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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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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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

“…We employ seven machine learning algorithms: Decision Tree, Logistic Regression, Support Vector Machine (SVM), Random Forest, Bagged Trees, Naive Bayes, and XGBoost, to identify key risk factors, with XGBoost demonstrating higher performance. …”
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Research on Welfare Robots: A Multifunctional Assistive Robot and Human–Machine System by Shuoyu Wang

“…In this paper, we discuss the research challenge points of human–machine welfare robot systems and their current situation using the multifunctional assistive robot as a typical example.…”
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Super Virus Machines: Faster Virus Transmission, More Efficiency Using Superchannels by Antonio Ramírez-de-Arellano-Marrero, Luis Valencia-Cabrera, David Orellana-Martín, Mario J. Pérez-Jiménez

“…The branch that approaches it from a theoretical point of view, inspired by nature, is called natural computation. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…To solve the problem of insufficient accuracy in the single surrogate model, this study proposes a CBR surrogate model that integrates convolutional neural networks with backpropagation and radial basis function models. The coordinates of the control points of the NURBS surface at the bulbous bow are taken as the design variables. …”
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Gold nanobiosensors and Machine Learning: Pioneering breakthroughs in precision breast cancer detection by Soheil Sadr, Ashkan Hajjafari, Abbas Rahdar, Sadanand Pandey, Parian Poorjafari Jafroodi, Narges Lotfalizadeh, Mahdi Soroushianfar, Shahla Salimpour Kavasebi, Zelal Kharaba, Sonia Fathi-karkan, Hassan Borji

“…The integration of gold nanobiosensors with emerging technologies, including microfluidics and machine learning, opens new perspectives for personalized diagnostics and point-of-care testing in resource-constrained settings. …”
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A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer. by Yifei Wang, Bingbing Chen, Jinhai Yu

“…<h4>Background</h4>The unique anatomical characteristics and blood supply of the rectosigmoid junction confer particular significance to its physiological functions and clinical surgeries. However, research on the prognosis of rectosigmoid junction cancer (RSC) is scarce, and reliable clinical prediction models are lacking.…”
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Legal aspects of functional security standardisation of the Internet of Things by P. S. Klimushyn, V. Ye. Roh, T. P. Kolisnyk

“…The functional security of the Internet of Things has been studied in terms of the security function, security completeness and resilience, which are subject to regulation in the technical requirements for the product being designed. …”
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The VNF Cybersecurity Dataset for Research (VNFCYBERDATA) by Believe Ayodele, Victor Buttigieg

“…Virtualisation has received widespread adoption and deployment across a wide range of enterprises and industries throughout the years. Network Function Virtualisation (NFV) is a technical concept that presents a method for dynamically delivering virtualised network functions as virtualised or software components. …”
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Modelling Soil Water Retention Using Support Vector Machines with Genetic Algorithm Optimisation by Krzysztof Lamorski, Cezary Sławiński, Felix Moreno, Gyöngyi Barna, Wojciech Skierucha, José L. Arrue

“…This work presents point pedotransfer function (PTF) models of the soil water retention curve. …”
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Best Possible Approximation Algorithms for Single Machine Scheduling with Increasing Linear Maintenance Durations by Xuefei Shi, Dehua Xu

“…We consider a single machine scheduling problem with multiple maintenance activities, where the maintenance duration function is of the linear form ft=a+bt with a≥0 and b>1. …”
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Machine learning models highlight environmental and genetic factors associated with the Arabidopsis circadian clock by Connor Reynolds, Joshua Colmer, Hannah Rees, Ehsan Khajouei, Rachel Rusholme-Pilcher, Hiroshi Kudoh, Antony N. Dodd, Anthony Hall

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