This article contemplates the problem of collecting and storing technological data during multichannel and multi - coordinate machining on CNC machines obtained using the OPC UA protocol and applying Node-RED open-sou...
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The aim of this research is to develop a specialized system for collecting and storing CNC machines data considering the possibilities of innovative technologies of OPC UA protocol, in this work an OPC UA information ...
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The process of developing a PLC program for controlling the electromechanical units of modern machine tools with computer numerical control (CNC) has been formalized. The architecture of a two-computer CNC system with...
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The paper considers the problems of manufacturing prototypes of printed circuit boards on bench-Type milling machines that require the prompt production of a small batch and correction, if it's necessary. We used ...
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There is a justified need for a cross-platform implementation of an OPC UA server for a CNC system. The available open-source libraries that implement the OPC UA stack have been analyzed, and a solution based on open6...
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The problem of synchronizing parallel tasks in control systems at the level of the part program is reviewed. A general solution, based on a high-level part programming language extension, is proposed for synchronizing...
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Binary translation serves as a fundamental technol-ogy for instruction set emulation, system virtualization, runtime instrumentation, and numerous other applications. Many techniques have been proposed to enhance the ...
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YOLOv7-tiny, as a lightweight variant of YOLOv7, boasts advantages of fast runtime and fewer parameters. However, when directly applied to infrared object detection, YOLOv7-tiny still faces challenges such as weak ext...
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The task of molecule generation guided by specific text descriptions has been proposed to generate molecules that match given text inputs. Mainstream methods typically use simplified molecular input line entry system(...
The task of molecule generation guided by specific text descriptions has been proposed to generate molecules that match given text inputs. Mainstream methods typically use simplified molecular input line entry system(SMILES) to represent molecules and rely on diffusion models or autoregressive structures for modeling. However, the one-to-many mapping diversity when using SMILES to represent molecules causes existing methods to require complex model architectures and larger training datasets to improve performance, which affects the efficiency of model training and generation. In this paper, we propose a text-guided diverse-expression diffusion(TGDD) model for molecule generation. TGDD combines both SMILES and self-referencing embedded strings(SELFIES) into a novel diverse-expression molecular representation, enabling precise molecule mapping based on natural language. By leveraging this diverse-expression representation, TGDD simplifies the segmented diffusion generation process, achieving faster training and reduced memory consumption, while also exhibiting stronger alignment with natural language. TGDD outperforms both TGM-LDM and the autoregressive model MolT5-Base on most evaluation metrics.
Rapid advances in deep learning and computer vision enable traditional cloud-based decision-making through edge computing with the Artificial Intelligent Internet of Things (AIoT) image sensors (AIoT-IS), thus improvi...
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