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The sequence patterns of 11 types of frequently occurring connecting peptides, which lead to a classification of supersecondary motifs, were studied. A database of protein supersecondary motifs was set up. An artificial neural network method, i.e. the back propagation neural network, was applied to the predictions of the supersecondary motifs from protein(More)
The rise of health care cost is one of the world’s most important problems. Disease prediction is also a vibrant research area. Researchers have approached this problem using various techniques such as support vector machine, artificial neural network, etc. This study typically exploits the immune system’s characteristics of learning and memory to solve the(More)
Estimation of distribution algorithms are a class of optimization algorithms based on probability distribution model. In this paper, we propose an improved estimation of distribution algorithm using opposition-based learning and Gaussian copulas. The improved algorithm employs multivariate Gaussian copulas to construct probability distribution model and(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a r t i c l e i n f o a b s t r a c t In this paper, we introduce the maximum(More)
a r t i c l e i n f o a b s t r a c t In this paper, we introduce the maximum duo-preservation string mapping problem (MPSM), which is complementary to the minimum common string partition problem (MCSP). When each letter occurs at most k times in any input string, the version of MPSM is called k-MPSM. In order to design approximation algorithms for MPSM, we(More)
Network anomaly detection has become the promising aspect of intrusion detection. The existing anomaly detection models depict the detection profiles with a static way, which lack good adaptability and interoperability. Furthermore, the detection rate is low, so they are difficult to be deployed the realtime detection under the high-speed network(More)
—Based on the correspondence between the artificial immune system antibody and pathogen invasion intensity, this paper is to establish a real-time network risk evaluation model. According to the network intrusion own characteristics and the consequence from service, assets and attack, this paper design to build a hierarchical, quantitative measurement(More)