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Convolutional neural network (CNN) has been successfully applied in character recognition. To further reduce the error rate of classification, based on traditional CNN, a recurrent-type CNN (RCNN) is presented in this paper. The Elman-Jordan recurrent model is embedded in the full connection layer of the proposed CNN. By optimizing the structure of the traditional CNN and making full use of the better...
This paper proposes a cloud application framework, which integrates both the development and production environment seamlessly. The framework consists of the client-side integrated development environment (IDE), and the server-side service portfolio and cloud controller. The IDE has requirement definition, architecture design and application prototyping tools, and it can simulate execution of large-scale...
Efficient methods for Local Field Potential (LFP) signal analysis amenable to interpretation are becoming increasingly relevant. LFP signals are believed, in part, to reflect neural action potential activity, and LFP frequency modulations are linked to spiking events. Furthermore, LFP signals are increasingly accessible in human brain regions previously unreachable due to a proliferation of deep brain...
Almost all existing social learning models assume that each agent can perceive her private signal which is used in updating her belief. In this work, we assume that there are some uninformed agents in the network which cannot observe their private signals and update their beliefs just based on the beliefs of their neighbors. We prove that under mild assumptions, even one informed agent is enough to...
Cloud computing paradigm contains many shared resources, such as infrastructures, data storage, various platforms and software. Resource monitoring involves collecting information of system resources to facilitate decision making by other components in Cloud environment. It is the foundation of many major Cloud computing operations. In this paper, we extend the prevailing monitoring methods in Grid...
This paper proposes a framework, which integrates the development and operation environments for cloud applications. Adopting perspectives on lifecycle management, the framework is equipped with tools and platforms, which seamlessly integrate lifetime phases: requirement analysis, architecture design, application implementation, operation and improvement. These are predicated on theories in design...
To propose test day model genetic parameter estimation and breeding value prediction for the dairy cow genetic evaluation system, mathematical models, relational database development tools, SQL SERVER. Determination of cows on the system to record data management, genetic parameter estimation and breeding value estimation fusion as a whole, to provide users with a unified window interface, and to...
As software being used in a larger scale, the problems of their reliability become more and more important. In addition to the design problems of the software itself, more attention was paid to the statistical law showed by the software reliability. As researches getting along, lots of patterns are raised. However, some of the patterns pay too much attention to the randomness of the software failure...
The back-analysis of mechanics parameters needs iterative forward calculating, resulting in low efficiency; meanwhile the Particle Swarm Optimization (PSO) algorithm and other optimization algorithms are exposed to local optimum possibilities. In this paper, DEPSO-ParallelFEM, a system integrated of an algorithm of hybrid particle swarm with Differential Evolution (DE) operator, termed DEPSO, and...
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