The investigation of crustal stress state is an important scientific problem for the theoretical investigating of tectonic processes and solving many practical issues of mineral deposits searching and exploration, und...
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At present, the self-similarity of images has received wide attention in many fields such as image compression. Most of the images have strong self-similarity through the human eye visual system observation. However, ...
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At present, the self-similarity of images has received wide attention in many fields such as image compression. Most of the images have strong self-similarity through the human eye visual system observation. However, the special images with strong self-similarity for human eye observation such as biomicroscopy are not digitally reflected by a certain algorithm, this paper proposes a self-similarity coefficient algorithm that is applicable to special natural images such as biomicroscopy and aerial photography, which has high self-similarity coefficients for biomicroscopy and other images.
The edgeless active contour model can solve the initialization problem, noise problem and boundary leakage problem, but due to the use of level sets, there are still problems of low computational efficiency and diffic...
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The edgeless active contour model can solve the initialization problem, noise problem and boundary leakage problem, but due to the use of level sets, there are still problems of low computational efficiency and difficult implementation. Combining the global effect of CV model and the local effect of RSF, this paper establishes a global and local biphasic level set model based on CV-RSF by setting weight coefficients and introducing bilevel set. By increasing the energy penalty term, the level set function maintains an approximate signed distance function during the evolution process. The comparison experiments with other level set models show that the segmentation efficiency and accuracy of this model are improved.
Virtual machine provides cloud computing services that offer computing resources to users through the Internet based on virtualization technology. Generally, supercomputing or gridcomputing has been used to process a...
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ISBN:
(纸本)9789813292444;9789813292437
Virtual machine provides cloud computing services that offer computing resources to users through the Internet based on virtualization technology. Generally, supercomputing or gridcomputing has been used to process a large scale job in scientific, technology, and engineering application problems. Currently, services for large scale parallel processing through idle virtual machines in cloud computing are not provided. Previously, the utilization rate of computing resources in cloud computing was low when users do not use virtual machines anymore or for a long period of time since all the rights in relation to the use of virtual machine are given to users. This study proposes a scheme that increase resource utilization of idle virtual machines and process a large scale job through the idle virtual machines. Basically, idle virtual machines are identified based on virtual machines created through OpenStack, and idle virtual machine-computing service (IVM-CS) is proposed.
This chapter presents the application of an artificial neural network-based monitoring system power grid network. Neural net modules used for this study are of two kinds, a distributed separate artificial neural net (...
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This paper explores parallelism performance for C, C++, Go, Java, Julia, and Rust on N-body simulations. We begin with a basic O(N2) simulation for each language based on the n-body benchmark in the Benchmark Game. Th...
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The power Internet of things (IOT), which integrates edge computing, has become a research hotspot because of its characteristics of edge intelligence, wide interconnection and real-time decision-making. However, with...
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Complex interference signal identification has been a paramount concern, yet there are very few effective methods. In this work, we propose a composite interference signal identification method based on target detecti...
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Complex interference signal identification has been a paramount concern, yet there are very few effective methods. In this work, we propose a composite interference signal identification method based on target detection, which uses a detection box to detect the single interference signal in the composite interference signals (CISs) without separating CISs. This method based on YOLOv5 network can avoid the problem of difficult separation of CISs and be not affected by the multiple characteristics of the composite signal. It can not only effectively identify the composite signal, but also obtain the position information of each single signal. The experimental results validate our analysis. Moreover, it can be concluded that our proposed method is fault-tolerant and easy to migrate.
Simultaneous localization and mapping (SLAM) is a key problem for mobile robots to realize autonomous exploration. SLAM is a typical computing intensive task, and has high computing requirements for mobile robots. To ...
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Opinion prediction is an important and challenging task. Previous work often only predicts opinions based on users’ content, ignoring the influence of neighbors’ opinions on users in social networks. In this paper, ...
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Opinion prediction is an important and challenging task. Previous work often only predicts opinions based on users’ content, ignoring the influence of neighbors’ opinions on users in social networks. In this paper, we utlize Graph Attention Networks to capture neighbor information for opinion prediction. Firstly, we divide users in the online social media platform into general users and online influencers by the number of their fans. Then we built the implicit link between general users by their following list, and construct the implicit network for opinion prediction. Experimental results show that the proposed model is more accurate in opinion prediction compared to many competitive baselines.
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