Brain tumor is the most deadly disease that affects human life span. To segment the brain tumor part, many segmentation techniques have been emerged in image processing like region based Segmentation, Boundary based segmentation. In this paper, several entropies based methods and several cluster techniques are compared and analyzed for brain tumor segmentation. Several entropies such as rough e...

As the number of networked computers grows, intrusion detection is an essential component in keeping networks secure. Various approaches for intrusion detection are currently being in use with each one has its own merits and demerits. This paper presents our work to test and improve the performance of a new class of decision tree c-fuzzy decision tree to detect intrusion. The work also includes...

This paper proposes a construction of a new distance in the HSL color space by a combination of the distances of HSL scalar components and by using the fuzzy cmeans framework to derive a fuzzy color clustering method. The main contribution consists in introducing two particular parameters to control the balance between the hue distance and the luminosity distance in the color Euclidean distance...

Fuzzy clustering has been used widely in education, statistics, engineering, communication...etc. The fuzzy partition clustering algorithms are most based on Euclidean distance function, which can only be used to detect spherical structural clusters. Extending Euclidean distance to Mahalanobis distance, GustafsonKessel (GK) clustering algorithm and Gath-Geva (GG) clustering algorithm were devel...

Fuzzy logic and genetic algorithms are well-established computational techniques that have been employed to deal with the problem of classification as this is presented in the context of data mining. Based on Fuzzy Miner which is a recently proposed state-of-the-art fuzzy rule based system for numerical data, in this paper we propose GF-Miner which is a genetic fuzzy classifier that improves Fu...

1106 | P a g e Abstract--Image processing plays an important role in medical field because of its capability. Particularly, image segmentation offer several guides in medical field for analyzing the captured image. Usually, the medical images are captured via different medical image acquisition techniques. The captured image may be affected by noise because of some faults in the capturing devis...

Image segmentation is one of the vital steps in Image processing. It is a challenging task in segmenting MRI(Magnetic Resonance Imaging) images because these images have no linear features. But MRI images provide high quality when compared to any other imaging techniques, so it is best suited for clinical diagnosis, biomedical research, etc. This paper presents a novel approach for segmenting M...

Clustering for data aggregation is essential nowadays for increasing the wireless sensor network (WSN) lifetime, by collecting the monitored information within a cluster at a cluster head. The clustering algorithm reduces overall transmission of data from each sensor to the sink node thus energy spent by individual sensor node is minimized .The cluster heads collect all sensed information from ...

In this paper, a new segmentation method using hyperbolic tangent fuzzy cmeans (MHTFCM) algorithm for medical image segmentation. The proposed method uses two hyperbolic tangent functions for clustering of images. The performance of the proposed algorithm is tested on OASIS-MRI image dataset. The performance is tested in terms of score, number of iterations (NI) and execution time (TM) under di...

The paper presents model based on fuzzy methods for churn prediction in retail banking. The study was done on the real, anonymised data of 5000 clients of a retail bank. Real data are great strength of the study, as a lot of studies often use old, irrelevant or artificial data. Canonical discriminant analysis was applied to reveal variables that provide maximal separation between clusters of ch...