in mice by Hanhua Cai, Yujian Lan, Huan Liu, Qi Hao

“…This finding suggests a potential link between these processes, opening new avenues for research into diagnostic markers and therapeutic targets. …”
Get full text

Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding by Xiaomei Hu, Fanqi Liang, Man Zheng, Juying Xie, Shanxi Wang

“…Advanced analytical tools, including Lasso regression and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), were employed to refine our gene selection. …”
Get full text

Radar Echo Characteristics and Recognition of Warm-sector Torrential Rain in Sichuan Basin by Luo Hui, Xiao Dixiang, Kuang Qiuming, Qing Quan, Kang Lan

“…They are accompanied by long-term merge when moving. Among 28 processes, a large proportion appears in the northwest and has the longest duration. …”
Get full text

Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…Aiming at the problems of poor data effectiveness, low modeling accuracy, and weak generalization in the tuning process of microwave cavity filters, a parametric model for coaxial cavity filter using kernel canonical correlation analysis (KCCA) and multioutput least squares support vector regression (MLSSVR) is proposed in this study. …”
Get full text

Study of Online Parameter Identification Technology Based on Mathematical Model of Three-phase Asynchronous Induction Motor by Xuedi WANG, Bijun DAI, Yang YANG

“…According to the equivalent circuit diagram of the motor model, the mathematical expression for solving the rotor resistance iteratively was derived.In the process of iteration, the parallel relationship between the voltage and current of the rotor resistance in the space vector diagram of the motor variable was used as the sign to judge the end of calculation. …”
Get full text

Implementasi Algoritme Morus V2 untuk Pengamanan Data Pada Perangkat Bluetooth Low Energy by Diah Ratih Destyorini, Ari Kusyanti, Reza Andria Siregar

“…From the test results, the MORUS V2 algorithm has been successfully implemented through test vector testing with the same keystream value.  Confidentiality testing has been successfully carried out through encryption and decryption processes. …”
Get full text

Multimodal Visualization and Explainable Machine Learning–Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With... by Jun Wang, Jiajun Zhu, Hui Li, Shili Wu, Siyang Li, Zhuoya Yao, Tongjian Zhu, Bi Tang, Shengxing Tang, Jinjun Liu

“…A total of 5 ML model-decision trees, K-nearest neighbors, random forest, support vector machine, and extreme gradient boosting were used to construct a visualization and explainable predictive framework to elucidate model decision-making processes. …”
Get full text