HARD- AND SOFTWARE SUPPORT OF DATA AND KNOWLEDGE PROCESSING METHOD WITH CIPHERING ELEMENTS FOR INTERNET by V. A. Vishniakov, D. S. Borodaenko

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Disulfidptosis-related classification patterns and tumor microenvironment characterization in skin cutaneous melanoma by Li Yang, Zi-jian Cao, Yuan Zhang, Jin-ke Zhou, Jun Tian

“…The consensus clustering algorithm was applied to categorize SKCM patients into different DRG subtypes. …”
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Modular Mobile Charging Facility Layout Optimization Method and Deployment Strategy by Jiajun ZHENG, Xiaoyu DUAN, Zechun HU, Xiaorui HU, Bin ZHU

“…Firstly, an electric vehicle user travel mechanism model is established to predict the spatial and temporal distribution of charging demand at the node level. …”
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Study on Vibration Characteristic of Trilobe Raceway Cylindrical Roller Bearing with Elastic Support by Sun Xue, Deng Sier, Zhang Yuanjun, Chen Guoding

“…Based on dynamics analysis of rolling bearing,the dynamics differential equations for cylindrical roller bearing with trilobe raceway and elastic support are established. By using the predict-correct integer algorithm with variable step,the dynamics equation is solved,and the influence of structural parameters of elastic support and working conditions on the vibration characteristics of the bearing is investigated. …”
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Quantitative Structure-Activity Relationship Studies for Potential Rho-Associated Protein Kinase Inhibitors by Giovanna Cardoso Gajo, Tamiris Maria de Assis, Letícia Cristina Assis, Teodorico Castro Ramalho, Elaine Fontes Ferreira da Cunha

“…The models were generated applying genetic algorithm (GA) optimization combined with partial least squares (PLS) regression. …”
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Practical aspects of forecasting the company’s financial performance by V. V. Kookueva, A. A. Aliev, R. I. Khavich

“…The article considers the methodological problems of forecasting key financial indicators related to forecasting the final results of the company. The algorithm for creating refined factor predictive models of financial indicators has been presented and tested. …”
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Numerical simulation of cavitating two-phase gas-liquid three-dimensional flow in a duct of varying cross-section based on homogenous mixture model by Nguyen The Duc

“…The numerical method uses artificial compressibility algorithm extended to unsteady flows with dual-time technique. …”
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Formation of Scattering Characteristics for Acoustical Ray Tracing Simulation by Srđan BOJIČIĆ, Dragana ŠUMARAC-PAVLOVIĆ, Miomir MIJIĆ

“…Ray tracing simulation of sound field in rooms is a common tool in room acoustic design for predicting impulse response. There are numerous commercial engineering tools utilising ray tracing simulation. …”
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Determining Functional Safety Indices of CWR Track Subject to Action of Thermal Compression Forces by O. A. Suslov

“…In the present paper there is proposed failure probability assessment algorithm based on the thermal track buckling emergence criterion. …”
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Reducing Unnecessary Handovers Using Logistic Regression in 5G Networks by Alison M. Fernandes, Hermes I. Del Monego, Bruno S. Chang, Anelise Munaretto

“…This paper proposes using machine learning in 5G mobile networks, employing a Logistic Regression algorithm to predict handovers. Considering selection criteria like Reference Signal Received Power, Signal-to-Interference-Plus-Noise Ratio, Received Signal Strength Indicator, and distance, our proposal shows that it can significantly reduce the consequences of frequent handovers and provide a better quality of service to the user, together with low computational complexity. …”
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SAB: Self-Adaptive Bias by Suchan Choi, Jinyoung Oh, Jeong-Won Cha

“…In this paper, we propose a new algorithm that determines how to select learning data and when to start and stop curriculum learning by considering learning errors. …”
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A multivariate model incorporating subharmonic measurements for evaluating vocal roughness by Itsuki Kitayama, Kiyohito Hosokawa, Shinobu Iwaki, Misao Yoshida, Akira Miyauchi, Kenji Aruga, Takanari Kawabe, Toshihiro Kishikawa, Hidenori Tanaka, Takeshi Tsuda, Takashi Sato, Yukinori Takenaka, Makoto Ogawa, Hidenori Inohara

