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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PLFF-SLAM: A Point and Line Feature Fused Visual SLAM Algorithm for Dynamic Illumination Environments by Shucheng Huang, Wenhan Ren, Mingxing Li

“…Firstly, we designed a point feature extraction method based on the GCNV2 network, which improves the extraction performance of the point feature network by modifying the encoding layer structure and reconstructing the loss function. …”
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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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Postoperative Adverse Outcomes in Patients With Frailty Undergoing Urologic Surgery Among American Patients: A Propensity-Score Matched Retrospective Cohort Study by Hsu CW, Chang CC, Lam F, Liu MC, Yeh CC, Chen TL, Lin CS, Liao CC

“…The mFI-5 includes five items: hypertension, diabetes, congestive heart failure, chronic obstructive pulmonary disease, and physical function status. Each item is assigned one point, and an mFI-5 score of 2 or greater indicates frailty. …”
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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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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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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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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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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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Investigation using single point incremental forming (SPIF) to fabricate patient-specific, titanium orbital floor implants by Mamros Elizabeth M., Blaha Lauren E., Kauffman Christian A.

“…This investigation focuses on single-point incremental forming as a novel technique to fabricate patient-specific orbital floor implants. …”
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Terrain and individual tree vertical structure-based approach for point clouds co-registration by UAV and Backpack LiDAR by Tingwei Zhang, Xin Shen, Lin Cao

“…Second, individual tree positions were extracted from each platform’s LiDAR dataset and employed as key feature points for matching. Third, a similarity function was constructed to evaluate the most geometrically consistent point correspondences across platforms, which were subsequently refined through an Iterative Closest Point (ICP) algorithm. …”
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Variational Autoencoder Transfer Functions for Onshore Tsunami Hazard Curves by Willington Renteria, Patrick Lynett, Maile McCann, Behzad Ebrahimi, Hong Kie Thio, Ian Robertson, Chris Siverd, Betsy Hicks

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Solving the Control Synthesis Problem Through Supervised Machine Learning of Symbolic Regression by Askhat Diveev, Elena Sofronova, Nurbek Konyrbaev

“…Initially, the optimal control problem is solved from each point in a given set of initial states, resulting in a collection of control functions expressed as functions of time. …”
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Effect of Cutting Tool Rake and Inclination Angles and Feeding Method on Cutting Force and Surface Quality in Single-point Threading by Rzgar Mhammed Abdalrahman, Sarkawt Rostam, Abdelhakim Deboucha

“… Single-point threading is the most common and useful thread machining technique. …”
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Multi-objective Optimization Method for Pocket Milling Driven by Massive Virtual Machining by SHEN Bin, TU Weiyi, NIE Pengfei, WANG Chenghan, AI Di, WU Jun, ZHENG Zujie, GUO Guoqiang

“…The neural network is combined to predict the machining state. The objective function and constraint conditions are set, and the gradient descent method is used to optimize the feed rate and spindle speed. …”
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