Artificial Neural Networks (ANN) have been essentially used as regression models to predict the concentration of one or more pollutants usually requiring information collected from air quality stations. In this work we consider a Multilayer Perceptron (MLP) with one hidden layer as a classifier of the impact of air quality on human health, using only traffic and meteorological data as inputs. O...

As an important preprocessing technology in text categorization (TC), feature selection can improve the scalability, efficiency and accuracy of a text classifier [1]. In this paper, we propose a two-stage TC model—a fully non-parametric feature selection model. This classification model first selects features using non-parametric statistical methods, and then applies non-parametric classifiers ...

In digital image classification the conventional statistical approaches for image classification use only the gray values. Different advanced techniques in image classification like Artificial Neural Networks (ANN), Support Vector Machines (SVM), Fuzzy measures, Genetic Algorithms (GA), Fuzzy support Vector Machines (FSVM) and Genetic Algorithms with Neural Networks are being developed for imag...

One of the major health problems of global concern is Tuberculosis (TB). According to global report of the WHO, approximately 1.3 million people, out of the 8.6 million reported, died of TB in 2012. Most of the TB deaths can be prevented if it is detected at an early stage. Hindrance to this is improper diagnosis at initial stages. Chest X ray (CXR) image is the primary medical diagnosis used f...

One of the most severe threats to revenue and quality of service in telecom providers is fraud. The advent of new technologies has provided fraudsters new techniques to commit fraud. SIM box fraud is one of such fraud that has emerged with the use of VOIP technologies. In this work, a total of nine features found to be useful in identifying SIM box fraud subscriber are derived from the attribut...

Oral Bioavailability is the rate and extent to which an active drug substance is absorbed and becomes available to the general circulation. A computational model for the prediction of oral bioavailability is a vital initial step in the drug discovery. It is decisive for selecting the promising compounds for the next level optimizations and recognition for the clinical trials. In the present inv...

One approach to deal with real complex systems is to use two or more techniques in order to combine their different strengths and overcome each other’s weakness to generate hybrid solutions. In this project we pointed out the needs of an improved system in toxicology prediction. An architecture able to satisfy these needs has been developed. The main tools we integrated are rules and ANN. We de...

While many non-destructive ultrasonic signal test scenarios involve very shallow surfaces, signals for testing shafts are long and the new problem of mode-converted reflection emerges. They are echoes that do not correspond to cracks in the material, neither to characteristics of the shaft. Also, the length of the signals demands the application of efficient feature extraction mechanism to redu...

The prediction of traffic accidents is one of most important issues in our life. In the prediction of traffic accidents, a GIS platform to extract the important features including day, temperature, humidity, weather conditions, and month of occurred traffic accidents has been used. In this study, a decision making system (DMS) based on correlation-based feature selection and classifier algorith...

We investigated the feasibility of using texture features extracted from mammograms to predict whether the presence of microcalcifications is associated with malignant or benign pathology. Eighty-six mammograms from 54 cases (26 benign and 28 malignant) were used as case samples. All lesions had been recommended for surgical biopsy by specialists in breast imaging. A region of interest (ROI) co...