Performance Analysis of Diabetes Detection Using Machine Learning Classifiers by Hung Huynh, Liu Hui, Ngoc Han Nguyen, Ruixuan Qiao

“…Three types of machine learning classifiers are used: Tree-based, Function-based, and Rule-based. …”
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Fault Diagnosis of Axial Piston Pump Based on Extreme-Point Symmetric Mode Decomposition and Random Forests by Lei Yafei, Jiang Wanlu, Niu Hongjie, Shi Xiaodong, Yang Xukang

“…Aiming at fault diagnosis of axial piston pumps, a new fusion method based on the extreme-point symmetric mode decomposition method (ESMD) and random forests (RFs) was proposed. …”
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$$\alpha$$ -decay half-life predictions with support vector machine by Amir Jalili, Feng Pan, Jerry P. Draayer, Ai-Xi Chen, Zhongzhou Ren

“…Our analysis of 2232 nuclear data points demonstrates that the use of the radial basis function kernel yields predictive models with root mean square errors of 0.819 (for set1) and 0.352 (for set2), aligning with results obtained from comparable machine learning methodologies. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functional remodeling of the left ventricle in certain pathologies. …”
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Recent advances in ultra-precision machining of lithium niobate crystals by Yebing TIAN, Chengwei WEI, Xiaomei SONG, Cheng QIAN

“…Given the fundamental challenges and technological implications, the ultra-precision machining of LiNbO3 crystals is expected to remain a focal point of research for the foreseeable future, warranting continued investigation and development in this field.…”
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Machine Learning in Cyber-Physical Systems and Manufacturing Singularity – it Does Not Mean Total Automation, Human Is Still in the Centre: Part I – Manufacturing Singularity and a... by Goran D. PUTNIK, Vaibhav SHAH, Zlata PUTNIK, Luis FERREIRA

“…In many popular, as well scientific, discourses it is suggested that the "massive" use of Artificial Intelligence, including Machine Learning, and reaching the point of ‘singularity’ through so-called Artificial General Intelligence (AGI), and Artificial Super-Intelligence (ASI), will completely exclude humans from decision making, resulting in total dominance of machines over human race. …”
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Knee Osteoarthritis Detection and Classification Using Autoencoders and Extreme Learning Machines by Jarrar Amjad, Muhammad Zaheer Sajid, Ammar Amjad, Muhammad Fareed Hamid, Ayman Youssef, Muhammad Irfan Sharif

“…Background/Objectives: Knee osteoarthritis (KOA) is a prevalent disorder affecting both older adults and younger individuals, leading to compromised joint function and mobility. Early and accurate detection is critical for effective intervention, as treatment options become increasingly limited as the disease progresses. …”
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A new method for reconstructing building model using machine learning by Shengjie Wu, Haibo Ye, Antao Li, Huawei Tu, Shenxin Xu, Dong Liang

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On Safety of Unary and Non-unary IFP-operators by Sergey Dudakov

“…In this paper, we investigate the safety of unary inflationary fixed point operators (IFPoperators). The safety is a computability in finitely many steps. …”
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Using Nearest-Neighbor Distributions to Quantify Machine Learning of Materials’ Microstructures by Jeffrey M. Rickman, Katayun Barmak, Matthew J. Patrick, Godfred Adomako Mensah

“…In particular, we assess the rate of microstructural learning in terms of the moments of the <i>k</i>-th nearest-neighbor pixel distributions and associated metrics, including a microstructural cross-entropy, that embody the spatial correlations among the pixels through a hierarchy of <i>n</i>-point correlation functions. From the moments of these distributions, we obtain so-called learning functions that highlight the rate at which the important topological features of a grain-boundary network appear. …”
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Utilising machine learning classification models for meteorological drought monitoring and analysis by Iqra Mumtaz, Rizwan Niaz, Zamama Sajid, Abdu Qaid Alameri, Zulfiqar Ali, Khaled A. Gepreel

“…Independent variables included average temperature, specific humidity, soil moisture, and dew point. To address model-specific challenges, ridge regression was applied to mitigate multicollinearity in Logistic Regression, while SVM incorporated the Radial Basis Function (RBF) kernel and isolation forest to manage non-linearity and outliers. …”
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RESEARCH ON THE 8-BALL UNIVERSAL JOINT INNER SLEEVE STRUCTURE AND STATIC STRENGTH DESIGN MATCHING BASED ON STRENGTH FIELD by HUANG JiaWei, LU Xi

“…The results show that the eight-channel constant speed universal joint inner sleeve designed according to the static strength design method of structure based on strength field can meet the strength and functional requirements.…”
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Defect modeling in semiconductors: the role of first principles simulations and machine learning by Md Habibur Rahman, Arun Mannodi-Kanakkithodi

“…Here, we provide a comprehensive overview of the current state of research on point defects in semiconductors, focusing on the application of density functional theory (DFT) and machine learning (ML) in accelerating the prediction and understanding of defect properties. …”
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Clinician Attitudes and Perceptions of Point-of-Care Information Resources and Their Integration Into Electronic Health Records: Qualitative Interview Study by Marlika Marceau, Sevan Dulgarian, Jacob Cambre, Pamela M Garabedian, Mary G Amato, Diane L Seger, Lynn A Volk, Gretchen Purcell Jackson, David W Bates, Ronen Rozenblum, Ania Syrowatka

“…Some recommended that further integration would allow us to leverage existing POCI tool features, such as chatbots and knowledge links, as well as aspects of artificial intelligence and machine learning, such as predictive algorithms and personalized alert systems, to enhance EHR functionality. …”
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Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…<i>Background and Objectives</i>: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterised by joint inflammation and pain. Metabolomics approaches, which are high-throughput profiling of small molecule metabolites in plasma or serum in RA patients, have so far provided biomarker discovery in the literature for clinical subgroups, risk factors, and predictors of treatment response using classical statistical approaches or machine learning models. …”
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NIMS polymer database PoLyInfo (I): an overarching view of half a million data points by Masashi Ishii, Takuro Ito, Hiroko Sado, Isao Kuwajima

“…We also describe the data curation policy of PoLyInfo, which can be observed through search functions and data tables, and show the unique taxonomy of various polymers. …”
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Human and Machine: A View through Kant's Use of Regulative Reason by Ümit Taştan

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Evaluation of a novel elbow joint torque measurement device in healthy subjects and stroke patients: a randomized trial by Qingqin Xu, Mengxuan Hu, Lei Li, Shi Chen, Bo Liu, Jianwei Lu, Hemu Chen

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Machine learning technology in the classification of glaucoma severity using fundus photographs by Sukhumal Thanapaisal, Passawut Uttakit, Worapon Ittharat, Pukkapol Suvannachart, Pawasoot Supasai, Pattarawit Polpinit, Prapassara Sirikarn, Panawit Hanpinitsak

“…Glaucoma severity grading was based on the Hodapp-Parrish-Anderson (HPA) criteria incorporating the mean deviation value, defective points in the pattern deviation probability map, and defect proximity to the fixation point. …”
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Symmetric physically unclonable functions of the arbiter type by V. N. Yarmolik, A. A. Ivaniuk

“…It is shown that the joint use of these functions, on the one hand, makes it possible to achieve high characteristics of the APUF, and on the other hand, leads to the formation of an asymmetric behavior of the APUF. …”
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