Investigation of operation factors in the self-balancing device of the washing machine in resonance zone by Sergey N. Alekhin, Sergey P. Petrosov, Alexey S. Alekhin

“…The paper objective is to solve the issues related to the increase of reliability, profitability, and safety of modern washing machines on the basis of decrease in dynamic loads under whizzing. …”
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An approach to estimate occupational accidents using least-squares support vector machines by Hüseyin Ceylan, Şakir Parlakyıldız

“… Least-squares support vector machines represent an emerging technique that has been adopted to estimate accidents. …”
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Machine Learning Exploration of Experimental Conditions for Optimized Electrochemical CO2 Reduction by Vuri Ayu Setyowati, Shiho Mukaida, Kaito Nagita, Takashi Harada, Shuji Nakanishi, Kazuyuki Iwase

“…This ML‐based approach allowed us to quantitatively assess the effect of experimental parameters on these targets with a reduced number of experimental trials (only 56 experiments). …”
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Comparative Analysis of Machine Learning Models for CO Emission Prediction in Engine Performance by Beytullah Eren, İdris Cesur

“…This study presents a comparative analysis of machine learning models for predicting carbon monoxide (CO) emissions in automotive engines. …”
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Knowledge embedding and interpretable machine learning optimize comprehensive benefits for water treatment by Yu-Qi Wang, Wenchong Tian, Hao-Lin Yang, Yun-Peng Song, Jia-Ji Chen, Qiong-Ying Xu, Wan-Xin Yin, Le-Qi Ding, Xi-Qi Li, Han-Tao Wang, Ai-Jie Wang, Hong-Cheng Wang

“…Leveraging multi-stage water quality parameters, we developed a machine learning (ML) framework for coagulation control that incorporates knowledge embedding (KE) through hyper-parametric constraints on threshold water quality, energy consumption, and economic costs. …”
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Refined Judgment of Urban Traffic State Based on Machine Learning and Edge Computing by Lijuan Liu

“…Machine learning is a discipline that covers probability theory, statistics, approximate theoretical knowledge, and complex algorithm knowledge. …”
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Advanced machine learning for regional potato yield prediction: analysis of essential drivers by Dania Tamayo-Vera, Morteza Mesbah, Yinsuo Zhang, Xiuquan Wang

“…This research evaluates machine learning models, including Random Forest and Gradient Boosting, for predicting crop yields. …”
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Transforming Cardiac Care: Machine Learning in Heart Condition Prediction Using Phonocardiograms by Sandra D’Souza, Niranjan Reddy S, Saikonda Krishna Tarun, Sohan P, aneesha acharya k

“…Heart diseases are primarily caused by a multitude of parameters, including high blood pressure, diabetes, and excessive cholesterol, which are controlled by poor dietary and lifestyle choices. …”
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Prediction of the sound absorption performance for micro-perforated panel based on machine learning by Binxia Yuan, Tianqi You, Huanhuan Jiang, Hong Qian, Lan Cao, Rui Zhu

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Research on the mechanism of human-machine security collaboration of miners considering automation trust by Juan Yang, Xue Yang, Shan Chai, Likun Ni, Xiao Wang, Langxuan Pan

“…With the implementation of intelligent construction in coal mines, humans–machine collaboration is critical to accident prevention. …”
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Data-efficient optimization of thermally-activated polymer actuators through machine learning by Yuhao Zhang, Maija Vaara, Azin Alesafar, Duc Bach Nguyen, Pedro Silva, Laura Koskelo, Jussi Ristolainen, Matthias Stosiek, Joakim Löfgren, Jaana Vapaavuori, Patrick Rinke

“…To overcome these problems, we employed an active machine learning workflow using Bayesian optimization. …”
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Assessment of Electrical Machines’ State Based on Mathematical Modeling of Defect Formation in Windings by A. V. Isaev, U. V. Suchodolov, D. V. Balakhonov

“…Mathematical models of the phase-frequency characteristics are obtained, coefficients of polynomials are determined and the relative discrepancy between these mathematical dependences relative to the experimental data is estimated depending on the considered parameters characterizing defects in the coils’ windings of electrical machines.Obtained mathematical models and coefficients for them can serve as the basis for construction of automated control and diagnostic systems for checking of the windings state of electrical machines including assessing the residual life of their work.…”
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Comparisons of Machine Learning Methods in Ship Speed Prediction Based on Shipboard Observation by Weidong Gan, Dianguang Ma, Yu Duan

“…Six machine learning models—the Backpropagation (BP) Neural Network, Support Vector Regression (SVR), Decision Tree (DT), Random Forest (RF), XGBoost, and LightGBM—were employed to develop predictive models. …”
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Performance comparison of machine learning algorithms for condition monitoring of tapered roller bearings by Harshal Aher, Nilesh Ghuge

“…This paper investigated the implementation of machine learning algorithms for health monitoring and fault detection of tapered roller bearings (TRBs) (30205 J2/Q, 30206 J2/Q and 30207 J2/Q). …”
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QM40, Realistic Quantum Mechanical Dataset for Machine Learning in Molecular Science by Ayesh Madushanka, Renaldo T. Moura, Elfi Kraka

“…Abstract The growing popularity of machine learning (ML) and deep learning (DL) in scientific fields is hindered by the scarcity of high-quality datasets. …”
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Integrated Iot Approaches for Crop Recommendation and Yield-Prediction Using Machine-Learning by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…In this study, we present an integrated approach utilizing IoT data and machine learning models to enhance precision agriculture. …”
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Artificial liver classifier: a new alternative to conventional machine learning models by Mahmood A. Jumaah, Yossra H. Ali, Tarik A. Rashid

“…IntroductionSupervised machine learning classifiers sometimes face challenges related to the performance, accuracy, or overfitting.MethodsThis paper introduces the Artificial Liver Classifier (ALC), a novel supervised learning model inspired by the human liver's detoxification function. …”
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The Prediction of Somatic Cell Count Through Multilayer Perceptron of Deep Machine Learning by M. İ. Yeşil, S. Göncü

“…The test model (ANN) had a higher performance (AIC=-338) than the control model (AIC=-240) created with the classical linear model despite using more parameters (81). Using big data from automated milking information—like estrus cycle, lactation stage, and milk yield—on supercomputers can improve the accuracy of performance assessments in dairy farming. …”
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Influence of simulated traffic on foundation pit deformation via machine vision technology by Xi Wu, Miao-Miao Sun, Zhi-Yu Xie, Song-Qiang Chen, Zhen-Yu Zhang, Xing-Lang Fan, Hai-Min Qian

“…Following statistical analysis of traffic parameters, Monte Carlo sampling is utilised to simulate actual traffic loads. …”
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Sequential learning on a tensor network Born machine with trainable token embedding by Wanda Hou, Miao Li, Yi-Zhuang You

“…Quantum-inspired generative models, such as Born machines based on the matrix product state (MPS) framework, have demonstrated remarkable capabilities in unsupervised learning tasks. …”
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