Clustering is the process of dividing a set of input data into a number of subgroups. The members of each subgroup are similar to each other but different from members of other subgroups. The genetic algorithm has enjoyed many applications in clustering data. One of these applications is the clustering of images. The problem with the earlier methods used in clustering images was in selecting in...

We introduce a density-based clustering method called skeleton that can detect clusters in multivariate and even high-dimensional data with irregular shapes. To bypass the curse of dimensionality, we propose surrogate density measures are less dependent on dimension but have intuitive geometric interpretations. The framework constructs concise representation given as an intermediate step be tho...

The increasingly larger scale of available data and the more restrictive concerns on their privacy are some of the challenging aspects of data mining today. In this paper, Entropy-based Consensus on Cluster Centers (EC3) is introduced for clustering in distributed systems with a consideration for confidentiality of data; i.e. it is the negotiations among local cluster centers that are used in t...

this study aimed at investigating the effect of graphic organizer strategy on improving iranian efl learners’ vocabulary learning. fifty students participated in this study which lasted for one academic semester. the students were divided into two groups: one experimental group in which students were taught new vocabulary items through graphic organizers in form of clusters and pictures, and on...

a thorough recognition of the nature and duties of the genes is based upon having adequate information about the proteins. however, the proteomic projects follow a slow trend; therefore, solving the protein-related problems has become as one of the most important challenges in bio-informatics. consequently, the presence of tools which can enhance the structural recognition, classification, and ...

Introduction: Contrary to Diagnostic and Statistical Manual of Mental Disorders (DSM-5), fifth edition, some studies indicate that ADHD-inattentive presentation (ADHD-I) is a distinct diagnostic disorder and not an ADHD presentation.  Methods: In this study, 12 ADHD-combined presentation (ADHD-C), 10 ADHD-I, and 13 controls were enrolled and their resting state EEG recorded. Following thi...

Recognizing genes with distinctive expression levels can help in prevention, diagnosis and treatment of the diseases at the genomic level. In this paper, fast Global k-means (fast GKM) is developed for clustering the gene expression datasets. Fast GKM is a significant improvement of the k-means clustering method. It is an incremental clustering method which starts with one cluster. Iteratively ...