Microarray Data Retrieval Using Fuzzy Signature Sets

Interactive image retrieval using fuzzy sets

We present an image retrieval system which permits the user to submit a coarse initial query and continuously re®ne it. The user's relevance feedbacks is modeled by fuzzy sets, and is used to discover and use the more discriminatory features for the given query. The proposed system uses a dissimilarity measure based on the fuzzy integral.

Fuzzy retrieval of encrypted data by multi-purpose data-structures

The growing amount of information that has arisen from emerging technologies has caused organizations to face challenges in maintaining and managing their information. Expanding hardware, human resources, outsourcing data management, and maintenance an external organization in the form of cloud storage services, are two common approaches to overcome these challenges; The first approach costs of...

Dominant Sets in Microarray Data

Clustering allows us to extract groups of genes that are tightly coexpressed from Microarray data. In this paper, a new method DSF_Clust is developed to find dominant sets (clusters). We have preformed DSF_Clust on several gene expression datasets and given the evaluation with some criteria. The results showed that this approach could cluster dominant sets of good quality compared to kmeans met...

cDNA Microarray Data Normalization

PRICING STOCK OPTIONS USING FUZZY SETS

We use the basic binomial option pricing method but allow someor all the parameters in the model to be uncertain and model this uncertaintyusing fuzzy numbers. We show that with the fuzzy model we can, with areasonably small number of steps, consider almost all possible future stockprices; whereas the crisp model can consider only n + 1 prices after n steps.