Acoustical parameters extracted from the recorded voice samples are actively pursued for accurate detection of vocal fold pathology. Most of the system for detection of vocal fold pathology uses high quality voice samples. This paper proposes a hybrid expert system approach to detect vocal fold pathology using the compressed/low quality voice samples which includes feature extraction using wave...

P. Scheunders Vision Lab, Dept. of Physics, RUCA University of Antwerp, Groenenborgerlaan 171, 2020 Antwerpen, Belgium email: [email protected] Abstract: In this paper color image quantization by clustering is discussed. A clustering scheme, based on competitive learning is constructed and compared to the well-known C-means clustering algorithm. It is demonstrated that both perform equally w...

This paper presents Hybrid Particle Swarm Optimization (PSO) Genetic Algorithm (GA) approaches for the document clustering problem. To obtain an optimal solution using Genetic Algorithm, operation such as selection, reproduction, and mutation procedures are used to generate for the next generations. In this case, it is possible to obtain local solution because chromosomes or individuals which h...

A hybrid approach based on Fuzzy Logic and neural networks with the combination of the classic Hu & Zernike moments joined with Geodesic descriptors is used to keep the maximum amount of information that are given by the color of the image. These moments are calculated for each color level and geodesic descriptors are applied directly to binary images to get information about the general shape ...

Many visualization approaches teach us that ease of use is the key to effective visual data analysis. The Table Lens is an excellent example of a simple, yet expressive visual method that can help in analyzing even larger volumes of data. In this work, we present two extensions of the original Table Lens approach. In particular, we extend the Table Lens by Two-Tone Pseudo Coloring (TTPC) and a ...

In this paper we present an approach based on two hybrid clustering methods for Web Usage Mining (WUM). The WUM process contains three steps: pre-processing, data mining and result analysis. First, we give a brief description of the WUM process and Web data, followed in section 2 by the presentation of the pre-processing step and the data warehouse that we employed. Two hybrid clustering method...

Data mining algorithms extracts the unknown interesting patterns from large collection of data set. Some clandestine or secret information may be exposed as part of the data mining process. In this paper we put forward a hybrid approach for achieving privacy during the mining procedure. The first step is to sanitize the original data using a geometrical data transformation. In the second stage ...

Unrepresentative data samples are likely to reduce the utility of data classifiers in practical application. This study presents a hybrid mining approach in the design of an effective credit scoring model, based on clustering and neural network techniques. We used clustering techniques to preprocess the input samples with the objective of indicating unrepresentative samples into isolated and in...

This paper introduces a hybrid approach that is based on color information that utilizes a mask and K-Means clustering algorithm along with the frame averaging background subtraction technique. This hybrid approach efficiently removes artifacts caused by lightening changes such as highlight and reflection from segmentation, while also successfully removing shadows of stationary objects and dark...

BACKGROUND Clustering is a key step in the processing of Expressed Sequence Tags (ESTs). The primary goal of clustering is to put ESTs from the same transcript of a single gene into a unique cluster. Recent EST clustering algorithms mostly adopt the alignment-free distance measures, where they tend to yield acceptable clustering accuracies with reasonable computational time. Despite the fact th...