“…Furthermore, we introduce the acoustic roughness index (ARI), a predictive acoustic model that integrates these parameters with existing acoustic parameters. …”
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Cascade Machine Learning Approach Applied to Short-Term Medium Horizon Demand Forecasting by Bruno Brentan, Ariele Zanfei, Martin Oberascher, Robert Sitzenfrei, Joaquin Izquierdo, Andrea Menapace

“…The LSTM model estimates, utilizing a univariate approach, the hourly forecasting of water demand for the entire available dataset and the minimum night flow. The algorithm considers various time series sizes for each DMA and predicts the water demand values for each hour throughout the week. …”
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Analisis Sentimen Pengguna Aplikasi SIMANTAP Pondok Pesantren Salafiyah Syafi’iyah Situbondo by Ach. Zubairi, Luckman Ashary

“…Based on the test data results using the Naïve Bayes classifier algorithm, the classification can predict quite well; this is shown by the precision results of 82%, 97% recall, and 89% fi-score.…”
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Deep learning-based anterior segment identification and parameter assessment of primary angle closure disease in ultrasound biomicroscopy images by Xingzhi Sun, Guotong Xie, Kun Lv, Xiaoyue Zhang, Bin Lv, Yuan Ni, Yao Ma, Fangting Li, Kangyi Yang, Jiayin Qin, Huijuan Wu

“…Purpose To develop an artificial intelligence algorithm to automatically identify the anterior segment structures and assess multiple parameters of primary angle closure disease (PACD) in ultrasound biomicroscopy (UBM) images.Design Development and validation of an artificial intelligence algorithm for UBM images.Methods:2339 UBM images from 592 subjects were collected for algorithm development. …”
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MODERN APPROACHES TO CLINICAL AND LABORATORY DIAGNOSTICS OF RHEUMATOID ARTHRITIS EARLY ONSET by D. G. Rekalov, S. Y. Dotsenko, A. V. Kylinich

“…The data on the sensitivity and specificity of the diagnostic classification and clinical criteria of eRA and an algorithm for the identification of the disease were presented. …”
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Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course by Handityo Aulia Putra, Kaechang Park, Kaechang Park, Fumio Yamashita

“…Feature selection and classification were performed using the Random Forest machine learning algorithm, optimized to identify the most predictive GM regions.ResultsOut of 114 GM regions, eleven were selected as optimal predictors: left angular gyrus, frontal operculum, occipital fusiform gyrus, parietal operculum, postcentral gyrus, planum polare, superior temporal gyrus, and right hippocampus, orbital part of the inferior frontal gyrus, posterior cingulate gyrus, and posterior orbital gyrus. …”
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Artificial Intelligence in Pediatric Blood Transfusion during Anesthesia: A Scoping Review by Parisa Akbarpour, Parisa Moradimajd, Azam Saei, Maryam Aligholizadeh, Siavash Sangi

“…Relevant keywords, including artificial intelligence, machine learning, predictive model, neural network, predictive algorithm, blood transfusion, children, pediatric, neonates, anesthesia, surgery, and operation, were extracted from the Medical Subject Headings (MeSH). …”
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Theoretical investigation of the free fall of a spherical particle in a viscous fluid using continuous piecewise linearization method by Akuro Big-Alabo, Joseph Chukwuka Ofodu

“…The CPLM algorithm was shown to predict published experimental results accurately and compared very well with numerical solutions and existing analytical solutions. …”
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A Multi-Input Neural Network Model for Accurate MicroRNA Target Site Detection by Mohammad Mohebbi, Amirhossein Manzourolajdad, Ethan Bennett, Phillip Williams

“…These images are processed in parallel by the MINN algorithm, allowing it to learn a comprehensive and precise representation of the underlying biological mechanisms. (3) Results: Our method, on an experimentally validated test set, detects target sites with an AUPRC of 0.9373, Precision of 0.8725, and Recall of 0.8703 and outperforms several commonly used computational methods of microRNA target-site predictions. (4) Conclusions: Incorporating diverse biologically explainable features, such as duplex structure, substructures, their MFEs, and binding probabilities, enables our model to perform well on experimentally validated test data. …”
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