Predicting Compressive Strength of Concrete Containing Industrial Waste Materials: Novel and Hybrid Machine Learning Model by Mohammed Majeed Hameed, Mustafa Abbas Abed, Nadhir Al-Ansari, Mohamed Khalid Alomar

“…The suggested models are evaluated against extreme learning machine (ELM) via quantitative and visual evaluations. …”
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Comprehensive Environmental Monitoring System for Industrial and Mining Enterprises Using Multimodal Deep Learning and CLIP Model by Shuqin Wang, Na Cheng, Yan Hu

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scSMD: a deep learning method for accurate clustering of single cells based on auto-encoder by Xiaoxu Cui, Renkai Wu, Yinghao Liu, Peizhan Chen, Qing Chang, Pengchen Liang, Changyu He

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Perbandingan Metode Supervised Machine Learning untuk Prediksi Prevalensi Stunting di Provinsi Jawa Timur by M Syauqi Haris, Ahsanun Naseh Khudori, Wahyu Teja Kusuma

“…In addition, several methods in supervised machine learning are also compared, namely, linear regression, support vector regression, and random forest regression. …”
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Living, Caring, Learning – Collaborating across borders to support a haemophilia patient with a rare complication by Githinji Cyrus

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Fusion-Learning-Based Optimization: A Modified Metaheuristic Method for Lightweight High-Performance Concrete Design by Ghodrat Rahchamani, Seyed Mojtaba Movahedifar, Amin Honarbakhsh

“…It is possible to accurately predict the quality of concrete and the amount of raw materials used using machine learning-enhanced methods. An automated process based on machine learning strategies is proposed in this paper for predicting the compressive strength of concrete. …”
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Diagnosis of Coronary Heart Disease Through Deep Learning-Based Segmentation and Localization in Computed Tomography Angiography by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

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Classification of NSCLC subtypes using lung microbiome from resected tissue based on machine learning methods by Pragya Kashyap, Kalbhavi Vadhi Raj, Jyoti Sharma, Naveen Dutt, Pankaj Yadav

“…To address this, we developed a machine learning-based approach utilizing resected lung-tissue microbiome of AC and SCC patients for subtype classification. …”
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Comparison of Machine Learning Algorithms for the Prediction of Mechanical Stress in Three-Phase Power Transformer Winding Conductors by Fausto Valencia, Hugo Arcos, Franklin Quilumba

“…To simplify the design, only one hyperparameter was varied on each machine learning technique. The random forests technique had the most accurate results. …”
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Human mobility is well described by closed-form gravity-like models learned automatically from data by Oriol Cabanas-Tirapu, Lluís Danús, Esteban Moro, Marta Sales-Pardo, Roger Guimerà

“…Here, we show that simple machine-learned, closed-form models of mobility can predict mobility flows as accurately as complex machine learning models, and extrapolate better. …”
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Predicting cadmium enrichment in crops/vegetables and identifying the effects of soil factors based on transfer learning methods by Rui Chen, Zean Liu, Jingyan Yang, Tiantian Ma, Aihong Guo, Rongguang Shi

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Using deep learning model integration to build a smart railway traffic safety monitoring system by Chin-Chieh Chang, Kai-Hsiang Huang, Tsz-Kin Lau, Chung-Fah Huang, Chun-Hsiung Wang

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Exploration Degree Bias: The Hidden Influence of Node Degree in Graph Neural Network-Based Reinforcement Learning by Peter Tarabek, David Matis

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FS-DDPG: Optimal Control of a Fan Coil Unit System Based on Safe Reinforcement Learning by Chenyang Li, Qiming Fu, Jianping Chen, You Lu, Yunzhe Wang, Hongjie Wu

Subjects: “…safe reinforcement learning…”
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Machine Learning as a Downscaling Approach for Prediction of Wind Characteristics under Future Climate Change Scenarios by Abbas Yeganeh-Bakhtiary, Hossein EyvazOghli, Naser Shabakhty, Bahareh Kamranzad, Soroush Abolfathi

“…In the present study, the Model Output Statistics (MOS) method was used to downscale a Coupled Model Intercomparison Project Phase 5 (CMIP5) with General Circulation Model (GCM) results for a case study in the North Atlantic Ocean, and a supervised machine learning method (M5’ Decision Tree model) was developed for the first time to establish a statistical relationship between predicator and predicant. …”
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Using Inertial Measurement Units and Machine Learning to Classify Body Positions of Adults in a Hospital Bed by Eliza Becker, Siavash Khaksar, Harry Booker, Kylie Hill, Yifei Ren, Tele Tan, Carol Watson, Ethan Wordsworth, Meg Harrold

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An Efficient Malware Detection Approach Based on Machine Learning Feature Influence Techniques for Resource-Constrained Devices by Subir Panja, Subhash Mondal, Amitava Nag, Jyoti Prakash Singh, Manob Jyoti Saikia, Anup Kumar Barman

“…Utilizing a machine learning (ML) based model is a superior option for promptly identifying malware. …”
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Unlocking the link: predicting cardiovascular disease risk with a focus on airflow obstruction using machine learning by Xiyu Cao, Jianli Ma, Xiaoyi He, Yufei Liu, Yang Yang, Yaqi Wang, Chuantao Zhang

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Plant MicroRNA Prediction by Supervised Machine Learning Using C5.0 Decision Trees by Philip H. Williams, Rod Eyles, Georg Weiller

“…A variety of machine learning methods have successfully predicted miRNA precursors, mature miRNAs, and other nonprotein coding sequences. …”
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Penggunaan Model Pembelajaran Student Centered Learning (SCL) Pada Mata Kuliah Kimia Bahan Alam by Lili Andriyani

Subjects: “…student centered learning…”
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