We propose a new passive system for indoor localization of mobile nodes. After the setup, our system only relies on arbitrary wireless communication from the nodes, whereby neither the mobile nodes nor the communication needs to be under our control. The presented system is composed of three Artificial Neural Networks (ANN) using a radiomap approach and the Received Signal Strength (RSS) for lo...

This paper describes a novel application of a probabilistic neural network for overcoming the computational complexity involved in performing sensor configuration management in a collaborative sensor network. We consider the problem of reliably tracking a target moving through a field of stationary sensors by fusing the measurements returned from the distributed array of sensors while conservin...

Gene expression profiling by microarray technology has been successfully applied to classification and diagnostic prediction of cancers. Various machine learning and data mining methods are currently used for classifying gene expression data. However, these methods have not been developed to address the specific requirements of gene microarray analysis. First, microarray data is characterized b...

Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...

In this paper a Neural Networks (NN) is proposed for transient stability prediction. Transient stability of a power system is first determined based on the generator relative rotor angles procured from time domain simulation outputs. Simulations were carried out on a single machine infinite bus system by considering three phase short circuit fault on the system. The data collected from the time...

Protein Secondary Structure Prediction (PSSP) is considered as one of the major challenging tasks in bioinformatics, so many solutions have been proposed to solve that problem via trying to achieve more accurate prediction results. The goal of this paper is to develop and implement an intelligent based system to predict secondary structure of a protein from its primary amino acid sequence by us...

The paper presents assessment of various power quality events based on Empirical Mode Decomposition (EMD) with Hilbert Transform (HT). EMD method decomposes the signal into waveforms modulated in both amplitude and frequency. The oscillatory modes embedded in the signal are extracted by employing sifting process. These oscillatory modes are called Intrinsic Mode Functions (IMFs). The magnitude ...

Artificial neural networks are promissing for separating signals from interference. However, their success depends on the amount of training data and network complexity which is prohibitively high. Pruned neural networks (PNN) are explored in this paper for the specific problem of separating artifacts from EEG signals. It is shown that PNN provides better performance than the fully interconnect...

Introduction: In this paper, a method is presented to classify the breast cancer masses according to new geometric features. Methods: After obtaining digital breast mammogram images from the digital database for screening mammography (DDSM), image preprocessing was performed. Then, by using image processing methods, an algorithm was developed for automatic extracting of masses from other norma...

In India, the oral cancers are usually presented in advanced stage of malignancy. It is critical to ascertain the diagnosis in order to initiate most advantageous treatment of the suspicious lesions. The main hurdle in appropriate treatment and control of oral cancer is identification and risk assessment of early disease in the community in a cost-effective fashion. The objective of this resear...