Fever is a common illness in the pediatric age group ,the causes could be viral ,bacterial and fungal , this study was focused on bacterial pathogens as gram positive like Staphylococci, coagulase positive or negative ,Streptococci and gram negative like E-coli , Klebsialla ,Proteus, Pseudomonas, Burkhoderia , Acinetobacter and others like Pusturella ,E-alkalescendiaper, Haemophillus influenza and yeast like candida . Four thousand and seventy eight blood samples (4078)were collected in a period between January 2011 and the end of May 2012 at the child welfare hospital ,all the samples were cultured on suitable culture media and then biochemical tests were done using API-E 20 and sugar fermentation tests ,sensitivity

Background: Oral tumors are one of the most challenging
tumors regarding their good prognosis in early diagnosis and
very difficult control in advancing stages.
Objectives: To study the prevalence, types and clinical
presentation of oral tumors in comparison to other oral
lesions among patients attending ENT clinic.
Al-Kindy Col Med J 2008 Vol.5(1) Original Article 11
Methods: This study included 534 patients with different
oral complains attending ENT clinics in AI-Yarmouk
Teaching Hospital, and AI-Kindy Teaching Hospital -
Baghdad, in the period from 1st jan1999 till 31th des 2006 (8
years interval).
Results: The results of this study showed that the prevalence
of malignant lesions was 13.5% (72 o

Abstract

Objectives: To find out the association between enhancing learning needs and demographic characteristic of (gender, education level and age).

Methods: This study was conducted on purposive sample was selected to obtain representative and accurate data consisting of (90) patients who are in a peroid of recovering from myocardial infarction at Missan Center for Cardiac Diseases and Surgery, (10) patients were excluded for the pilot study, Data were analyzed using descriptive statistical data analysis approach of frequency, percentage,  and analysis of variance (ANOVA).

Results: The study finding shows, there was sign

In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.

Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

This study aims to analyze the spectral properties of plasma produced from rice husk(Rh) using the laser breakdown spectroscopy (LIBS) method. The plasma generation process used the fundamental harmonic (1064 nm) of a Q-switched Nd:YAG laser. Yttrium aluminum garnet (YAG) is a man-made crystalline material. The laser fired pulses with a duration of 10 ns and a repetition rate of 6 Hz. Thus, the energy outputs achieved were 50–200 mJ at the wavelength of 1064 (nm). The silica content in the rice hulls was verified using an XRF measurement, which revealed the presence of silica in the rice hulls in a high percentage. Precise beam focusing was achieved by focusing the laser on the target material. This target material is placed with

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

The study area is located within the Hit area, western Iraq. The measurements of Graphical Bristow’s method were carried out by using Pole-dipole array, to delineate the anomaly of apparent resistivity caused by a known cavity target. The survey was applied along two traverses: traverse in W-E direction and traverse in S-N direction above Um El-Githoaa cavity. Data interpretation of the traverse trending W-E, with a-spacing equal to(2m)identified the anomaly of the cavity at a depth of (2.6m), (1.6m) height, and( 9.5m) width, while the actual dimensions of depth, height, and width were (3.80m),( 2.2m), and (12.30m) respectively, with variations of depth equal to (1.2m), high (0.8m), and width( 2.8m). The data interpretation with a-spac