Effect of fabrication techniques of high entropy alloys: A review with integration of machine learning by Mohamed Yasin Abdul Salam, Enoch Nifise Ogunmuyiwa, Victor Kitso Manisa, Abid Yahya, Irfan Anjum Badruddin

“…Additionally, the integration of Machine Learning (ML) techniques in HEA research is highlighted, demonstrating their potential for optimizing fabrication parameters and predicting phase stability, microstructure evolution, and mechanical properties. …”
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Enhancing the destructive egg quality assessment using the machine vision and feature extraction technique by Ehsan Sheidaee, Pourya Bazyar

“…These findings underscore the effectiveness of combining machine vision with statistical methods to enhance the egg grading accuracy, contributing to consumer safety and industry standards.…”
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A Review of Developments and Metrology in Machine Learning and Deep Learning for Wearable IoT Devices by Minh Long Hoang

“…Additionally, this review presents metrological approaches for evaluating AI performance in wearable systems, including data quality parameters such as accuracy, precision, and sampling rate. …”
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A Novel Hybrid Network Traffic Prediction Approach Based on Support Vector Machines by Wenbo Chen, Zhihao Shang, Yanhua Chen

“…In this paper, a new hybrid network traffic prediction method (EPSVM) primarily based on Empirical Mode Decomposition (EMD), Particle Swarm Optimization (PSO), and Support Vector Machines (SVM) is presented. The EPSVM first utilizes EMD to eliminate the impact of noise signals. …”
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Hydrogen Enhancement in Syngas Through Biomass Steam Gasification: Assessment with Machine Learning Models by Yunye Shi, Diego Mauricio Yepes Maya, Electo Silva Lora, Albert Ratner

“…This study assesses the effectiveness of various machine learning algorithms in engineering, focusing on a comparative analysis of artificial neural networks (ANNs), support vector machines (SVMs), tree-based models, and regularized regression models. …”
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Experimental Evaluation of a New Perfusion Machine Using Normothermic Cycles on Explanted Livers by Eleonora Barcali, Lorenzo Maggi, Rebecca Panconesi, Fabio Staderini, Leonardo Bocchi, Cosimo Nardi, Nadia Navari, Adriano Peris, Matteo Risaliti, Mauricio F. Carvalho, Fabio Marra, Philipp Dutkowski, Gian Luca Grazi, Andrea Schlegel, Filippo Bigi, Mattia Dimitri, Andrea Corvi

“…<italic>Conclusion:</italic> This study showed the effectiveness of the developed machine. Future development of the system will include a more sophisticated control system to ensure the correct parameters for perfusion.…”
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AI/Machine Learning and Sol-Gel Derived Hybrid Materials: A Winning Coupling by Aurelio Bifulco, Giulio Malucelli

“…Indeed, further improvements are being observed thanks to the introduction of a very recent approach based on the use of artificial intelligence (AI) through the exploitation of a “machine learning (ML)” strategy: this way, it is possible to “teach” AI how to use literature data already available (and even incomplete) for material systems similar to the one being explored to predict key parameters of this latter, minimizing the error while maximizing the reliability. …”
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Characteristics of machining high hardness steels with face milling using carbide inserts and CBN by V.О. Zaloga

“…Research shows that the correct selection and optimization of machining parameters are the key to achieving the best results in face milling of high-hardness steels. …”
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Quantum machine learning regression optimisation for full-scale sewage sludge anaerobic digestion by Yomna Mohamed, Ahmed Elghadban, Hei I Lei, Amelie Andrea Shih, Po-Heng Lee

“…We, thus, propose a hybrid quantum-classical machine learning (Q-CML) regression algorithm using a quantum circuit learning (QCL) strategy. …”
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Exploring a cost-effective way for nutrient management with machine learning for container plants by Ping Yu, Kuan Qin

“…Due to the close relationships between plant canopy color values and growth parameters, an RGB imaging system using ImageJ to process the image analysis with a supervised machine learning approach was used to classify fertilization input status with four levels: extreme-underuse, sub-underuse, sufficient, and overuse. …”
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Deployment and Operation of Battery Swapping Stations for Electric Two-Wheelers Based on Machine Learning by Yu Feng, Xiaochun Lu

“…This study developed a data-driven optimization model based on machine learning algorithms using Beijing’s battery swapping stations and point of interest (POI) dataset. …”
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Modeling working processes of the marine thruster of the PMM-2M ferry-bridge machine by A. V. Mesropyan, E. A. Platonov, R. R. Rakhmatullin

“…The methods of 3D modeling of propellers in CAD and CAE packages are applied, which can determine and optimize the parameters of ongoing work processes with reliable accuracy. …”
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Data-driven analysis of hysteresis and stability in perovskite solar cells using machine learning by Sharun Parayil Shaji, Wolfgang Tress

“…Regarding stability, we are not able to obtain good performance from the machine learning model. Reasons are non-standardized measurements and lack of sufficient data.…”
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Evaluation of Privacy-Preserving Support Vector Machine (SVM) Learning Using Homomorphic Encryption by William J. Buchanan, Hisham Ali

“…The requirement for privacy-aware machine learning increases as we continue to use PII (personally identifiable information) within machine training. …”
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USING MACHINE LEARNING METHODS FOR PREDICTION OF DURABLE ECONOMIC DEVELOPMENT: ROMANIA CASE STUDY by Dumitrel-Victor TIȚA, Daniel NIJLOVEANU, Nicolae BOLD, Doru-Anastasiu POPESCU

“…The actors from within these economies must consider various parameters of the economy and tackle many different aspects regarding inputs, methodologies and economic strategies. …”
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Impact of Rice Husk Ash Properties on Concrete Strength: Experimental and Machine Learning Study by Yali Li, Huina Jia, Shikuan Li

“…Smaller rice husk ash particles lead to better performance in these strength tests. The ideal parameters identified were a calcination temperature of 650°C and a particle size of 5 µm. …”
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Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

“…The SVR algorithm is a machine learning algorithm that uses regression functions. …”
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Micro-Abrasive Air Jet Machining Technology for Fabrication of Helical Grooves on Bovine Bone by Jialin Li, Quanlai Li, Yafeng Deng, Weipeng Zhang, Haonan Yin

“…Analyses of the material removal mechanism and the effect of process parameters on the groove shapes were carried out. The results show that the helical grooves could be effectively machined using micro-abrasive air jets with a spring mask. …”
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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data by Manuel Ciba, Marc Petzold, Caroline L. Alves, Francisco A. Rodrigues, Yasuhiko Jimbo, Christiane Thielemann

“…This study presents a machine learning workflow to analyze drug-induced changes in neuronal biosensor data using complex network measures from graph theory. …”
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Machine learning model for predicting in-hospital cardiac mortality among atrial fibrillation patients by Huasheng Lv, Xuehua Bi, Shuai Shang, Meng Wei, Xianhui Zhou, Kai Wang, Baopeng Tang, Yanmei Lu

“…Abstract This study developed and validated a machine learning (ML) model to predict in-hospital cardiac mortality in 18,727 atrial fibrillation (AF) patients using electronic medical record data. …”
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