This paper presents a relevance vector regression (RVR) based parametric approach to the bias field estimation in brain magnetic resonance (MR) image segmentation. Segmentation is a very important and challenging task in brain analysis, while the bias field existed in the images can significantly deteriorate the performance. Most of current parametric bias field correction techniques use a pre-...

This paper presents a new computer aided detection method for identifying malignant images in digital mammograms using fuzzy soft set theory approach. Fuzzy soft set theory is a mathematical model based on parameterization concept for solving uncertainties and we have implemented a more efficient decision making method using fuzzy soft aggregation operator. This method helps the radiologists to...

This paper proposes an automatic system which can perform the entire diagnostic process from the extraction of the liver to the recognition of a tumor. In particular, the proposed technique uses shape information to identify and recognize a lesion adjacent to the border of the liver, which can otherwise be missed. In addition, since the intensity of a lesion can vary greatly according to the pa...

The steady-state operation of maintaining voltage stability is done by switching various controllers scattered all over the power network. When a contingency occurs, whether forced or unforced, the dispatcher is to alleviate the problem in a minimum time, cost, and effort. Persistent problem may lead to blackout. The dispatcher is to have the appropriate switching of controllers in terms of typ...

The Demarcation and prediction of the area of the tumor have an important role in medical treatments of malignant tumors. This paper describes an application of Fuzzy set theory in medical image processing, namely brain tumor demarcation. Fuzzy C-Means is proved to be a good and efficient segmentation method. But the main disadvantage of this method is that it is highly sensitive to noise. In t...

We investigated the Classification of satellite images and multispectral remote sensing data .we focused on uncertainty analysis in the produced land-cover maps .we proposed an efficient technique for classifying the multispectral satellite images using Support Vector Machine (SVM) into road area, building area and green area. We carried out classification in three modules namely (a) Preprocess...

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...

Data clustering techniques have been applied to extract information from gene expression data for two decades. A large volume of novel clustering algorithms have been developed and achieved great success. However, due to the diverse structures and intensive noise, there is no reliable clustering approach can be applied to all gene expression data. In this paper, we aim to the feature of high no...

In psychopathological diagnosis, a correct classification of mental retardation level is needed to choose the better treatment for rehabilitation and to assure a quality of life suitable for the specific patient condition. In order to meet this need we studied a technique that allows to perform automatic diagnoses efficiently and reliably and at the same time is easy for psychotherapists to use...