Investigating Tensile Strength in SLA 3D Printing Enhancement Through Experimentation and Finite Element Analysis by Siwasit Pitjamit, Norrapon Vichiansan, Parida Jewpanya, Pinit Nuangpirom, Pakpoom Jaichomphu, Komgrit Leksakul, Pattarawadee Poolperm

“…Experimental testing, conducted using an Instron 5566 machine, reveals that a print orientation of 22.5 degrees and side orientations yield the highest tensile strength, reaching 72.01 MPa. …”
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Production of externally gear parts with a new multi-level forming tool based on rotary ballizing technology using Numerical and experimental study by Hammad Elmetwally, Emad Fahmy, Eman S. M. Abd-Elhalim, Ahmed M.I. Abu-Oqail, Mohamed El-Sheikh, Ayman Abd-Eltwab

“…Examples include transportation equipment, aerospace equipment, and machine tools such as lathes and milling machines, all of which rely on gearboxes. …”
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Learning models for predicting pavement friction based on non-contact texture measurements: Comparative assessment by Xiuquan Lin, You Zhan, Zilong Nie, Joshua Qiang Li, Xinyu Zhu, Allen A. Zhang

“…In this research, traditional multiple linear regression and four machine learning methods, support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and convolutional neural network (CNN), are utilized to evaluate and predict pavement frictional performance. …”
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Non-destructive textural quality assessment of peaches and nectarines using near-infrared spectroscopy integration time by Eva Cristina Correa, Paola Baltazar, Pilar Barreiro, Natalia Hernández-Sánchez, Lourdes Lleó, Ángela Melado-Herreros, Belén Diezma

“…These findings indicate that integration time, combined with machine learning, is a feasible, efficient method for non-destructive ripeness classification. …”
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Experimental investigation of the effect of intermittent operation on membranes in wind-powered SWRO plants, focusing on frequent start-stop scenarios by José A. Carta, Pedro Cabrera, Noemi Melián-Martel, Sigrid Arenas-Urrea

“…The evolution of various parameters was analyzed using machine learning techniques, hypothesis testing, and effect size analysis. …”
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Elements of artificial intelligence in a predictive personalized model of pharmacotherapy choice in patients with heart failure with mildly reduced ejection fraction of ischemic or... by O. A. Osipova, A. V. Kontsevaya, V. V. Demko, E. V. Gosteva, A. A. Komisov, А. A. Kuzub, A. V. Serdyukova, A. S. Brizhaneva, R. N. Shepel, O. M. Drapkina

“…The result of this function is a parameter vector: AL, TNF-α, MMP-9, SI and quality of life (QOL). …”
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Dynamic mapping of dissolved oxygen in freshwater aquaculture ponds using UAV multispectral imagery by Xingyu Liu, Yancang Wang, Xiaohe Gu, Mengjie Li, Wenxu Lv, Xuqing Li, Ruiyin Tang, Guangxin Chen, Baoyuan Zhang, Shuaifei Liu, Fajian Zong, Yongkun Ji, Xiaolong Yu, Tianen Chen

“…However, since DO is a non-photosensitive parameter, it is difficult to directly inverse using UAV imaging technology. …”
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Retrospective analysis of COVID-19 clinical and laboratory data: Constructing a multivariable model across different comorbidities by Mahdieh Shokrollahi Barough, Mohammad Darzi, Masoud Yunesian, Danesh Amini Panah, Yekta Ghane, Sam Mottahedan, Sohrab Sakinehpour, Tahereh Kowsarirad, Zahra Hosseini-Farjam, Mohammad Reza Amirzargar, Samaneh Dehghani, Fahimeh Shahriyary, Mohammad Mahdi Kabiri, Marzieh Nojomi, Neda Saraygord-Afshari, Seyedeh Ghazal Mostofi, Zeynab Yassin, Nazanin Mojtabavi

“…Identifying clinical symptoms and laboratory parameters as key predictors can guide prognosis and inform effective treatment strategies. …”
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Cálculo de la capacidad de trabajo y parámetros de funcionamiento de los cojinetes de deslizamiento, actualidad del tema. // Calculation of work capacity and operation parameters o... by A. García Toll, O. Yera Pérez

