Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. …”
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Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges by Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

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Technology of Post-Institutional Support to Exiters of State-Run Institutions for Orphans in the Process of Obtaining Professional Education and Primary Employment by Oslon V.N., Celenina E.V.

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Distributivity, partitioning, and the multiplication algorithm by Chris Hurst, Ray Huntley

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Optimizing knee osteoarthritis severity prediction on MRI images using deep stacking ensemble technique by Punita Panwar, Sandeep Chaurasia, Jayesh Gangrade, Ashwani Bilandi, Dayananda Pruthviraja

“…In order to address the limitation of time and expedite the diagnostic process, deep learning algorithms have been implemented in the medical field. …”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

Subjects: “…Arrhythmia prediction…”
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An Exploration of the Use of Educational Robotics in Preschool Education by Veronica Mihaela Rus, Beatrice Almășan

“…Given today's society, the premises of the key competencies that early childhood education must provide future students based on the Curriculum for Early Childhood Education and supported by constructivist theory (of Vygotsky's zone of proximal development), this study aims to investigate the development of computational thinking for the child in preschool education. …”
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TEACHER EDUCATION AND FEATURES OF THE CONTEMPORARY EDUCATIONAL CONTEXT by Irina G. Zakharova

“…By analogy with the Web-technologies, the concept of educational context (dynamically changing conditions in which educational content is studied) is introduced. …”
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Reduction of electric energy consumption for heating passenger railway carriages by A. А. Kuznetsov, S. S. Gorobei

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Constant time lattice reduction in dimension 4 with application to SQIsign by Otto Hanyecz, Alexander Karenin, Elena Kirshanova, Péter Kutas, Sina Schaeffler

“… In this paper we propose a constant time lattice reduction algorithm for integral dimension-4 lattices. …”
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Ensemble-Based Neighborhood Attribute Reduction: A Multigranularity View by Yuan Gao, Xiangjian Chen, Xibei Yang, Pingxin Wang, Jusheng Mi

“…Different from traditional process which computes reduct through employing a fixed granularity, our algorithm aims to obtain reduct from the viewpoint of multigranularity. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…In particular, we employed the CatBoost algorithm, trained on student activity logs from the Moodle platform. …”
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Reduction of artifacts associated with missing data in coherent diffractive imaging by Erik Malm, Yuriy Chushkin

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Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm by Hao Cai, Yue Shao, Xuan-yu Liu, Chang-ying Li, Hao-yu Ran, Hao-ming Shi, Cheng Zhang, Qing-chen Wu

“…Abstract Objectives This study aims to develop a reliable and interpretable predictive model for long-term survival in Type A aortic dissection (TAAD) patients, utilizing machine learning (ML) algorithms. …”
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Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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Domain general noise reduction for time series signals with Noisereduce by Tim Sainburg, Asaf Zorea

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Rough decision rules extraction and reduction based on granular computing by Hong-can YAN, Feng ZHANG, Bao-xiang LIU

“…Rule mining was an important research content of data mining,and it was also a hot research topic in the fields of decision support system,artificial intelligence,recommendation system,etc,where attribute reduction and minimal rule set extraction were the key links.Most importantly,the efficiency of extraction was determined by its application.The rough set model and granular computing theory were applied to the decision rule reduction.The decision table was granulated by granulation function,the grain of membership and the concept granular set construction algorithm gener-ated the initial concept granular set.Therefore,attribute reduction could be realized by the distinguish operator of concept granule,and decision rules extraction could be achieved by visualization of concept granule lattice.Experimental result shows that the method is easier to be applied to computer programming and it is more efficient and practical than the existing methods.…”
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Efficient colour filter array demosaicking with prior error reduction by M.S. Safna Asiq, WR Sam Emmanuel

“…The proposed work introduces an error efficient demosaicking algorithm. The efficient prior error reduction technique helps to obtain better results. …”
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…Three sets of comparison experiments were conducted to demonstrate the superiority of this algorithm over the others. The experimental results show that the average classification accuracy of the TMKMCRIGWO algorithm is at least 0.1% higher than the other algorithms on 20 datasets, and the average value of the dimension reduction rate (DRR) reaches 24.76%. …”
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Edge Server Placement and Task Allocation for Maximum Delay Reduction by Koki Shibata, Sumiko Miyata

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