Simulation of Load–Sinkage Relationship and Parameter Inversion of Snow Based on Coupled Eulerian–Lagrangian Method by Ming Zhu, Pengyu Li, Dongqing Li, Wei Wei, Jianfeng Liu, Xixing Long, Qingkai Meng, Yongjie Shu, Qingdong Yan

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Basic Aspects Design of Machine-Tool Adaptations by Erokhin V.V.

“…In article the technique of design of the machine-tool accessories with the set parameters of quality and reliability is stated the main. …”
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Soil liquefaction assessment using machine learning by Gamze Maden Muftuoglu, Kaveh Dehghanian

“…In this study, the relationship between liquefaction potential and soil parameters is determined by applying feature importance methods to Random Forest (RF), Logistic Regression (LR), Multilayer Perceptron (MLP), Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) algorithms. …”
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Computer simulation of the indices of the acoustic assessment of machines by D. PLEBAN

“…The worked out indices are functions of several parameters such as e.g. variations of the operational conditions of the machine, or the acoustic properties of the room. …”
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Management of capital renewal at machine-building enterprises by N.A. Yefimenko

“…The model of structure formation in a rich creative process has been proposed for the upstream and downstream directions in order to introduce control over the totality of parameters for the renewal of capital in the machine industry. …”
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Experimental modelling and research on vibroacoustic phenomena in machines by D. Pleban

“…New indices - the energy transmission index and the energy radiation index, have been proposed for application in the quantitative analysis of energetic phenomena occurring in machines. Determining these indices calls for the measurement of specific vibro-acoustic parameters of machines, acoustic pressure levels and the vibration acceleration levels or vibration velocities of the surfaces of selected machine elements. …”
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Advances in Corneal Diagnostics Using Machine Learning by Noor T. Al-Sharify, Salman Yussof, Nebras H. Ghaeb, Zainab T. Al-Sharify, Husam Yahya Naser, Sura M. Ahmed, Ong Hang See, Leong Yeng Weng

“…This paper also examines the use of machine learning models, specifically Decision Tree and Nearest Neighbor Analysis, which enhance the accuracy of diagnosing based on topographical corneal parameters from corneal topography. …”
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Fuzzy control system of multioperational machine status by Andrey K. Tugengold, Andrey I. Izyumov, Roman N. Voloshin, Mikhail Y. Solomykin

“…The results obtained can be applied in the parts production where accuracy is one of the key parameters. Automated control systems for the machine condition allow reducing costs due to equipment downtime, and monitoring the tool status can reduce the rejection rate. …”
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Experimental Investigations on Leakages in Positive Displacement Machines by Hitesh H. Patel, Vikas J. Lakhera

“…The clearance gaps in positive displacement machines such as compressors, pumps, expanders, and turbines are critical for their performance and reliability. …”
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Flax Harvesting Technologies for Flax Harvesting Machines by V. G. Chernikov, R. A. Rostovtsev, V. Yu. Romanenko

“…(Research purpose) To establish patterns and the degree of correlation between the qualitative operation indicators (pulling and deseeding quality, flax line stretching); design parameters; machine dynamic properties and harvesting conditions (height and density of flax stem, field surface, thickness and unevenness of flax straw, etc.). …”
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Design and Modellingof a Pneumatic Vice Machine by Talemwa, Prosper

“…The methods included library searches, field surveys, internet searches, and interviews. Reviewing design parameters of different scholars to come up with the conceptual design and developing the layout by use of SOLID WORKS. …”
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The permissible concentration of abrasive particles in the machine oil by Madaminov S.M., Irgashev B.A., Boltoev A.Sh.

“…The wear rate of a gear wheel tooth is assessed taking the dust level and the size of abrasive fractions; the geometrical, kinematic, and dynamic parameters that are characteristic of toothed gears; and the mechanical properties of gear wheel materials into account. …”
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OPTIMISATION OF THE MACHINING PROCESS USING GENETIC ALGORITHM by Nadežda ČUBOŇOVÁ, Tomáš DODOK, Zuzana SÁGOVÁ

“…Genetic algorithms can be used for improvement of these operations and considerably reduce length of tool paths leading to the reduction of machine times and optimisation of cutting parameters. …”
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Geomagnetic Survey Interpolation with the Machine Learning Approach by Aleshin Igor, Kholodkov Kirill I., Malygin Ivan, Shevchuk Roman, Sidorov Roman

“…The interpolation relies on the very basic nearest neighbourss algorithm, although augmented with a Machine Learning approach. Such an approach enables the error of less than 5 percent by intelligently adjusting the nearest neighbours algorithm parameters. …”
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Spin-chain based quantum thermal machines by Edoardo Maria Centamori, Michele Campisi, Vittorio Giovannetti

“…We study the performance of quantum thermal machines in which the working fluid of the model is represented by a many-body quantum system that is periodically connected with external baths via local couplings. …”
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Quality and Machine Translation: A realistic objective? by Rebecca Fiederer Sharon O'Brien

“…Eleven suitably qualified raters rated 30 source sentences, three translated versions and three post-edited versions for the parameters clarity, accuracy and style. The results show that the machine translated, post-edited output was judged to be of higher clarity and accuracy, while the translations were judged to be of better style. …”
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DESIGN OF PART MACHINING WITH BALL-AND-ROD REINFORCER by Regina Zamirovna Yagudina, Mikhail Bensionovich Flek

“…Dependences to calculate the altitude parameters of the machined surface roughness, the work-hardened layer depth, and the inelastic deformation ratio are offered for various machining conditions and process material specifications. …”
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CONDITIONS OF REDUCED COST FOR MACHINE-BUILDING PRODUCTS by Dmytro NOVIKOV, Yury GUTSALENKO, Feodor NOVIKOV

“…It is shown that the optimal durability of the cutting tool which determines the minimum cost of processing depends only on the economic parameters. This indicates the need to solve technological problems associated with the mechanical treatment of machine parts through the use of economic methods. …”
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On the sample complexity of quantum Boltzmann machine learning by Luuk Coopmans, Marcello Benedetti

“…Abstract Quantum Boltzmann machines (QBMs) are machine-learning models for both classical and quantum data. …”
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Machine learning for reparameterization of multi-scale closures by Hilary Egan, Meagan Crowley, Hariswaran Sitaraman, Lila Branchaw, Peter Ciesielski

“…Here, rather than learning an entire closure operator, we adopt an existing reduced-dimension model of the microphysics and learn an optimal re-parameterization of the solver. We demonstrate two approaches for training the reduced dimension closure model (1) an a priori method that optimizes the closure parameterization and the neural network parameters separately and (2) an a posteriori method that simultaneously optimizes both. …”
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