Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty

Amputation of the upper limb significantly hinders the ability of patients to perform activities of daily living. To address this challenge, this paper introduces a novel approach that combines non-invasive methods, specifically Electroencephalography (EEG) and Electromyography (EMG) signals, with advanced machine learning techniques to recognize upper limb movements. The objective is to improve the control and functionality of prosthetic upper limbs through effective pattern recognition. The proposed methodology involves the fusion of EMG and EEG signals, which are processed using time-frequency domain feature extraction techniques. This enables the classification of seven distinct hand and wrist movements. The experiments conducte

Background: H1N1 influenza pandemic or swine flu was an influenza pandemic first described in Iraq in October 2009 .The virus appeared to be anew strain of H1N1 causes wide range of morbidity and mortality among different genders and age groups as part of worldwide pandemics.Seasonal flu is a contagious respiratory illness caused by influenza viruses that infect the nose, throat, and lungs. It can cause mild to severe illness, and at times can lead to death. The best way to prevent the flu is by getting a flu vaccine each year.

Objectives: Is to determine the morbidity and mortality in different age groups in patients with H1N1 influenza versus those patients with seasonal influenza who were admitted at the same time to AL-kindy

Background: A Catheter-associated with candidiasis infection is the most common nosocomial infection and the objective of this work is to isolate and identify Candida species from catheterized patients by ordinary culture and PCR.Objective:To study the isolation and identification of Candida species from catheterized patients by culture media and polymerase chain reaction(PCR).Methods: One hundred and thirty five Candida species isolates were obtained from urine culture of catheterized specimens from male and female patients , During the period between October 2011 to April 2012 , attending AL-Ramadi general teaching Hospital. A quantitative urine culture for isolation and identification of Candida species was. The isolation of Candida s

Background: Invasion in oral cancer involves alterations in cell-cell and cell-matrix interactions that accompanied by loss of cell adhesion. Catenins stabilize cellular adherence junctions by binding to E-cadherin, which further mediates cell-cell adhesion and regulates proliferation and differentiation of epithelial cells. The Wnt/β-catenin pathway is one of the major signaling pathways in cell proliferation, oncogenesis, and epithelial-mesenchymal transition. Aims of the study: to detect immunohistochemical distribution pattern and different subcellular localization of β-catenin in oral squamous cell carcinoma and relate such expression to Bryne’s invasive grading system. Materials and Methods: This study included 30 paraffi

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

Background: The genetic polymorphisms of vitamin D receptor (VDR) have an association with thalassemia development, additionally to the environmental elements that elicited the disorder in the genetically predisposed individuals. As well, VDR functions responsible for the regulation of bone metabolism, such its part in immunity. Aim: The sitting study intended to inspect the association between thalassemia disease and the genetic polymorphisms of VDR among the Iraqi population then compared these findings to other findings of thalassemia patients in other different ethnic populations. Materials and methods: The restriction enzymes Bsm-I and Fok-I were applied to determine the genetic polymorphisms frequencies of VDR by a Polymerase Chain Re

      Basal breccia unconformity layer between Anah and Euphrates Formations in Al-Haqlaniyah area, Western desert, include enormous sinkholes and cavities usually cause severe damages to any kind of engineering facilities built over it. Two-dimensional resistivity imaging has been applied to detect the depth and extent of the subsurface caves at five stations. The dipole-dipole array is chosen with an electrode spacing of 2 meters. 2D Dipole-dipole imaging inverse models show the resistivity values have a big variation between the anomalous background resistivity of rocks and part of cavities. These models showed shallow cavities at 1 to 3 m depth and others at 5to 6 m depth and extending to a depth of 23 m. The unconformity layer