Optimization of aluminum 6061 surface integrity on dry-running machining CNC milling using Taguchi methods by Rifky Maulana Yusron, Mohamad Imron Mustajib, Imam Hanafi

“…Computerized Numerical Control had excellent capability to process mass-production products. Unsubstantial machining parameter setting will lead to a lack of surface roughness or even worse damage on tool steel. …”
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Machine Learning-Based Model in Predicting the Plate-End Debonding of FRP-Strengthened RC Beams in Flexure by Tianyu Hu, Guibing Li

“…In this study, considering the extremely complicated nonlinear relationship between the PE debonding and the parameters, machine learning algorithms, namely, linear regression, ridge regression, decision tree, random forest, and neural network improved by sparrow search algorithm, are established to predict the PE debonding of RC beams strengthened with FRP. …”
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An Extreme Learning Machine Based on the Mixed Kernel Function of Triangular Kernel and Generalized Hermite Dirichlet Kernel by Senyue Zhang, Wenan Tan

“…According to the characteristics that the kernel function of extreme learning machine (ELM) and its performance have a strong correlation, a novel extreme learning machine based on a generalized triangle Hermitian kernel function was proposed in this paper. …”
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Integration of smart insoles for gait assessment in exoskeleton assisted rehabilitation by Luigi D’Arco, Haiying Wang, Huiru Zheng

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Research on Simplified Design of Model Predictive Control by Qing Zhang, Chi Zhang, Qi Wang, Shiyun Dong, Aoqi Xiao

“…PID controllers have been dominant in the field of process control for a long time, but their control quality is not ideal and the difficulty of parameter tuning has always been a problem. MPCs have good control quality and robustness, but due to the complexity of the algorithm, most are limited to software on PC machines. …”
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Computational machine learning estimation of digitoxin solubility in supercritical solvent at different temperatures utilizing ensemble methods by Hadil Faris Alotaibi, Waqed H. Hassan, Ahmed Kateb Jumaah Al-Nussairi, Narinderjit Singh Sawaran Singh, Ahmed Salah Al-Shati, M. M. Rekha, Subhashree Ray, Aashna Sinha, Gunjan Garg

“…Temperature and pressure are the input parameters, while solvent density and digitoxin solubility are the output parameters. …”
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Investigation of machining performance in ecdm of Al6061-SiC-B4C hybrid composites by Safa Lafta, Abbas Ibrahim

“…The findings emphasize the importance of parameter optimization in improving machining efficiency and surface integrity, offering valuable insights for hybrid composite applications. …”
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SSB expression is associated with metabolic parameters of 18F-FDG PET/CT in lung adenocarcinoma and can improve diagnostic efficiency by Zi-Yue Liu, Ling-Ling Yuan, Yan Gao, Yu Zhang, Yao-Hua Zhang, Yi Yang, Yu-Xuan Chen, Xu-Sheng Liu, Zhi-Jun Pei

“…By utilizing 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) machines, we correlated SSB gene expression with PET/CT parameters, as well as its value in LUAD diagnosis. …”
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IMPLEMENTATION OF THE STANDARD STB ISO 7500–1–2008 «MATERIALS METALLIC. CHECK OF UNIAXIAL TESTING MACHINES FOR TESTS AT STATISTICAL LOADINGS. Part 1. Machines for tests for tension... by I. V. Bujanova, E. V. Borisenko

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Streamflow Prediction at the Intersection of Physics and Machine Learning: A Case Study of Two Mediterranean‐Climate Watersheds by S. Adera, D. Bellugi, A. Dhakal, L. Larsen

“…In this study, we performed model benchmarking to (a) compare hybrid model performance to PB and machine learning models and (b) examine the sensitivity of hybrid model performance to PB model parameter calibration, structural complexity, and variable selection. …”
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Supervised machine learning classification algorithms for detection of fracture location in dissimilar friction stir welded joints by Akshansh Mishra, Apoorv Vats

“…In the present study, four supervised machine learning-based classification models i.e. …”
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Offline-Online pattern recognition for enabling time series anomaly detection on older NC machine tools by Markus Netzer, Yannic Palenga, Philipp Goennheimer, Juergen Fleischer

“…Unfortunately, many old machines and systems are characterized by insufficient, inconsistent IoT connectivity and heterogeneous parameter naming. …”
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Experimental Investigation of Dynamic Contact Stiffness and Damping in Mixed Lubrication for Machine Tool Sliding Guide Interfaces by Huailin Li, Haonan Dong, Yunpeng Xi, Zhiqiang Gao

“…This paper presents an experimental study on the dynamic contact stiffness and damping characteristics of hybrid lubricated mechanical motion joint surfaces formed by machine tool sliding guides. A stiffness and damping parameter testing system was established, utilizing an m+p dynamic signal acquisition and analysis system as its centerpiece. …”
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A Closed-Loop Brain Stimulation Control System Design Based on Brain-Machine Interface for Epilepsy by Moshu Qian, Guanghua Zhong, Xinggang Yan, Heyuan Wang, Yang Cui

“…The stability and reachability analysis of the closed-loop tracking control system gives the guideline of parameter selection, and simulation results based on comprehensive comparisons are carried out to demonstrate the effectiveness of proposed approach.…”
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Modeling and Optimization of MRR in Wire Electrical Discharge Machining of Silicon Particle-Reinforced AA6063 Composite by CR Mahesha, R .Suprabha, NPG Bhavani, Prashant Sunagar, Raja Ramesh, P. Balamurugan, Rajasekar Rajendran, Anirudh Bhowmick

“…This work studies the machinability of Al 6063 reinforced with silicon carbide particles with wire electrical discharge machining. …”
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Improving End-Point Position Control in Hydraulic Testing Machines with a Fuzzy Logic Based Approach by Serkan Anlak, Ekrem Düven

“…During the repetitive operation of hydraulic testing machines, some undesirable vibration movements and non-compliance with the set value may occur at the piston end-point, which is the output of the system. …”
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An Interpretable Machine Learning Procedure Which Unravels Hidden Interplanetary Drivers of the Low Latitude Dayside Magnetopause by Sheng Li, Yang‐Yi Sun, Chieh‐Hung Chen

“…Abstract In this study, we propose an interpretable machine learning procedure to unravel the importance of multiple interplanetary parameters to the Earth's magnetopause standoff distance (MSD). …”
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Reliability-Centered Maintenance: Analyzing Failure in Harvest Sugarcane Machine Using Some Generalizations of the Weibull Distribution by Pedro L. Ramos, Diego C. Nascimento, Camila Cocolo, Márcio J. Nicola, Carlos Alonso, Luiz G. Ribeiro, André Ennes, Francisco Louzada

“…Maximum likelihood is used for parameter estimation. Further, different discrimination procedures were used to obtain the best fit for each component. …”
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Assessing the Impact of Multimodal Transportation on Economic Growth: A Machine Learning and Cointegration Approach in 28 Countries by Esme Isik, Ayfer Ozyilmaz, Yüksel Bayraktar, Metin Toprak, Mehmet Fırat Olgun, Nazli Keyifli Senturk

“…According to the cointegration analysis, all transportation modes (road, rail, and air) are cointegrated with growth. Additionally, machine learning models were used to predict growth based on each transportation mode for each country for the upcoming four years and to determine the importance of the input parameters. …”
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Research on state machine control optimization of double-stack fuel cell/super capacitor hybrid system. by Mengjie Li, Qianchao Liang, Jianfeng Zhao, Yongbao Liu, Yan Qin

“…Utilizing a polynomial differentiation approach, the parameter equation for the maximum system efficiency is computed. …”
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