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Impact of the Technical Means and Technologies on Mechanical Soil Erosion on Slopes by S. G. Mudarisov, Z. Sh. Rakhimov

“…The article presents the influence of used tillage machines and technologies of agricultural crops cultivation on mechanical soil erosion on slope agricultural landscapes. …”
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APPLICATION OF POLYSTYRENE FOAM CORE FUSIBLE PATTERNS IN PRODUCTION OF GAS TURBINES’ CAST PARTS by O. I. Shinsky, I. I. Maksіuta, Yu. G. Kvasnitskaya, E. V. Mikhnyan, A. V. Neima

“…The absence of surface defects of castings, reduction of roughness, increased their accuracy class in comparison to accepted technological regulations of the process of production, which reduced the cost of machined parts and increased utilization of expensive heat-resistant alloys were produced.…”
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Automatic Generation Control of Multi-Area Power System Using a Fuzzy Wavelet Neural Network Load Frequency Controller Combined With Shuffled Frog Leaping Algorithm by Leila Esteki, Abas Ali Zamani, Seyed Mohamad Kargar, SayedAli Mousavi

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Physics-Informed Neural Network-Based Inverse Framework for Time-Fractional Differential Equations for Rheology by Sukirt Thakur, Harsa Mitra, Arezoo M. Ardekani

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Formulation of low temperature mixed mode crack propagation behavior of crumb rubber modified HMA using artificial intelligence by Sepehr Ghafari, Mehrdad Ehsani, Sajad Ranjbar, Mohammad Nabi Nazari, Fereidoon Moghadas Nejad

“…Two dataset configurations were used: dataset 1 contains all entries, while dataset 2 excludes Gb0, Gf0, and Gi0 (mode I). Five machine learning techniques, Regression, Multi-Gene Genetic Programming (MGGP), Support Vector Regression (SVR), Random Forest, and Artificial Neural Networks were employed to predict three key fracture parameters. …”
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Prediction and optimization of robot processing technology based on neural network and genetic algorithm by Fusen WU

“…This model can clearly reveal the role of various grinding process parameters in machining and reflect their importance in improving machining efficiency and material removal rate. …”
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ELECTROHYDROCYLINDER OF INCREASED EFFICIENCY: PROSPECTS FOR THE DEVELOPMENT OF MECHATRONIC SYSTEMS by A. E. Karamguzhinova, V. N. Kuznetsova, V. V. Savinkin, D. A. Koptyaev

“…The proposed combined tracking system with the specified parameters allows for the efficient operation of the drive of many machines.Materials and methods. …”
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Critical statistical assessment of data in metal additive manufacturing by Raymond Wong, Anh Tran, Bogdan Dovgyy, Claudia Santos Maldonado, Minh-Son Pham

“…Obtaining high quality data reflecting the relationships between the additive manufacturing (AM) process parameters, material microstructure and mechanical properties is crucial for the use of machine learning in AM. …”
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Flood Image Classification using Convolutional Neural Networks by Olusogo Julius Adetunji, Ibrahim Adepoju Adeyanju, Adebimpe Omolayo Esan, Adedayo Aladejobi Sobowale Sobowale

“…This study develops a novel model using convolutional neural networks (CNN) for the prediction of floods. Important parameters such as standard deviation and variance were incorporated in the parameters tuned CNN model that performed flood images feature extraction and classification for better predictive performance. …”
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Microstructure and Properties of Mooring Chain Steel Prepared by Selective Laser Melting by Xiaojie Cui, Xiaoxin Li, Changqing Hu, Dingguo Zhao, Yan Liu, Shuhuan Wang

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Subtle changes on electrocardiogram in severe patients with COVID-19 may be predictors of treatment outcome by Illya Chaikovsky, Illya Chaikovsky, Dmytro Dziuba, Olga Kryvova, Katerina Marushko, Julia Vakulenko, Kyrylo Malakhov, Оleg Loskutov, Оleg Loskutov

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