Study of the Atomization Performance of Swirl Nozzle for Snow-making Machine by Wu Haifeng, Liu Jiawei, Wang Ruixiang, Zhang Bowen, Xu rongji, Yan gang, Dong peiwen, Zhang hongjun

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Machine learning modeling for thermochemical biohydrogen production from biomass by Yingju Chang, Wei Wang, Jo-Shu Chang, Duu-Jong Lee

“…This paper outlines the steps for applying machine learning (ML) models to predict biohydrogen yields from biomass using thermochemical treatments. …”
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Rational redistribution of waste of resources. Manufacturing of equipment for cutting machine by Yu. E. Soloviev, I. A. Kovaleva

“…The staff of the Central laboratory LFMI proposed to use waste knives drop-hummer shop for the manufacture of knives for the chopping of the machine SIMA GEL-30. On the basis of the conducted researches the technological scheme was developed for production of knives for the chopping of the machine SIMA GEL-30 cold cutting of reinforcing bar mill 320 the rolling shop № 1.…”
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Constructing multicomponent cluster expansions with machine-learning and chemical embedding by Yann L. Müller, Anirudh Raju Natarajan

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Traffic modeling for machine type communication and its overload control by Xin JIAN, Xiao-ping ZENG, Yun-jian JIA, Jun-yi YANG, Yuan HE

“…Machine type communications (MTC),defined as machine to machine communication over cellular mobile network,is an integral part of future ubiquitous network and has broad application prospects and market potentials.To carry out the performance analysis of network in context of MTC applications,a Beta/M/1 queue model was proposed for modeling the network with MTC applications and its full performance analysis wer iven out by deducing the analytical expression of Beta distribution’s moment generation function,in which the shape parameters of Beta distribut are as-sumed to be integer.In addition,to handle the congestion caused by mass concurrent data and signaling transmission from many MTC devices,three overload control measures were also presented,that is:1) inter-class grouping techniques; 2) re-shaping the inter-arrival time distribution of MTC devices; 3) segment-wise uniform back-off scheme.The Beta/M/1 mod-el and segment-wise uniform back-off scheme proposed here can be used as a preliminary model for different MTC ap-plication scenarios and serve as a fundamental traffic model and overload control method for future ubiquitous network.…”
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Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

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An Overview and Classification of Machine Learning Approaches for Radar Signal Deinterleaving by Louis Lesieur, Jean-Marc Le Caillec, Ali Khenchaf, Vincent Guardia, Abdelmalek Toumi

“…As radar signals are more complex and observations are denser, new Machine Learning (ML) approaches appear in the literature to enhance traditional Radar Signal Deinterleaving (RSD). …”
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Theoretical studies of hydromechanical drive of mobile technological machine member by Alexander Timofeyevich Rybak, Alan Ruslanovich Temirkanov, Vladislav Maximovich Peshkov, Evgeny Sergeyevich Shamaylov

“…The research results can be used in design and improvement of the synchronous hydromechanical drives of mobile technological machines.…”
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Powder Bed Fusion via Machine Learning-Enabled Approaches by Utkarsh Chadha, Senthil Kumaran Selvaraj, Abel Saji Abraham, Mayank Khanna, Anirudh Mishra, Isha Sachdeva, Swati Kashyap, S. Jithin Dev, R. Srii Swatish, Ayushma Joshi, Simar Kaur Anand, Addisalem Adefris, R. Lokesh Kumar, Jayakumar Kaliappan, S. Dhanalakshmi

“…For PBF to reach its maximum potential, machine learning (ML) algorithms are used with suitable materials to achieve goals cost-effectively. …”
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Additive manufacturing and topology optimization of magnetic materials for electrical machines by A. R. Safin, Ranjan Kumar Behera

“…The need to establish a relationship between the properties of the starting material, the diameters of the extrusion nozzles, the printing parameters, as well as the mechanical and functional properties of the resulting magnets is indicated. …”
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DASH Framework Using Machine Learning Techniques and Security Controls by Aref Shaheed, Haisam Al-radwan

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Large-scale moral machine experiment on large language models. by Muhammad Shahrul Zaim Bin Ahmad, Kazuhiro Takemoto

“…While our previous study examined four prominent LLMs using the Moral Machine experimental framework, the dynamic landscape of LLM development demands a more comprehensive analysis. …”
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Impact of Technological System’s Characteristics on the Machining Accuracy of Bearing Rings by Halchuk T. N., Povstyanoy O. Yu., Bembenek M., Redko R. G., Chetverzhuk T. I., Polinkevych R. M.

“…It was proven that the quality of products is formed under the influence of the use of modern computer technologies at all stages of manufacturing and control of parts, which ensures research in a wide range of changes in technological parameters and comparison of individual studies with actual machining conditions on the machine, with the results of a sufficient level of reliability.…”
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$$\alpha$$ -decay half-life predictions with support vector machine by Amir Jalili, Feng Pan, Jerry P. Draayer, Ai-Xi Chen, Zhongzhou Ren

“…Abstract In this study, we investigate the application of support vector machines utilizing a radial basis function kernel for predicting nuclear $$\alpha$$ -decay half-lives. …”
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Design of a Rice Rope Laying Machine for Direct Sowing by Xiao-Lian LV, Xiao-Rong LV, Rong-Chao MA

“…The RRLM has been developed based on an in-depth analysis of the design principles and main structure parameters of rice direct seeding machines. The completed machine consists of all necessary components including an anti-blocking device, sowing device, opening device, banking device, compacting device, etc. …”
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Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…Our research addresses this critical imperative by introducing an innovative predictive model that refines crop recommendation systems through advanced machine learning techniques, specifically random forest and SHapley Additive exPlanations (SHAP). …”
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Formation of Machine Learning Features Based on the Construction of Tropical Functions by Sergey N. Chukanov, Ilya S. Chukanov

“…To increase the variety of parameters (machine learning features), filtering of object scanning by rows from left to right and scanning by columns from bottom to top are built. …”
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Application of Machine Learning for Target Selection and Acid Treatment Design by I. I. Mannanov, M. A. Varfolomeev, G. R. Ganieva, A. R. Gimaeva, R. R. Giniyatullin

“…Current approaches to acid treatment design rely on advanced software tools that evaluate major acidizing factors. Machine learning is a valuable complement to the existing techniques: it facilitates the selection of target wells and aids in defining initial parameters for design engineering on reliable and effective software platforms. …”
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Integrated Machine Learning Models for Bakery Product Defect Prediction by Nataliia Zaiets, Nataliia Lutska, Lidiia Vlasenko

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Enhancing Irrigation Efficiency Through the Selection of Sprinkler Machine Design by R. N. Zadorozhniy, I. V. Romanov

“…(Research purpose) Improving irrigation efficiency by selecting the optimal parameters of sprinklers based on local conditions. …”
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