Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

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STATE-OF-THE-ART OF MACHINE LEARNING IN NEURO DEVELOPMENT DISORDER: A SYSTEMATIC REVIEW by Lilian Yen Wei Lee, Ag Asri Ag Ibrahim, Rayner Alfred

“…The search employed terms such as "Predicting Neurodevelopmental Disorder" and/or "Detection of Disorder using Machine Learning." The analysis focuses on identifying common ML and DL approaches, ensemble models, types of datasets utilized, as well as the parameters and performance metrics employed in NDD prediction and detection studies. …”
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Performance evaluation of rotor shears machine with bottom sieves for comminution of waste PCB by Radon Dhelika, Daniel Meino Soedira

“…Utilizing a low-speed, high-torque rotor shears design, the research investigates the impact of operational parameters, specifically sieve sizes (4 mm, 6 mm, and 8 mm) and motor speeds (700 rpm, 850 rpm, 1000 rpm, and 1150 rpm), on the machine’s performance in terms of particle size distribution, material liberation, and machine throughput. …”
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INVESTIGATION OF SURFACE MACROSCOPIC RESIDUAL STRESSES OF CUTTING CERAMICS AFTER MECHANICAL MACHINING by Jakub Němeček, Jiří Čapek, Nikolaj Ganev, Kamil Kolařík

“…The resulting values were discussed depending on machining parameters and surface structure of the studied samples.…”
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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

“…Regional variations of the four parameters and their effects on regional WWTP electricity consumption are elaborated. …”
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Machine learning based seizure classification and digital biosignal analysis of ECT seizures by Max Kayser, René Hurlemann, Alexandra Philipsen, Nils Freundlieb, Maximilian Kiebs

“…To this end, we developed the first machine learning (ML) framework that can classify ictal and non-ictal EEG segments, accurately identifying seizure endpoints—a critical step in deriving seizure quality parameters—and computing these metrics at least as reliable as existing precomputed scores. …”
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Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning by Yan Zhu, Li Wang, Aichao Ruan, Zhiyu Peng, Zhenzhong Zhang

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Investigation of Inlet Guide Vane Efficiency in Centrifugal Compressors for the Turbo Refrigeration Machines by Danilishin A.M., Kozhukhov Y. V., Fateeva E.S., Aksenov A.A.

“…The article investigates the influence of geometric parameters of inlet guide vanes (IGVs), including blade profiling and design features, on their operational efficiency. …”
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Machine learning-based equations for improved body composition estimation in Indian adults. by Nick Birk, Bharati Kulkarni, Santhi Bhogadi, Aastha Aggarwal, Gagandeep Kaur Walia, Vipin Gupta, Usha Rani, Hemant Mahajan, Sanjay Kinra, Poppy A C Mallinson

“…We combined BIA measurements (TANITA BC-418) with skinfold thickness, body circumferences, and grip strength to develop equations to predict six DXA-measured body composition parameters in a cohort of Indian adults using machine learning techniques. …”
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ASPECTS REGARDING THE TECHNICAL EXPERTISE OF ELECTRIC EQUIPMENT CABIN OF THE COAL MINING MACHINE by Marius Liviu CÎRŢÎNĂ, Alin STĂNCIOIU, Constanța RĂDULESCU

“…In this paper we presents technical condition, how it looks and which deffects are electrical cabin of coal mining machine after technical expertise made it. The rehabilitation to which electric cabinets will be subjected will be done by performing the intervention works that will restore both the structural part and the functional part in the normal operating parameters. …”
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Prediction of Horizontal in Situ Stress in Shale Reservoirs Based on Machine Learning Models by Wenxuan Yu, Xizhe Li, Wei Guo, Hongming Zhan, Xuefeng Yang, Yongyang Liu, Xiangyang Pei, Weikang He, Longyi Wang, Yaoqiang Lin

“…To address the limitations of traditional methods in modeling complex nonlinear relationships in horizontal in situ stress prediction for shale reservoirs, this study proposes an integrated framework that combines well logging interpretation with machine learning to accurately predict horizontal in situ stress in shale reservoirs. …”
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Near-Infrared Spectroscopy and Machine Learning for Fast Quality Prediction of Bottle Gourd by Xiao Guo, Hongyu Huang, Haiyan Wang, Chang Cai, Ying Wang, Xiaohua Wu, Jian Wang, Baogen Wang, Biao Zhu, Yun Xiang

“…Protein and amino acid content are the crucial quality parameters in bottle gourd, and traditional measurement methods for detecting those parameters are complicated, time-consuming, and costly. …”
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THE METHOD OF RECEIPTION OF FINAL VOLUME SET OF WEIGHT AVERAGE TENSION IN THE DETAILS OF THE MACHINES by V. E. KASYANOV, T. N. ROGOVENKO, M. M. ZAITSEVA

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Machine learning derivation of two cardiac arrest subphenotypes with distinct responses to treatment by Weidong Zhang, Chenxi Wu, Peifeng Ni, Sheng Zhang, Hongwei Zhang, Ying Zhu, Wei Hu, Mengyuan Diao

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Study on Thermal Conductivity Prediction of Granites Using Data Augmentation and Machine Learning by Yongjie Ma, Lin Tian, Fuhang Hu, Jingyong Wang, Echuan Yan, Yanjun Zhang

“…This study provides quantitative evidence for data augmentation and machine learning in predicting rock thermophysical parameters, promoting intelligent geothermal resource development.…”
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Predictive Modeling for Diabetes Subtype Classification in India: A Machine Learning Approach by Ulagamadesan Venkatesan, Anandakumar Amutha, Ranjit Mohan Anjana, Ranjit Unnikrishnan, Bagavandas Mappillairaju, Viswanathan Mohan

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Machine learning-based approach for bandwidth and frequency prediction of circular SIW antenna by Md Mahabub Alam, Nurhafizah Abu Talip Yusof, Ahmad Afif Mohd Faudzi, Md Raihanul Islam Tomal, Md Ershadul Haque, Md. Suaibur Rahman

“…Abstract Machine Learning (ML) has significantly transformed antenna design by enabling efficient optimization of geometrical parameters, modeling complex electromagnetic behavior, and accelerating performance prediction with reduced computational cost. …”
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A Machine-Learning-Based Classification Method for Meteorological Conditions of Ozone Pollution by Yang Cao, Xiaoli Zhao, Debin Su, Xiang Cheng, Hong Ren

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Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing by Lifei Wang, Yucheng Gu, Xiaoqing Tian, Jun Wang, Yan Jia, Junjie Xu, Zhen Zhang, Shiying Liu, Shuo Liu

“…However, due to the unclear influence mechanisms of process parameters, as well as the high cost and time-consuming nature of experiments, identifying the optimal femtosecond laser processing parameters within the process space remains a significant challenge. …”
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Prediction on rock strength by mineral composition from machine learning of ECS logs by Dongwen Li, Xinlong Li, Li Liu, Wenhao He, Yongxin Li, Shuowen Li, Huaizhong Shi, Gaojian Fan

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