The Static Breaking Technique for Sustainable and Eco-Environmental Coal Mining by Hao Bing-yuan, Huang Hui, Feng Zi-jun, Wang Kai

“…In accordance with the actual geological situation of Yangquan No. 3 Mine, the basic parameters of manpower manipulated caving breaking with static crushing are settled, which reaps bumper industrial effects.…”
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MALWARE DETECTION CAPABILITIES FOR MOBILE DEVICES RUNNING ANDROID OS BY MONITORING HARDWARE RESOURCE CONSUMPTION by Andrew M. Bonch-Bruevich, Alyona A. Borisovskaya

“…Unlike traditional signature-based methods, monitoring parameters such as CPU usage, RAM utilization, network activity, and power consumption allows for the detection of sophisticated malicious mobile applications. …”
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Towards solving NLP tasks with optimal transport loss by Rishabh Bhardwaj, Tushar Vaidya, Soujanya Poria

“…Such functions play a vital role in machine learning algorithms as they steer the learning process. …”
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ATHEMATICAL MODEL FOR THE OPTIMISATION OF HIERARCHICAL MULTI-LEVEL PRODUCTION SYSTEMS by Yu. V. Minaeva

“…Operative parameters for processing machines according to a single optimisation criterion for the workshop were established. …”
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On numerical stability of continued fractions by V. Hladun, V. Кravtsiv, M. Dmytryshyn, R. Rusyn

“…It follows from the obtained conditions that the numerical stability of the algorithm depends not only on the rounding errors of the elements and errors of machine operations but also on the value sets and the element sets of the continued fraction. …”
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Modeling of Basic Processes of Labor Market Functioning and Development: Methodological and Practical Aspects by Zh. B. Kenzhin, Kh. U. Nursapina, Zh. Abzhanova, Zh. M. Bulakbay, T. K. Kuangaliyeva

“…Research methods: generalization, comparison, analysis and synthesis, induction and deduction, structural-logical analysis, monographic method, statistical modeling methods, machine learning methods, neural network modeling, fuzzy logic. …”
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Observation of a rare beta decay of the charmed baryon with a Graph Neural Network by The BESIII Collaboration

“…This work highlights a new approach to further understand fundamental interactions in the charmed baryon sector, and showcases the power of modern machine learning techniques in experimental high-energy physics.…”
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Anxiety Detection Using Consumer Heart Rate Sensors by Soraya Sinche, Jefferson Acán, Pablo Hidalgo

“…The classification performance was evaluated using decision trees, a support vector machine (SVM), and meta-classifiers to accurately distinguish between “stressed” and “non-stressed” states. …”
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The Whale Optimization Algorithm and Markov Chain Monte Carlo-Based Approach for Optimizing Teacher Professional Development in Creative Learning Design with Technology by Kalliopi Rigopouli, Dimitrios Kotsifakos, Yannis Psaromiligkos

“…A further Markov Chain Monte Carlo-based approach helped us in deciding with accuracy that these were the correct parameters of our training. In this article, we show that metaheuristic algorithms like the whale optimization algorithm, validated by a Markov chain technique like Markov Chain Monte Carlo, can help not only in areas like machine learning but also in fields without structured data, like creativity in technology-enhanced learning design. …”
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Exploring feature sparsity for out-of-distribution detection by Qichao Chen, Kuan Li, Zhiyuan Chen, Tomas Maul, Jianping Yin

“…One key drawback, however, is that the loss function parameters are highly dependent on involved datasets, which means it cannot be dynamically adapted and implemented in others settings; in other words, the general ability of the energy score is considerably limited. …”
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Multi-stage adaptive speed control with torque ripple optimization for a switched reluctance motor in electric vehicle applications by Youness Boumaalif, Hamid Ouadi, Fouad Giri

“…The speed controller is designed with the backstepping approach based on a SRM nonlinear model taking into account the magnetic saturation phenomenon of this machine. This ensures good control performance across a wide operating range. …”
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Determination of the tangential component of cutting resistance during frozen sedimentary rock cutting using blocked, deeply blocked and cell cutting methods by Stanislav A. Shemyakin, Evgenii A. Shishkin

“…For all three methods of cutting, under equal geometrical parameters of the cutting tool and the physical and mechanical properties of the frozen rock, the numerical value of the tangential component of cutting resistance is obtained. …”
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Wind Turbine Airfoil Noise Prediction Method Based on Generalized Airfoil Database and Residual Neural Network by Quan Wang, Haoran Zhang, Xiaodi Wang, Yang Ni

“…Finally, classical machine learning models were utilized to construct the airfoil noise prediction model. …”
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Performance analysis of deep neural networks for direction of arrival estimation of multiple sources by Min Chen, Xingpeng Mao, Xiuhong Wang

“…Abstract Recently, popular machine learning algorithms have successfully been applied to the direction of arrival (DOA) estimation. …”
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Implementation of Indoor 4G Signal Interference Detection using USRP B210 and RTL-SDR by Ciksadan Ciksadan, Feri Thabroni, Suroso Suroso

“…This approach proves effective for indoor signal monitoring and can be further developed to support automation using machine learning techniques.…”
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Water Quality Monitoring: A Water Quality Dataset from an On-Site Study in Macao by Jiawei Gao, Bochao Chen, Su-Kit Tang

“…The collected data were analyzed and validated using machine learning algorithms, including Isolation Forest, Random Forest, Logistic Regression, and Local Outlier Factor. …”
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Mechanical performance dataset for alloy with applications at low temperatures by Haoxuan Tang, Zhiyuan Chen, Xin Yao, Zhiping Xu

“…The product dataset encompasses key performance parameters such as yield strength, tensile strength, elongation at fracture, and Charpy impact energy. …”
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Modular Autonomous Virtualization System for Two-Dimensional Semiconductor Quantum Dot Arrays by Anantha S. Rao, Donovan Buterakos, Barnaby van Straaten, Valentin John, Cécile X. Yu, Stefan D. Oosterhout, Lucas Stehouwer, Giordano Scappucci, Menno Veldhorst, Francesco Borsoi, Justyna P. Zwolak

“…High-fidelity initialization, control, and readout of spin qubit registers require exquisite and targeted control over key Hamiltonian parameters that define the electrostatic environment. …”
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Consensus artificial intelligence-driven prognostic signature for predicting the prognosis of hepatocellular carcinoma: a multi-center and large-scale study by Wen Wen, Rui Wang

“…This study developed a consensus artificial intelligence-derived prognostic signature (CAIPS) by integrating ten machine learning algorithms (101 methods) across six multi-center HCC cohorts (n = 1110). …”
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Big data analysis on flow characteristics according to welded penetration locations for fire sprinkler piping system design by Joo Hyun Moon, Jae Heon Gu, Dong Kyu Kim, In Woo Jang

“…Over 2000 simulation cases were generated by varying key parameters, including inlet velocity, base and branch diameters, and penetration depths. …”
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