Material Identification During Turning by Neural Network by Berend DENKENA, Benjamin BERGMANN, Miriam HANDRUP, Matthias WITT

“…Thus, it is mandatory to classify the material during machining for the relevant range of process parameters. …”
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A Comparative Investigation on Powder Mixed EDM Machining of Steel Alloys with Multi-Objective Optimization Using Fuzzy-TOPSIS Method by Md Nadeem Alam, Mohd Atif Wahid, Raghib Ahsan, Naveen Kumar, Shoaib Sabri

“… The current work offers a comparative study that examined the effects of various process parameters, such as dielectric fluid, current (IP), pulse on time (TON), and different conductive powder particles mixed dielectric fluids, on electrical discharge machining (EDM) of AISI 1040, EN31, and HCHCr steels, respectively. …”
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Blood Glucose Concentration Prediction Based on Double Decomposition and Deep Extreme Learning Machine Optimized by Nonlinear Marine Predator Algorithm by Yang Shen, Deyi Li, Wenbo Wang, Xu Dong

“…Then, the NMPA algorithm is utilized to optimize the weight parameters of the DELM network to avoid any fluctuations in prediction performance, and all the decomposed subsequences are predicted separately. …”
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Interpretable machine learning excavates a low-alloyed magnesium alloy with strength-ductility synergy based on data augmentation and reconstruction by Qinghang Wang, Xu Qin, Shouxin Xia, Li Wang, Weiqi Wang, Weiying Huang, Yan Song, Weineng Tang, Daolun Chen

“…The application of machine learning in alloy design is increasingly widespread, yet traditional models still face challenges when dealing with limited datasets and complex nonlinear relationships. …”
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Supervised and unsupervised machine learning approaches for prediction and geographical discrimination of Iranian saffron ecotypes based on flower-related and phytochemical attribu... by Seid Mohammad Alavi-Siney, Jalal Saba, Alireza Fotuhi Siahpirani, Jaber Nasiri

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Lokomat-Assisted Robotic Rehabilitation in Spinal Cord Injury: A Biomechanical and Machine Learning Evaluation of Functional Symmetry and Predictive Factors by Alexandru Bogdan Ilies, Cornel Cheregi, Hassan Hassan Thowayeb, Jan Reinald Wendt, Maur Sebastian Horgos, Liviu Lazar

“…However, the objective evaluation of treatment effectiveness through biomechanical parameters and machine learning approaches remains underexplored. …”
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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S Jatti, Nitin K Khedkar, Rahul B. Dhabale, Ashwini V Jatti

“…This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to effectively do the classification, detection, and many other tasks. …”
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Comparative study of machine learning methods for mapping forest fire areas using Sentinel-1B and 2A imagery by Xinbao Chen, Xinbao Chen, Yaohui Zhang, Shan Wang, Zecheng Zhao, Chang Liu, Junjun Wen

“…To investigate the adaptability of machine learning methods in various scenarios for mapping forest fire areas, this study presents a comparative study on the recognition and mapping accuracy of three machine learning algorithms, namely, Support Vector Machine (SVM), Random Forest (RF), and Neural Network (NN), based on Sentinel-1B and 2A imagery. …”
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Predicting urban landslides in the hilly regions of Bangladesh leveraging a hybrid machine learning model and CMIP6 climate projections by Md․ Ashraful Islam, Musabbir Ahmed Arrafi, Mehedi Hasan Peas, Tanvir Hossain, Md Mehedi Hasan, Sanzida Murshed, Monira Jahan Tania

“…The model was trained using diverse geospatial parameters including topographical, hydrological, soil, and geological parameters, along with an updated landslide inventory, enabling spatially explicit predictions of landslide susceptibility. …”
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Rock and machine interaction law during TBM crossing fault and prevention and control technology of jamming disaster in Shoushan No.1 Mine by Jianguo ZHANG, Tongtong MU, Yiqiang LU, Jiawei LIU, Zhanbiao YANG, Sheng ZHANG, Longfei WANG

