In this paper, we propose an extension to the local binary patterns for image retrieval. We focus on the spatial distribution information in images, and present a spatial-distribution-information-enhanced local pattern for content-based image retrieval. Differing from traditional local patterns, we group those gray-level varying values according to three directions, and each group is then merge...

In this paper, we propose an effective microaggregation algorithm to produce a more useful protected data for publishing. Microaggregation is mapped to a clustering problem with known minimum and maximum group size constraints. In this scheme, the goal is to cluster n records into groups of at least k and at most 2k_1 records, such that the sum of the within-group squ...

the rapid change of land use and land cover in the metropolitan area of tehran has influenced the distribution pattern of land surface temperature (lst). in this study, a spatial autocorrelation analysis is adopted to process the spatial-temporal changes of lst and normalized difference vegetation index (ndvi) in tehran during the period of 1987 to 2010. global spatial autocorrelation analysis ...

introduction: counting is of the most basic mathematical abilities. many researches have demonstrated that different perceptual abilities can affect counting skills. we investigated the impact of visual search (vs) and visuoumotor organization (vmo) on counting speed. material  and  methods:   a  total  of  40  people  in  two  groups  of borderline  and  normal intellectual ability (20 subject...

In this paper the performance of the Cultural Algorithms-Iterated Local Search (CA-ILS), a new continuous optimization algorithm, is empirically studied on multimodal test functions proposed in the Special Session on Real-Parameter Optimization of the 2005 Congress on Evolutionary Computation. It is compared with state-of-the-art methods attending the Session to find out whether the algorithm i...

This study examined the selection of spatial frames of reference for target localization in visual search. Participants searched for local target characters in global character configurations. The local targets could be localized relative to the character configuration in which they were embedded or relative to the presentation screen on which the configurations were displayed. We investigated ...

UNIRANDI is a stochastic local search algorithm that performs line searches from starting points along good random directions. In this paper, we focus on a modified version of this method. The new algorithm, addition to the random directions, considers more promising directions in order to speed up the optimization process. The performance of the new method is tested empirically on standard tes...

A new local search algorithm for multiobjective optimization problems is proposed to find the global optima accurately and diversely. This paper models the cooperatively local search as a potential field, which is called neighborhood field model (NFM). Using NFM, a new Multiobjective Neighborhood Field Optimization (MONFO) algorithm is proposed. In MONFO, the neighborhood field can drive each i...

This paper discusses the reason why QEA works and verifies how QEA works. The theoretical analysis of the simplified model of the segment process of QEA shows that QEA with a single individual for ONEMAX problem guarantees the global solution in terms of expected running number of generations. The analysis for exploration shows clearly that QEA starts with a global search scheme and changes aut...