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Displacement amplification ratio and input stiffness are significant design characteristics for an ultra-precision positioning flexure-based compliant mechanism. Early and accurate performance prediction models can significantly improve the reliability and availability of product in the field of ultra-precision positioning, but Existing theoretic models cannot predict its characteristics accurately...
Identifying the genes causing a genetic disease is a key challenge in human health. Recently molecular interaction data has been used to prioritize candidate genes with respect to a particular disease. As a result, different methods have been implemented to rank genes which cause a given disease. However it has been suggested in literature that, to prioritize candidate genes it is necessary to consider...
Many methods for inferring genetic regulatory networks have been proposed. However inferred networks can hardly be used to analyze the dynamics of genetic regulatory networks. Recently nonlinear differential equations are proposed to model genetic regulatory networks. Based on this kind of model, the stability of genetic regulatory networks has been intensively investigated. Because of difficulty...
Modeling genetic regulatory networks in terms of differential equations with time delays provides a powerful tool for understanding gene regulatory processes in living organisms. In this paper we studied the globally delay-independent stability ring-structured genetic regulatory networks. We first present a sufficient condition for globally delay-independent stability of such genetic regulatory networks,...
From biochemical reaction principles, a genetic regulatory network can be described by a group of nonlinear differential equations with time delays. Previous studies have investigated delay-independent stability of genetic regulatory networks with time delays. However, if it is delay-independently stable, a genetic regulatory network loses other interesting properties such as oscillation. In this...
This paper deals with application of fuzzy least square method to the land-cover classification of remotely sensed data. The proposed method has a considerable advantage of extracting the reflectance of spectral bands for each category from pixel data and thus avoiding difficulties in electing training sets for each land-cover class when the class number gets large, which exist in conventional supervised...
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