Real-time Data Sharing Platform Technology for Rail Transit Management Systems by LIU Chao, LI Shen, SU Cheng, WANG Wei, HUANG Qing

“…Finally, a qualitative and quantitative comparison is conducted to evaluate the suitability of different middleware options, identifying the most appropriate middleware for platform implementation. …”
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Patterns of inflammation and immune activation by coreceptor use in people living with HIV-1 by Francisco Xavier Guerra-Castillo, Francisco Xavier Guerra-Castillo, Sandra Pinto-Cardoso, Santiago Ávila-Ríos, Monserrat Chávez-Torres, Amy Peralta-Prado, Carolina González-Torres, Javier Gaytán-Cervantes, Brenda Requena-Benitez, Dafne Díaz-Rivera, Carmen Alaez-Verson, María Concepción Hernández-García, Vilma Carolina Bekker-Méndez

“…Differences in immune activation patterns between R5 and X4 group were explored using Mann-Whitney Wilcoxon test and t-test, and a principal component analysis (PCA). …”
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Edge-based detection and localization of adversarial oscillatory load attacks orchestrated by compromised EV charging stations by Khaled Sarieddine, Mohammad Ali Sayed, Sadegh Torabi, Ribal Atallah, Chadi Assi

“…Finally, a security metric is createdto evaluate the resiliency of the ecosystem based on its design and architecture.…”
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Intelligent Reflecting Surface-Assisted Wireless Communication Using RNNs: Comprehensive Insights by Rana Tabassum, Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Hyoung-Kyu Song

“…These RNN algorithms were evaluated with respect to bit error rate (BER) and symbol error rate (SER) for IRS-enhanced communication. …”
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Racial disparities in continuous glucose monitoring-based 60-min glucose predictions among people with type 1 diabetes. by Helene Bei Thomsen, Livie Yumeng Li, Anders Aasted Isaksen, Benjamin Lebiecka-Johansen, Charline Bour, Guy Fagherazzi, William P T M van Doorn, Tibor V Varga, Adam Hulman

“…Potential healthcare disparities can happen when machine learning models, used in diabetes technologies, are trained on data from primarily White patients. We aimed to evaluate algorithmic fairness in glucose predictions. …”
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Subcortical Brain Segmentation Based on a Novel Discriminative Dictionary Learning Method and Sparse Coding by Xiang Li, Ying Wei, Yunlong Zhou, Bin Hong

“…For the shared dictionary, a regularization term is used to minimize the between-class scatter of corresponding shared coefficients so that they can learn shared image patterns. The optimization algorithms are developed to solve the problems in the learning step. …”
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An efficient 3D column-only P300 speller paradigm utilizing few numbers of electrodes and flashings for practical BCI implementation. by Onur Erdem Korkmaz, Onder Aydemir, Emin Argun Oral, Ibrahim Yucel Ozbek

“…Many studies have been carried out to improve the performance of P300 speller systems either by developing signal processing algorithms and classifiers with different architectures or by designing new paradigms. …”
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Uniform Quantization for Multi-Antenna Amplify–Quantize–Forward Relay by Gangsan Jeong, Xianglan Jin

“…Given the challenge of finding optimal step sizes for the MIMO AQF relay, comparing outcomes across different determination algorithms proves to be a significant obstacle. …”
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Anatomical Parameter-driven Volumetric Modulated Arc Therapy Optimization in Left-sided Breast Cancer: A Machine Learning Framework for Lung Dose Prediction by Mukesh Kumar Zope, Deepali Patil, Rishi Raj, Seema Devi, Richa Madhawi

“…In addition, we established predictive models for lung doses utilizing the Least Absolute Shrinkage and Selection Operator, ridge, and linear regression algorithms while also evaluating dosimetric parameters for both the PTV and the organs at risk (OARs). …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Conclusion We compare the performance of standard Adam, LM, and LM SA on different datasets and computational conditions. Performance was evaluated using Loss function values, predicted Local Distance Difference Test (pLDDT), distance-based Root Mean Square Deviation (dRMSD), and Template Modeling (TM) scores. …”
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Enhancing Wind Turbine Power Output Estimation Using Causal Inference and Adaptive Neuro-Fuzzy Inference System ANFIS by Ahmed A. Mostfa, Nawfal A. Zakar, Rasha Raad Al-Mola, Abdel-Nasser Sharkawy

