Machine Learning Based Statistical Prediction Model for Improving Performance of Live Virtual Machine Migration by Minal Patel, Sanjay Chaudhary, Sanjay Garg

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Machine Learning for Internal Combustion Engine Optimization with Hydrogen-Blended Fuels: A Literature Review by Mateusz Zbikowski, Andrzej Teodorczyk

“…Hydrogen offers advantages such as high combustion efficiency and zero carbon emissions, yet challenges related to NO_x formation, storage, and specialized modifications persist. Machine learning (ML) techniques, including artificial neural networks (ANNs) and XGBoost, demonstrate strong predictive capabilities in optimizing engine performance and emissions. …”
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Enhancing flood prediction through remote sensing, machine learning, and Google Earth Engine by Sonia Hajji, Samira Krimissa, Kamal Abdelrahman, Abdelghani Boudhar, Abdelghani Boudhar, Abdelghani Boudhar, Abdenbi Elaloui, Maryam Ismaili, Meryem El Bouzekraoui, Mohamed Chikh Essbiti, Ali Y. Kahal, Biraj Kanti Mondal, Mustapha Namous, Mustapha Namous

“…The aim of this study was to automate the identification of flood-prone areas within a data-scarce, mountainous watershed using remote sensing (RS) and machine learning (ML) models. In this study, we integrate the Normalized Difference Flood Index (NDFI), using Google Earth Engine to generate flood inventory, which is considered a crucial step in flood susceptibility mapping. …”
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Machine Learning Algorithms Performance Evaluation for Intrusion Detection by Shyla ., Kapil Kumar, Vishal Bhatnagar

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Investigation of machining performance of waspaloy using copper-graphite composite electrodes in electric discharge machining by Priyanka Putta, Jayakumar V, Giridharan PK

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Enhanced Performance of Novel Amorphous Silicon Carbide Microelectrode Arrays in Rat Motor Cortex by Pegah Haghighi, Eleanor N. Jeakle, Brandon S. Sturgill, Justin R. Abbott, Elysandra Solis, Veda S. Devata, Gayathri Vijayakumar, Ana G. Hernandez-Reynoso, Stuart F. Cogan, Joseph J. Pancrazio

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Complementary Machining – Machining Strategy for Surface Modification: A Review by Thabo Mathonsi, Rudolph Frans Laubscher

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Optimization Design and Simulation Analysis of Horse Riding Machine based on Human Factor Engineering by Jie Huang, Zhanshu He

“…Based on the requirement of human factor engineering for safety performance， by using SolidWorks Simulation， the static analysis of the horse riding machine is carried out， and the corresponding maximum stress is also optimized. …”
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Bridging human and machine intelligence: Reverse-engineering radiologist intentions for clinical trust and adoption by Akash Awasthi, Ngan Le, Zhigang Deng, Rishi Agrawal, Carol C. Wu, Hien Van Nguyen

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Petrological controls on the engineering properties of carbonate aggregates through a machine learning approach by Javid Hussain, Tehseen Zafar, Xiaodong Fu, Nafees Ali, Jian Chen, Fabrizio Frontalini, Jabir Hussain, Xiao Lina, George Kontakiotis, Olga Koumoutsakou

“…These results highlight the ability of machine learning techniques to provide a more effective and reliable prediction of aggregate engineering properties based on petrographic data. …”
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Machine Learning-Based 3D Soil Layer Reconstruction in Foundation Pit Engineering by Chenxi Zhang, Nan Li, Xiuping Dong, Bin Liu, Meilian Liu

“…This paper proposes a machine learning-based soil layer reconstruction method to address this issue. …”
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Performance Analysis of a Waste-Gated Turbine for Automotive Engines: An Experimental and Numerical Study by Carla Cordalonga, Silvia Marelli, Vittorio Usai

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Recondition Cylinder Head Engine Wartsila Diesel 18V32DF by Hendri Van Hoten, Hairul Gustriranda, Nurbaiti Nurbaiti

“…The third  and fourth Power House consist of seven Diesel engine Generator.</p><p>To keep the engine performance stable that is produce  maximum power and prevent unknown damage that it make engine trip then the overhaul activity done.  …”
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Performance of vision language models for optic disc swelling identification on fundus photographs by Kelvin Zhenghao Li, Kelvin Zhenghao Li, Kelvin Zhenghao Li, Tuyet Thao Nguyen, Tuyet Thao Nguyen, Heather E. Moss, Heather E. Moss

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Machine learning-based risk of fall estimation using insole with force sensors while performing a sequence of activities in the TUG test by Clinton Enow Tabi, Johannes C. Ayena, Martin J.-D. Otis

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Influence of Different Textures on Machining Performance of a Milling Tool by Jianfeng Pan, Kai Feng, Lihua He, Kai Zhuang, Jing Ni, Junjie Lv

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INFLUENCE OF THE ELECTRODE MATERIAL ON ELECTRICAL DISCHARGE MACHINING PROCESS PERFORMANCE by OANA GHIORGHE, CAROL SCHNAKOVSZKY, EUGEN HERGHELEGIU, MARIA CRINA RADU, BOGDAN ALEXANDRU CHIRITA, NICOLAE CATALIN TAMPU, BOGDAN NITA, PETRICA RADU

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Advanced Morphological and Material Engineering for High‐Performance Interfacial Iontronic Pressure Sensors by Fengling Zhuo, Zhi Ding, Xi Yang, Fengjian Chu, Yulu Liu, Zhuoqing Gao, Hao Jin, Shurong Dong, Xiaozhi Wang, Jikui Luo

“…Abstract High‐performance flexible pressure sensors are crucial for applications such as wearable electronics, interactive systems, and healthcare technologies. …”
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Accurate multi-category student performance forecasting at early stages of online education using neural networks by Naveed Ur Rehman Junejo, Muhammad Wasim Nawaz, Qingsheng Huang, Xiaoqing Dong, Chang Wang, Gengzhong Zheng

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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

“…Abstract Science, Technology, Engineering, and Mathematics (STEM) education spans all levels, from preschool to postgraduate studies, fostering growth in social, cognitive, and psychomotor skills. …”
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