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Research ArticleOpen accessIn the abstractNON-COOPERATIVE IRIS RECOGNITION: A NOVEL APPROACH FOR SEGMENTATION AND FAKE IDENTIFICATIONM. Rajeev Kumar, M. Dilsath Fathima, K. Kiruthika, M. S. SaravananIris recognition, the ability to recognize and distinguish individuals by their pattern, is the most reliable biometric in terms of recognition and identification performance. However, performance of these systems is affected by the heterogeneous images (regarding focus, contrast, or brightness) and with several noise factors (iris obstruction and reflection) when the cooperation is not expectable from the subject. Current Iris … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 6,750 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Robust Recognition System for Pecan Weevil using Artificial Neural NetworksSaleh Mufleh Al-SaqerProblem statement: Pecan Weevil is a widely found pest among pecan trees and these pests are known to cause significant damage to the pecan trees resulting in enormous annual losses to pecan growers. Traditional identification techniques for pecan weevil include traps with pheromones to detect the infestation of these pests. However, these traditional methods require expensive labor hours to set-up … …American Journal of Applied Sciences, Vol. 9, Issue 9 · 14 Jul 2012 · 6,836 accessesView PDFCite
Research ArticleOpen accessIn the abstractExperiment of Tamper Detection and Recovery Watermarking in Picture Archiving and Communication SystemsSiau-Chuin Liew, Jasni Mohamad ZainProblem statement: Medical images such as x-rays, ultrasounds and Magnetic Resonance Imaging (MRI) plays an important role in helping the physicians to diagnose a disease or body conditions. These images can be tampered with existing image processing tools that is easily available. The usage of security measures such as watermarking can protect the integrity of the images. Numerous watermarking schemes … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,658 accessesView PDFCite
Review ArticleOpen accessIn the abstractRoles of DLK1 in Liver Development and OncogenesisIsabella Kurnia Liem, Sibiri Indriyani, Msy Rulan Adnindya, Ahmad Azmi NasutionHepato Cellular Carcinoma (HCC) has an increased mortality rate in the last decade. Protein expression in HCC has similarities to the liver cells during the development process. One of the proteins expressions is Delta-Like 1 homolog (DLK1) that was found during liver development and oncogenesis. This permits the opportunity to study pathophysiology and signaling pathway of DLK1 and to find … …OnLine Journal of Biological Sciences, Vol. 17, Issue 4 · 23 Oct 2017 · 8,056 accessesView PDFCite
Research ArticleOpen accessIn the abstractPotential Role of Migratory Quail in Spreading of Some Zoonotic Pathogens in EgyptAhmed I. Youssef, Dalia H. MansourThis study aimed to illustrate the potential role of wild migratory quails in the epidemiology of some zoonotic pathogens in Egypt. Ninety four apparently healthy migratory quails were collected from public markets after being trapped during hunting season from the North Sinai. Oral, cloaca and organs (liver, lung and heart) swabs were collected for bacteriological and viral examination. Bacteriological examination … …American Journal of Animal and Veterinary Sciences, Vol. 9, Issue 4 · 13 Dec 2014 · 7,532 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,081 accessesView PDFCite
Research ArticleOpen accessIn the abstractOPTIMIZED INCIDENT MATCHING AND AUTO-MATED VERIFICATION OF COMPOSITION PAT-TERNS IN LONG TERM COMPOSED SERVICESM. Thirumaran, M. Jannani, P. DhavachelvanWith the increase in the need and demand for evolving Web services, the rate at which changes are made to the services has increased. In case of importunate change requests, there arise critical situations where the business analysts are subjected to make changes by themselves without the aid of the developers because of the time and cost factors. However, there … …Journal of Computer Science, Vol. 10, Issue 10 · 12 May 2014 · 6,647 accessesView PDFCite
Research ArticleOpen accessIn the abstractSPLINE ACTIVATED NEURAL NETWORK FOR CLASSIFYING CARDIAC ARRHYTHMIAY. S. Kumaraswamy, R. Ganesh KumarElectro Cardiogram’s (ECG) biomedical signals characterizing cardiac anomalies are used for identifying cardiac arrhythmia. Irregular heartbeat-Arrhythmia-affects heart rate causing problems. Many methods, trying to simplify arrhythmia monitoring through automated detection, were developed over the years. ECG classification for arrhythmia is investigated in this paper based on soft computing techniques. RR interval are extracted from time series of the ECG and … …Journal of Computer Science, Vol. 10, Issue 8 · 9 Apr 2014 · 6,973 accessesView PDFCite
Research ArticleOpen accessIn the abstractA NEW AIR CONDITIONING SYSTEM FAN MODEL BASED ON NUMERICAL ANALYSISNabil Nassif, Raymond Tesiero, Nihal AlRaeesA large portion of energy use in buildings is attributed to air movement devices. Accurate estimation of fan performance is a key element in maximizing fan efficiency. This study proposes a new fan model that can be used in several applications such as optimization and fault detection and can also be incorporated into any commercial building models. The model uses … …American Journal of Engineering and Applied Sciences, Vol. 7, Issue 1 · 14 Mar 2014 · 8,189 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE ANALYSIS OF BRAIN TUMOR DIAGNOSIS BASED ON SOFT COMPUTING TECHNIQUESP. Shantha Kumar, P. Ganesh KumarComputed tomography images are widely used in the diagnosis of brain tumor because of its faster processing, avoiding malfunctions and suitability with physician and radiologist. This study proposes a new approach to automated detection of brain tumor. This proposed work consists of various stages in their diagnosis processing such as preprocessing, anisotropic diffusion, feature extraction and classification. The local binary … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 27 Dec 2013 · 6,989 accessesView PDFCite