Machining Performance of AA2024/5Al2O3/5Gr Hybrid Composites under Al2O3 Mixed Dielectric Medium by Nandagopal Kaliappan, M. Balaji, T. CH Anil Kumar, Haqqani Arshad, N. B. Prakash Tiruveedula, S. Hemavathi, Kibebe Sahile

“…In this research work, AA2024/5Al2O3/5Gr hybrid composites fabricated through stir casting were machined utilising an electric discharge machine (EDM). …”
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Research and design of TiN/TiAlN coated integral cemented carbide reamers under high cutting-speed and high feed-rate machining conditions by ChaoKuan Zhu, Ju Huang, Yong Zhang

“…The important structural parameters were determined, and the importance of adequate cooling and lubrication was clarified. …”
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Technical Economic Optimization Analysis for Cost-Effective Process of CNC Laser Machine G-Weike LC6090 Using Simplex Lattice – Centroid and Full Costing Methods by Rudi Tjahyono

“…Because there is no ideal tabulation that serves as a guide for the operator in setting machine parameters, one of the issues in operating the machine is that the engraving process for acrylic materials is still traditionally done through estimation or approximation. …”
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Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning Reveals the Giant Exoplanet AF Lep b in High-contrast Imaging Data from 2011 by Markus J. Bonse, Timothy D. Gebhard, Felix A. Dannert, Olivier Absil, Faustine Cantalloube, Valentin Christiaens, Gabriele Cugno, Emily O. Garvin, Jean Hayoz, Markus Kasper, Elisabeth Matthews, Bernhard Schölkopf, Sascha P. Quanz

“…We present updated orbital parameters for this object.…”
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Prediction of new HIV infection in men who have sex with men based on machine learning: secondary analysis of a prospective cohort study from Western China by Kangjie Li, Guiqian Shi, Cong Zhang, Bing Lin, Yi Tao, Qian Wang, Haijiao Zeng, Jielian Deng, Lei Zou, Biao Xie, Xiaoni Zhong

“…Objective This study aimed to construct a model based on machine learning to predict new HIV infections in HIV-negative men who have sex with men (MSM).Methods This is a secondary analysis of a previous random clinical trial aiming to evaluate the preventive effects of PrEP on new HIV infection in MSM. …”
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Wear Characteristics and Optimization Measures of Disc Cutters During Large-Diameter Slurry Tunnel Boring Machine Advancing in Soil-Rock Composite Strata: A Case Study by Yingran Fang, Xinggao Li, Yinggui Cao, Hongzhi Liu, Yidong Guo

“…The large-diameter slurry tunnel boring machine (TBM) is widely used in the construction of tunnels across rivers and seas. …”
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Utilizing Circadian Heart Rate Variability Features and Machine Learning for Estimating Left Ventricular Ejection Fraction Levels in Hypertensive Patients: A Composite Multiscale E... by Nanxiang Zhang, Qi Pan, Shuo Yang, Leen Huang, Jianan Yin, Hai Lin, Xiang Huang, Chonglong Ding, Xinyan Zou, Yongjun Zheng, Jinxin Zhang

“…We developed a comprehensive machine learning framework that initiated with preprocessed ECG signal in one-hour intervals to extract CMSE-based heart rate variability (HRV) features, then utilized machine learning models such as linear regression (LR), Support Vector Machines (SVMs), and random forests (RFs) with recursive feature elimination for optimal LVEF estimation. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…In addition, the unsupervised K-means algorithm was implemented to analyze vehicle gear changes, identify driving patterns, and segment the data into meaningful groups. Machine learning techniques, including K-Nearest Neighbors (KNN), decision trees, logistic regression, and Support Vector Machines (SVMs), were employed to classify gear shifts accurately. …”
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Automated mechanical cardiopulmonary resuscitation devices versus manual chest compressions in the treatment of cardiac arrest: protocol of a systematic review and meta-analysis co... by Katrin Jensen, Markus A Weigand, Manuel Obermaier, Johannes B Zimmermann, Erik Popp, Sebastian Weiterer, Alexander Dinse-Lambracht, Claus-Martin Muth, Benedikt L Nußbaum, Jan-Thorsten Gräsner, Stephan Seewald, Svenja E Seide

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A Computational Intelligence Framework Integrating Data Augmentation and Meta-Heuristic Optimization Algorithms for Enhanced Hybrid Nanofluid Density Prediction Through Machine and... by Priya Mathur, Hammad Shaikh, Farhan Sheth, Dheeraj Kumar, Amit Kumar Gupta

