Clustering is an important data exploration task. Its use in data mining is growing very fast. Traditional clustering algorithms which no longer cater to the data mining requirements are modified increasingly. Clustering algorithms are numerous which can be divided in several categories. Two prominent categories are distance-based and density-based (e.g. K-means and DBSCAN, respectively). While...

This paper presents a novel approach for automatic face recognition based on the Local Binary Patterns (LBP). One drawback of the current LBP based methods is that the feature positions are fixed and thus do not reflect the properties of the particular images. We propose to solve this issue by a method that automatically detects feature positions in the image. These key-points are determined us...

In this paper, we investigate the use of the non-local means (NLM) denoising approach in the context of image deblurring and restoration. We propose a novel deblurring approach that utilizes a non-local regularization constraint. Our interest in the NLM principle is its potential to suppress noise while effectively preserving edges and texture detail. Our approach leads to an iterative cost fun...

In this paper, the concept of {sl local base with  stratifiedstructure} in $I$-topological vector spaces is introduced. Weprove that every $I$-topological vector space has a balanced localbase with stratified structure. Furthermore, a newcharacterization of $I$-topological vector spaces by means of thelocal base with stratified structure is given.

in this paper, the concept of {sl local base with  stratifiedstructure} in $i$-topological vector spaces is introduced. weprove that every $i$-topological vector space has a balanced localbase with stratified structure. furthermore, a newcharacterization of $i$-topological vector spaces by means of thelocal base with stratified structure is given.

A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages ...

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The meshless local radial point interpolation (MLRPI) method is applied to examine the magnetohydrodynamic (MHD) ow of third grade uid in a porous medium. The uid saturates the porous space between the two boundaries. Several limiting cases of fundamental ows can be obtained as the special cases of present analysis. The variations of pertinent parameters are addressed.