a new structure learning approach for bayesian networks (bns) based on asexual reproduction optimization (aro) is proposed in this letter. aro can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. in aro, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survi...

This tutorial will discusses the issues related to content based retrieval in very large dataset of visual documents. Content based retrieval typically is not performed using the visual content itself, rather visual features are extracted and retrieval is performed searching by similarity on the extracted features. Similarity search is a difficult task because efficient techniques to process da...

We present a method for measuring similarity among any two image pixels, based on the distribution of image chromaticities near each pixel. This measure is designed for algorithms that use pairwise pixel similarity measures to segment images. We describe a way to combine the proposed color-based measure with previously developed grayscale similarity measures. We show that adding the colorbased ...

The hub location problem is employed for many real applications, including delivery, airline and telecommunication systems and so on. This work investigates on hierarchical hub network in which a three-level network is developed. The central hubs are considered at the first level, at the second level, hubs are assumed which are allocated to central hubs and the remaining nodes are at the third ...

In this paper we consider similarity between documents in contexts defined by ontologies. Two documents have different similarity degree depending on the context in which they are considered. We consider a scenario where context evolves incrementally, necessitating continual revision of similarity measures between documents. We develop algorithms that revise similarity between documents concurr...

Background: Regarding the importance of right diagnosis in medical applications, various methods have been exploited for processing medical images solar. The method of segmentation is used to analyze anal to miscall structures in medical imaging.Objective: This study describes a new method for brain Magnetic Resonance Image (MRI) segmentation via a novel algorithm based on genetic and regiona...

Background: The link prediction issue is one of the most widely used problems in complex network analysis. Link prediction requires knowing the background of previous link connections and combining them with available information. The link prediction local approaches with node structure objectives are fast in case of speed but are not accurate enough. On the other hand, the global link predicti...

Many different methods for automatic retrieval of music similarity have been proposed. There are a number of low-level descriptors that are widely used as a basis for comparison algorithms. Although the different authors usually have different sets of songs to evaluate the algorithms and there usually is no exhaustive user evaluation, which makes the comparison between the different algorithms ...

The purpose of this paper is to present a mathematical model for estimating semantic similarity among sentences in texts. The similarity measure is constructed from the semantic similarity among concepts and a set of concepts. Based on this model, we develop algorithms to calculate the semantic similarity between two set of concepts and then the ones to estimate the semantic similarity between ...

Wavelet-domain hidden Markov models have proven to be useful tools. for statistical signal and image processing. The hidden Markov tree ( H M T ) model captures the key features of the joint statistics of the wavelet coeficients of real-world data. One potential drawback to the H M T framework is the need for computationally expensive iterative training (using the E M algorithm, fo r example). ...