This article solves the issue of long extraction time and low extraction accuracy in traditional moving image contour feature extraction methods. Here authors have explored deformable active contour model to research the image processing technology in scientific research and the application of multiple sports and the method. A B-spline active contour model based on dynamic programming method is proposed in this article. This article proposes a method of using it to face image processing and extracting computed tomography (CT) image data to establish a three-dimensional model. The Lyapunov exponent, correlation dimension and approximate entropy of the nonlinear dynamics algorithm were used to extract the features of eight types of motor imagination electroencephalogram (EEG) signals. The results show that the success rate of pose reconstruction is more than 97% when the contour extraction quality is relatively ideal. The method is also robust to image noise, and the success rate of pose reconstruction can reach 94% when the video image has large noise. The execution efficiency is sub-linear, which can basically meet the requirements of real-time processing in video-based human posture reconstruction. The proposed method has a low error rate in the calculation of curvature features, effectively reduces the time for extracting contour features of moving images, and improves the accuracy of feature information extraction.
The emergence of Industry 4.0 has awoken the adoption of blockchain as a key factor to enhance the industrial supply chain across the globe, enabling cost-effective and fast-paced delivery of products and services, ownership of products with privacy, and high security as well as traceability. This new digital horizon is underpinning the future direction of humankind, aligning with the Sustainable Development Goal themes of Good Health and Well-being (SDG3) and Sustainable Cities and Communities (SDG 11). Thus, the main objective of this paper is to elucidate the adoption of blockchain technology in Science, Technology, Engineering, and Math (STEM) disciplines by determining of the key academic research players and the evolution of blockchain in different fields. It begins by clarifying the definition of these concepts, followed by a discussion regarding the chronological progress of blockchain over time, an evaluation of the adoption of blockchain technologies in different key research areas, and lastly, providing comments on several directions to guide practitioners in developing a sustainable global blockchain roadmap in education science.
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