Five axis Virtual Machining of Asymmetric Double Cone Expansion Wheel by ZHAO Yan-ling, QIN Sheng, YAN Zhao

“…Aiming at the problem that the size of the unfolding wheel with asymmetrical double cone is small, the structure of working surface is special, and the accuracy in actual processing is difficult to guarantee, and the accurate technical parameters are difficult to obtain, the fiveaxis virtual machining technology is used to simulate the unfolding wheel. …”
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Dispersion Analysis of Rounds Fired from a Glauberyt Machine Pistol by Zbigniew DZIOPA, Krzysztof ZDEB

“…The videos recorded were used to determine the initial kinematic parameters of the bullet trajectory.…”
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Probabilistic Evaluation of Hydraulic Fracture Performance Using Ensemble Machine Learning by Xiaoping Xu, Xianlin Ma, Jie Zhan

“…We present a probabilistic evaluation approach that integrates ensemble machine learning with Monte Carlo simulation. In the method, we employ the ensemble learning to develop a predictive model between well productivity and its influential factors including both geological properties and HF treatment parameters. …”
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Study on Application of Grey Prediction Model in Superalloy MAR-247 Machining by Chen Shao-Hsien

“…Moreover, with the superalloy machining parameters of the current effective application improved grey prediction model, it can decrease the errors, extend the tool life, and improve the prediction precision of surface accuracy.…”
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Scientific objectives of research on road machines life cycle in modern conditions by S. A. Evtiukov, S. V. Repin, S. M. Grushetskii, G. A. Kаrro

“…Today, the ERA-GLONASS system and similar systems are actively used in all areas of the road economy and allow tracking the position and other technical parameters of road machines over a long period of time. …”
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Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts by Marcin Gołaszewski, Marcin Królikowski, Bartosz Powałka

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A Review of Machine Learning Applications in Ocean Color Remote Sensing by Zhenhua Zhang, Peng Chen, Siqi Zhang, Haiqing Huang, Yuliang Pan, Delu Pan

“…Ocean color remote sensing technology has proven to be an indispensable tool for monitoring ocean conditions, as it has consistently provided critical data on global ocean optical properties, color, and biogeochemical parameters over several decades. With the rapid advancement of artificial intelligence, the integration of machine learning (ML) models into ocean color remote sensing has become a significant focus within the scientific community. …”
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Curvature-Based Machine Vision Method for Measuring the Dimension of Ball Screws by Yijia Chen, Yao Yao, Hao Yang, Yue Wu, Kunpeng Zhang, Xiaoming Pan

“…However, most of the current approaches are ineligible for rapid ball screw in-situ inspections due to the installation condition requirement of the production line. In this research, a machine vision method is presented to achieve highly accurate measurements of crucial parameters (the center distance and raceway arcs) in ball screws using a curvature edge detection algorithm. …”
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A Review of Simulations and Machine Learning Approaches for Flow Separation Analysis by Xueru Hao, Xiaodong He, Zhan Zhang, Juan Li

“…It highlights recent advancements in simulation and machine learning (ML) methods, which utilize flow field databases and data assimilation techniques. …”
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Application of Artificial Neural Networks in Predicting Surface Quality and Machining Time by Andrei Raul Osan, Raul Florentin Drenţa

“…This paper explores the use of artificial neural networks to optimize metal machining processes. It has two main components. The first component focuses on developing a neural network in EasyNN to predict quality errors of metal surfaces machined with toroidal milling. …”
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Nonlinear Dynamics and Machine Learning for Robotic Control Systems in IoT Applications by Vesna Antoska Knights, Olivera Petrovska, Jasenka Gajdoš Kljusurić

“…The machine learning models, including neural networks, are trained using historical data and real-time sensor inputs to dynamically adjust the control parameters. …”
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Translation in the Age of Artificial Intelligence: Machine Translation Markers in Journalistic Texts by Kim Lidiya, Deryabin Artem

“…The authors investigated machine-translated journalistic texts to reveal the potential of popular machine translation programs and markers of machine translation in political discourse. …”
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Power sequence definition under woodworking milling on contour-milling machines by Alexander N. Chukarin, Sergey V. Golosnoy

“…This study is devoted to determining parameters of the power sequence arising under the circular moulding. …”
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Study on the Magnitude of Reservoir-Triggered Earthquake Based on Support Vector Machines by Hai Wei, Mingming Wang, Bingyue Song, Xin Wang, Danlei Chen

“…An effective approach is introduced to predict the magnitude of reservoir-triggered earthquake (RTE), based on support vector machines (SVM) and fuzzy support vector machines (FSVM) methods. …”
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Using adaptability principles in developing chassis for transport and road construction machines by Dobretsov Roman, Shen Yunfeng, Karnaukhov Andrey, Malyukova Margarita, Sabitov Linar, Kiyamov Ilgam, Taraban Maria

“…The article considers the approach to determining the structure of a high-cross-country chassis and the principles of calculating its main weight, size and energy parameters. The relevance of the problem is determined by the lack of Russian developments in the field of creating chassis for road construction machines suitable for work in difficult terrain. …”
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A systematic mapping study on machine learning methodologies for requirements management by Chi Xu, Yuanbang Li, Bangchao Wang, Shi Dong

“…Abstract Requirements management (RM) plays an important role in requirements engineering. The development of machine learning (ML) is in full swing, and many ML software management techniques had been used to improve the performance of RM methods. …”
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Recent advances in structural health diagnosis: a machine learning perspective by Yuequan Bao, Huabin Sun, Yang Xu, Xiaoshu Guan, Qiuyue Pan, Dawei Liu

“…This article provides a brief review of the developments in machine learning-based structural health diagnosis, including data cleaning, structural modal parameters estimation, structural damage identification, digital twin technology, and structural reliability assessment. …”
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Distribution Characteristics of Machining Error in Turning Large Pitch External Thread by ZHANG Wei, ZHENG Min-li, JIANG Bin, LI Zhe, DING Yan

“…Therefore, according to the analysis results of geometric structure parameters and machining errors of the thread surface, two turning threads tests were carried out. …”
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Performance Evaluation of Machine Learning Algorithms for Detecting Gas Leakage System by Kondireddy Muni Sankar, Dr. B. Booba

“…Thus present research work focuses on evaluating intelligent models' efficacy in identifying minor leaks in gas pipelines with fundamental operational parameters. The research then proceeds to compare these models using established performance metrics. …”
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Using machine learning as a surrogate model for agent-based simulations. by Claudio Angione, Eric Silverman, Elisabeth Yaneske

“…In this proof-of-concept work, we evaluate the performance of multiple machine-learning methods as surrogate models for use in the analysis of agent-based models (ABMs). …”
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