The aim of the ERAMIS project is to create a Master degree Computer as a Second Competence in 9 beneficiary universities of Kazakhstan, Kyrgyzstan and Russia. This contribution presents how faculty development is orga...
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This paper presents Weight Computing in Competitive K-Means Algorithm which is derived from Improved K-means method and subspace clustering. By adding weights to the objective function, the contributions from each fea...
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This paper presents Weight Computing in Competitive K-Means Algorithm which is derived from Improved K-means method and subspace clustering. By adding weights to the objective function, the contributions from each feature of each clustering could simultaneously minimize the separations within clusters and maximize the separation between clusters. The experiments described in this paper confirm good performance of the proposed algorithm.
The increasing number of space missions and the market environment make it mandatory that the design process and design models have to be reused in future space missions. As a solution to such a reuse problem, Model-B...
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Along with the development of RFID technology, RFID tag is used for identifying object in more and more areas. RFID becomes one of the most important technologies in application and development of Internet of Things. ...
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The aim of the ERAMIS project is to create a Master degree “Computer as a Second Competence” in 9 beneficiary universities of Kazakhstan, Kyrgyzstan and Russia. This contribution presents how faculty development is ...
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The aim of the ERAMIS project is to create a Master degree “Computer as a Second Competence” in 9 beneficiary universities of Kazakhstan, Kyrgyzstan and Russia. This contribution presents how faculty development is organized inside this project.
The aim of the ERAMIS project is to set up a network of Master's degree “Informatics as a Second Competence” among 9 beneficiary universities of Kazakhstan, Kyrgyzstan and Russia, and 5 European universities. Th...
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The aim of the ERAMIS project is to set up a network of Master's degree “Informatics as a Second Competence” among 9 beneficiary universities of Kazakhstan, Kyrgyzstan and Russia, and 5 European universities. This contribution presents how this network is implemented.
Recent developments with Self-Organizing Maps (SOMs) produced methods capable of clustering graph structured data onto a fixed dimensional display space. These methods have been applied successfully to a number of ben...
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Situation Awareness is the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning and the projection of their status in the near future. It is a crucial fac...
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Neural networks have received much attention in the extraction of fetal electrocardiogram signal in recent years. This paper provides a new method to extract the fetal electrocardiogram signal which uses wavelet denoi...
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In this paper, we present a novel Differential Evolution (DE) algorithm to solve high-dimensional global optimization problems effectively. The proposed approach, called DEVP, employs a variable population size mechan...
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In this paper, we present a novel Differential Evolution (DE) algorithm to solve high-dimensional global optimization problems effectively. The proposed approach, called DEVP, employs a variable population size mechanism, which adjusts population size adaptively. Experiments are conducted to verify the performance of DEVP on 19 high-dimensional global optimization problems with dimensions 50, 100, 200, 500 and 1000. The simulation results show that DEVP out performs classical DE, CHC (Crossgenerational elitist selection, Heterogeneous recombination, and Cataclysmic mutation), G CMA-ES (Restart Covariant Matrix Evolutionary Strategy) and GODE (Generalized Opposition-Based DE) on the majority of test problems.
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