“…This research presents a robust and comprehensive framework for predicting the density of hybrid nanofluids using state-of-the-art machine learning and deep learning techniques. Addressing the limitations of conventional empirical approaches, the study used a curated dataset of 436 samples from the peer-reviewed literature, which includes nine input parameters such as the nanoparticle, base fluid, temperature (&#x00B0;C), volume concentration (<inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>), base fluid density (<inline-formula> <tex-math notation="LaTeX">$\rho _{\text {bf}}$ </tex-math></inline-formula>), density of primary and secondary nanoparticles (<inline-formula> <tex-math notation="LaTeX">$\rho _{\text {np1}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\rho _{\text {np2}}$ </tex-math></inline-formula>), and volume mixture ratios of primary and secondary nanoparticles. …”
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Fibrosis-4plus score: a novel machine learning-based tool for screening high-risk varices in compensated cirrhosis (CHESS2004): an international multicenter study by Bingtian Dong, Ruiling He, Shenghong Ju, Yuping Chen, Ivica Grgurevic, Jianzhong Ma, Ying Guo, Huizhen Fan, Qiang Yan, Chuan Liu, Huixiong Xu, Anita Madir, Kristian Podrug, Jia Wang, Linxue Qian, Zhengzi Geng, Shanghao Liu, Tao Ren, Guo Zhang, Kun Wang, Meiqin Su, Fei Chen, Sumei Ma, Liting Zhang, Zhaowei Tong, Yonghe Zhou, Xin Li, Fanbin He, Hui Huan, Wenjuan Wang, Yunxiao Liang, Juan Tang, Fang Ai, Tingyu Wang, Liyun Zheng, Zhongwei Zhao, Jiansong Ji, Wei Liu, Jiaojiao Xu, Bo Liu, Xuemei Wang, Yao Zhang, Qiong Yan, Hui Liu, Xiaomei Chen, Shuhua Zhang, Yihua Wang, Yang Liu, Li Yin, Yanni Liu, Yanqing Huang, Li Bian, Ping An, Xin Zhang, Shaoting Zhang, Jinhua Shao, Xiangman Zhang, Wei Rao, Chaoxue Zhang, Christoph Frank Dietrich, Won Kim, Xiaolong Qi

“…., age, aspartate aminotransferase, alanine aminotransferase, and platelet count [PLT]) were combined using machine learning algorithms (logistic regression [LR] and extreme gradient boosting [XGBoost]) to develop the LR-FIB-4plus and XGBoost-FIB-4plus models, respectively. …”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

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Development of a method for differential diagnosis of iron deficiency anemia and anemia of chronic disease based on demographic data and routine laboratory tests using machine lear... by N. V. Varekha, N. I. Stuklov, K. V. Gordienko, R. R. Gimadiev, O. B. Shchegolev, S. N. Kislaya, E. V. Gubina, A. A. Gurkina

“…Background. The study of machine learning methods, a branch of artificial intelligence science, is relevant for the development of optimal screening strategies, identification of risk groups, and application of less expensive and more accessible laboratory tests to assess the body iron status.   …”
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The Persistent Threat of Chronic Inflammation on the Mortality Among Cervical Cancer Survivors: A Mendelian Randomization and Machine Learning Analysis Using UK Biobank and Chinese... by Wang J, Chen Z, Guan M, Ma Z, Peng L, Chen J, Fiori PL, Carru C, Capobianco G, Coradduzza D, Zhou L

“…We aimed to comprehensively evaluate the genetic association between inflammation and cervical cancer, and construct an accurate prognosis model based on circulating inflammatory parameters and indexes with machine learning (ML) algorithms.Patients and Methods: We tested the genome-wide association of circulating inflammatory molecules (CIMs) (91 circulating inflammatory cytokines and 10 inflammatory cells) and summary data retrieved from the UK biobank (cases = 1659 and controls =381,902) with two-sample Mendelian randomization (MR) and colocalization analyses. …”
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Short time solar power forecasting using P-ELM approach by Shuqi Shi, Boyang Liu, Long Ren, Yu Liu

“…This paper proposes an accurate short-term solar power forecasting method using a hybrid machine learning algorithm, with the system trained using the pre-trained extreme learning machine (P-ELM) algorithm. …”
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A technique of building a value function at the stage of conceptual design of microprocessor systems by B. N. Chugaev, M. A. Shaposhnikova

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A review of the critical conditions required for effective hole cleaning while horizontal drilling by Amir Shokry Youssef, Ahmed Abdulhamid Mahmoud, Salaheldin Elkatatny, Talal Al Shafloot

“…It discusses different methodologies, including empirical correlations, experimental studies, machine learning models, and modeling techniques, used to assess hole cleaning efficiency. …”
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Design and Optimization for Straw Treatment Device Using Discrete Element Method (DEM) by Shaochuan Li, Peisong Diao, Xianghao Li, Yongli Zhao, Hongda Zhao

“…This research provides valuable insights for further parameter optimization and component development.…”
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Acoustic Voice Analysis as a Tool for Assessing Nasal Obstruction: A Systematic Review by Gamze Yesilli-Puzella, Emilia Degni, Claudia Crescio, Lorenzo Bracciale, Pierpaolo Loreti, Davide Rizzo, Francesco Bussu

“…A notable gap exists in the integration of advanced analytical approaches, such as machine learning, in this field. Future research should focus on the use of advanced analytical approaches to specifically extrapolate the contribution of nasal resonance to voice thus defining the specific parameters in the voice spectrogram that can give precise information on nasal obstruction.…”
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Enhancing Model Accuracy of UAV-Based Biomass Estimation by Evaluating Effects of Image Resolution and Texture Feature Extraction Strategy by Yaxiao Niu, Xiaoying Song, Liyuan Zhang, Lizhang Xu, Aichen Wang, Qingzhen Zhu

“…In response to this problem, spectral indices (SIs) were derived from UAV RGB images with four spatial resolutions, and eight gray-level co-occurrence matrix TFs were calculated using different calculation parameters (TF&#x005F;CP) including six window sizes and four directions. …”
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