Self-supervised learning typically suffers from lacking contrastive pairs and extracting unrepresentative vectors. To handle above mentioned challenges, this paper introduces a novel self-supervised learning framework...
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With the advent of artificial intelligence (AI)., organizations can harness the power of machine learning algorithms and big data analytics to gain greater insight into their supply chain processes and make more infor...
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There is growing attention on the importance of building intelligent systems where humans and Artificial Intelligence-based systems (AIs) form teams exploiting the potentially synergistic relationships between humans ...
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In this paper, a Super-Twisting sliding mode control strategy on account of a nonlinear disturbance observer is proposed to solve the problem of disturbance suppression in the beam scanning process of MEMS micromirror...
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From the analysis of static and dynamic characteristics of parallel machine tools, it can be found that the stiffness and vibration response of machine tools in different positions are obvious, which will inevitably c...
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The article considers the process of manufacturing of art piece by investment casting with the use of additive technologies and computer modeling. Optimization of the technological process allowed to significantly imp...
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In healthcare 4.0 industry, feature selection plays a significant role in performance of the prediction models. Feature selection provides a platform to improve the accuracy of the healthcare models and reduced the co...
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Existing Vehicle Monitoring Systems use an OBD-II device to retrieve problem codes and live data from the vehicle, which is then displayed to the user as raw data. A user-friendly system is required so that the user c...
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With over 90 storms emerging worldwide each year, tropical cyclones (TCs) are the most damaging weather systems to emerge over the tropical oceans. For the purpose of providing advanced warning to the impacted areas, ...
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This paper applies the theory of granular computing to the load forecasting model of electric power systems. By constructing the electric load data as a fuzzy extension set, the concepts of detectors and sample spaces...
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