“…In order to solve this problem, based on the rock-machine interaction data of the fault fracture zone excavated by TBM in Shoushan No.1 coal mine roadway, screening of large amounts of data for effective excavation-cycles, identification and division of each stage of the normal excavation-cycle, combined with the surrounding rock classification method of TBM rock-machine data fusion, the main excavation parameters changes and roadway damage phenomena of TBM before and during excavation in the fault are analyzed. …”
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Investigation of applicability of Peng–Robinson and GERG-2008 equations of state of real gas for calculating properties of Freons for refrigeration machines and compressors by M. I. Sokolov, Yu. V. Kozhukhov

“…A study of real gas state equations Peng–Robinson and GERG-2008 with respect to calculation of Freons R404A, R408A and R410A has been carried out. Four Freon parameters are calculated during the study: saturated vapor pressure at the saturation line at some Freon temperature, Freon density at saturation pressure and some temperature, enthalpy and entropy at the same pressures and temperature. …”
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Computer Vision Algorithm for the detection of fracture cracks in Oil Hardening Non-Shrinking (OHNS) die steel after machining process by Akshansh Mishra, Vijaykumar S. Jatti, Nitin K. Khedkar, Rahul B. Dhabale, Ashwini V. Jatti

“…This type of neural network receives input from an image and extracts features from the image while also providing learnable parameters to effectively do the classification, detection, and many other tasks. …”
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Production of metal cord construction size 7 x 7 x 0,22 on root machines type RIR –15 by O. M. Matveev, V. V. Shapovalov, I. V. Muzychenko, O. A. Starkina

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Modeling of working processes in the throttle-adjustable hydraulic drive of manipulation systems with separate movement of links during operation of mobile machines by Alexander V. Lagerev, Igor A. Lagerev

“…The adequacy of simulation results and real physical phenomena observed during the operation of mobile machines is shown.…”
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Exergy and energy-based sustainability evaluation of diesel-biodiesel-ethanol blends with emission forecasting using advanced machine learning models by Harish Venu, V. Dhana Raju, Jayashri N. Nair, Sameer Algburi, Ali E. Anqi, Ali A. Rajhi, Mohammed Kareemullah

“…The increasing influence of machine learning in engine emission prediction is on rising trend. …”
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Machine learning model interpretability using SHAP values: Applied to the task of classifying and predicting the nutritional content of different cuts of mutton by Li Wang, Xuchun Sun, Jing Liang, Zhiyuan Ma, Fei Li, Shengyan Hao, Baocang Liu, Long Guo, Xiuxiu Weng

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Machine Learning Models Derived from [¹⁸F]FDG PET/CT for the Prediction of Recurrence in Patients with Thymomas by Angelo Castello, Luigi Manco, Margherita Cattaneo, Riccardo Orlandi, Lorenzo Rosso, Giorgio Alberto Croci, Luigia Florimonte, Giovanni Scribano, Alessandro Turra, Stefano Ferrero, Mario Nosotti, Gianpaolo Carrafiello, Massimo Castellani, Paolo Mendogni

“…Additionally, three metabolic PET parameters were selected and included in the PET Model. …”
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Classification Of Rice Plant Diseases Based on Leaf Images Using the Multi Class Support Vector Machine (M-SVM) Method by Febiana Angela tanesab, Rangga Pahlevi Putra, Aviv Yuniar Rahman

“…Each variation of features and data division was evaluated by calculating the model performance parameters. The features used for classification include color (RGB) and texture (GLCM) from leaf images. …”
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Towards Machine Learning-Driven Catalyst Design and Optimization of Operating Conditions for the Production of Jet Fuel Via Fischer-Tropsch Synthesis by Parisa Shafiee, Bogdan Dorneanu, Harvey Arellano-Garcia

“…This study introduces the application of a machine learning (ML) framework to guide the design of Co/Fe-supported FTS catalysts and operating conditions for enhanced fuel selectivity. …”
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Modeling of working processes in the throttle-adjustable hydraulic drive of manipulation systems with conjoint movement of links during operation of mobile machines by Lagerev A.V., Lagerev I.A.

“…The article proposes a functional-structural scheme and a mathematical model of working hydrodynamic processes in a throttle-adjustable hydraulic drive of handling systems (cranes-manipulators) of mobile transport-technological machines during the conjoint movement of two links. …”
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