This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni

HR Al-Hamami, AA Noaimi, MM Al-Waiz, AS Al-Kabraty, Iraqi Postgraduate Medical Journal, 2010 - Cited by 4

AH Haider R, N Adil A, AW Makram M, AK Abdulkaleq S, 2010

Anti-Neutrophil Cytoplasmic Antibodies (ANCA) are a heterogeneous group of autoantibodies with a broad spectrum of clinically associated diseases. The diagnostic value is established for Proteinase 3 (PR3)-ANCA as well as Myeloperoxidase (MPO)-ANCA. To estimate the frequency of anti-neutrophile cytoplasmic antibodies (ANCA) in sera from a group of Iraqi patients with some autoimmune diseases compared with a healthy control group. Serum samples were collected from one hundred patient, 47 males and 53 females; with age range of 16-70 years; 20 specimens from patients with systemic lupus erythematosus (SLE), 30 from patients with ulcerative colitis (UC), and 50 from patients with rheumatoid arthritis (RA). A group of 40 apparently healthy b

OpenStreetMap (OSM) represents the most common example of online volunteered mapping applications. Most of these platforms are open source spatial data collected by non-experts volunteers using different data collection methods. OSM project aims to provide a free digital map for all the world. The heterogeneity in data collection methods made OSM project databases accuracy is unreliable and must be dealt with caution for any engineering application. This study aims to assess the horizontal positional accuracy of three spatial data sources are OSM road network database, high-resolution Satellite Image (SI), and high-resolution Aerial Photo (AP) of Baghdad city with respect to an analogue formal road network dataset obtain

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

        This Research deals with estimation the reliability function for two-parameters Exponential distribution, using different estimation methods ; Maximum likelihood, Median-First Order Statistics, Ridge Regression, Modified Thompson-Type Shrinkage and Single Stage Shrinkage methods. Comparisons among the estimators were made using Monte Carlo Simulation based on statistical indicter mean squared error (MSE) conclude that the shrinkage method perform better than the other methods