“…To meet the demand for renewable energy at the lowest cost, wind energy became the target of machine learning algorithms and was employed to predict the output power of wind turbines. …”
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On the principles of building a model of a specialist – a graduate of a pedagogical university by K. S. Kаtаеv, S. G. Kаtаеv, I. V. Kаmenskaya

“…The reasonableness of the obtained results of the study, the availability of a variety of algorithms for data interpretation indicate the real possibility of using in practice the proposed structure of the model, including the way of organising data as a monitoring system.…”
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Enhancing Stroke Prediction with Logistic Regression and Support Vector Machine Using Oversampling Techniques by Syamsul Risal, Fajar Apriyadi, A. Sumardin, Andini Dani Achmad, Annisa Nurul Puteri

“…This study compares the performance of Logistic Regression (LR) and Support Vector Machine (SVM) algorithms combined with different oversampling methods—SMOTE, Borderline-SMOTE, ADASYN, Random Over Sampling (ROS), and Random Under Sampling (RUS)—on a stroke prediction dataset. …”
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Transfer and deep learning models for daily reference evapotranspiration estimation and forecasting in Spain from local to national scale by Yu Ye, Aurora González-Vidal, Miguel A. Zamora-Izquierdo, Antonio F. Skarmeta

“…This study compares standard ML and Deep Learning (DL) algorithms for estimating and forecasting daily ET0 at different spatial scales in Spain. …”
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Assessment of road-cut slope stability using empirical, numerical, and machine learning methodologies by Virat Singh Chauhan, Md. Rehan Sadique, Mohd. Masroor Alam, Mohd. Ahmadullah Farooqi

“…The outcomes of the machine learning algorithms are compared against those obtained from Finite Element Analysis (FEA), with observed discrepancies ranging from 2 to 10% across the different ML models.…”
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Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments by Abhishek Sharma, Timothy N Fazio, Long Song, Samantha Plumb, Uwe Aickelin, Mojgan Kouhounestani, Mark John Putland

“…This framework was designed to be easily adapted by other institutions for the development of their own ML models.Methods We analysed data from 297 392 ED visits of patients aged 18 and above at a quaternary hospital between 30 June 2019 and 31 December 2022. Eight ML algorithms were evaluated, and ultimately, twelve lasso models built from 21 features were trained to predict four outcomes of LOS and DD at three time points post-triage. …”
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A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow-up in patients... by Syed Waseem Abbas Sherazi, Jang-Whan Bae, Jong Yun Lee

“…Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine learning (ML) algorithms.<h4>Methods</h4>We used the Korea Acute Myocardial Infarction Registry dataset and selected 11,189 subjects among 13,104 with the 2-year follow-up. …”
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Non-Invasive Continuous Respiratory Monitoring on General Hospital Wards: A Systematic Review. by Kim van Loon, Bas van Zaane, Els J Bosch, Cor J Kalkman, Linda M Peelen

“…<h4>Data synthesis</h4>Six intervention and five diagnostic studies were included, evaluating the use of eight different devices for continuous respiratory monitoring. …”
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Electronic catalog as an object of quality assessment by G. A. Skaruk

“…The composition of EC components as quality assessment objects and main evaluating indicators for each component are determined: bibliographical databases (including fullness, data identity and relevance, efficiency, completeness of documents’ identifying characteristics, compliance with the bibliographic description rules, entire and depth of document content reflection, stability of indexing); lexicographic databases (including the information search language (ISL) vocabulary completeness and detail, data identity and relevance, correct wording and alignment of the access points, the compliance with requirements of data presentation formats, ISL grammar tools composition and functionality); factographic data (information completeness and accuracy on the availability and location of publication copies, their movement); database management system and information processing s y st em (functional suitability, accessibility, ease of use, application reliability and security, efficiency, mobility); search system (ISL functionality, ease of navigation in the catalog, efficiency of search techniques and algorithms, relevance criteria, completeness and ease of understanding of search instructions, maintaining the system to help users); user interface (completeness of tasks solved by the system, compliance with human capabilities, visibility and functionality of formats, user-friendly modes of operation with the interface, user feedback, comfort, compliance with aesthetic requirements); system for ensuring the reliability of information storage .…”
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Classification of Structural and Functional Development Stage of Cardiomyocytes Using Machine Learning Techniques by V. R. Bondarev, K. O. Ivanko, N. G. Ivanushkina

“…A pre-processed and augmented dataset is used for training of the convolutional neural network having an architecture with hierarchical structure and residual block usage. The model is evaluated based on the confusion matrix and the heat maps of different convolutional layers are analyzed. …”
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