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Enhancing Manufacturing Precision: Leveraging Motor Currents Data of Computer Numerical Control Machines for Geometrical Accuracy Prediction Through Machine Learning.
Sensors (Basel)
December 2024
Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.
Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.
View Article and Find Full Text PDFA Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities.
Sensors (Basel)
December 2024
2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece.
The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.
View Article and Find Full Text PDFFirst report of the whole‑genome sequence analysis of Fig badnavirus 2 from China.
Virus Genes
January 2025
College of Agronomy, Key Laboratory of Prevention and Control of Invasive Alien Species in Agriculture & Forestry of the North-Western Desert Oasis, Ministry of Agriculture and Rural Affairs, Xinjiang Agricultural University, Urumqi, 830052, China.
A novel plant virus was identified in fig trees exhibiting ring spot symptoms through high-throughput sequencing (HTS). The complete genome sequence was successfully determined using PCR and RT-PCR techniques. The virus features a circular DNA genome of 7233 nucleotides (nt) in length, encompassing four open reading frames (ORFs).
View Article and Find Full Text PDFOptimising Venturi flume oxygen transfer efficiency using uncertainty-aware decision trees.
Water Sci Technol
December 2024
Department of Civil Engineering, National Institute of Technology Kurukshetra, Haryana 136119, India.
This study optimizes standard oxygen transfer efficiency (SOTE) in Venturi flumes investigating the impact of key parameters such as discharge per unit width (), throat width (), throat length (), upstream entrance width (), and gauge readings ( and ). To achieve this, a comprehensive experimental dataset was analyzed using multiple linear regression (MLR), multiple nonlinear regression (MNLR), gradient boosting machine (GBM), extreme gradient boosting (XRT), random forest (RF), M5 (pruned and unpruned), random tree (RT), and reduced error pruning (REP). Model performance was evaluated based on key metrics: correlation coefficient (CC), root mean square error (RMSE), and mean absolute error (MAE).
View Article and Find Full Text PDFMolecular characterization of a novel victorivirus isolated from Stagonosporopsis citrulli.
Arch Virol
December 2024
Hubei Key Laboratory of Germplasm Innovation and Utilization of Fruit trees, Research Institute of Fruit and Tea, Hubei Academy of Agricultural Sciences, Wuhan, Hubei, 430064, P. R. China.
Members of the fungal genus Stagonosporopsis are important plant pathogens that can cause severe disease on a wide range of economically important plants and crops. Here, a novel victorivirus, tentatively named "Stagonosporopsis citrulli victorivirus 1" (SciVV1), was isolated from S. citrulli isolate HS2-8.
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