Recently new concepts such as free data or Volunteered Geographic Information (VGI) emerged on Web 2.0 technologies. OpenStreetMap (OSM) is one of the most representative projects of this trend. Geospatial data from different source often has variable accuracy levels due to different data collection methods; therefore the most concerning problem with (OSM) is its unknown quality. This study aims to develop a specific tool which can analyze and assess the possibility matching of OSM road features with reference dataset using Matlab programming language. This tool applied on two different study areas in Iraq (Baghdad and Karbala), in order to verify if the OSM data has the same quality in both study areas. This program, in general, consists of three parts to assess OSM data accuracy: input data, measured and analysis, output results. The output of Matlab program has been represented as graphs. These graphs showed the number of roads during different periods such as each half meter or one meter for length and every half degree for directions, and so on .The results of the compared datasets for two case studies give the large number of roads during the first period. This indicates that the differences between compared datasets were small. The results showed that the case study of Baghdad was more accurate than the case study of holy Karbala.
Abstract Objective: The aim of this study is to evaluate the level of the anatomical knowledge of undergraduate students in Nursing collage/Baghdad university.Methodology:The sample was collected by symmetrical probability. Research sample includes (197)students represent four classes which is distributed as following: fifty students represent first class, fifty students represent the second class, forty nine students represent the third class,&fourty eight students represent the fourth class. Results:The study concludes that the anatomical knowledge level for collage students is intermediate .The m
The objective of this study was to assess the nutritional status of childs of nurseries in Baghdad city so that an early detection of malnutrition cases could be carried out. The results revealed that the daily consumption of food calories, protein, fat and carbohydrate were 1180.5 calories, 27.2gm, 38gm and 180gm, respectively, which were less than the RDA values and the percentages of these nutrients supplied by the food intake were 90.8, 83.7, 87.3 and 90.3%, respectively. It was also demonstrated that the highest percentages of stunting, underweight and wasting, which amounted to 32, 22.7 and 1.5%, respectively, were among those childs who obtained inadequate calories, while the percentages of the forementioned malnutrition cases amon
... Show MoreObjectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
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designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee
Abstract : A descriptive study was conducted out patient in Neuralgic Hospital and Teaching Baghdad Teaching Hospital from 1st July / 2004 through October 1st / 2004 . in order to assess with QOL for CVA patients , the study aimed to identifying the QOL domain of ( physical , psychological , level of independence , social and environment ) and it relation with some demographic characteristic which is related to those patients .A purposive sample of ( 50 ) CVA patients who selected from out patient clinic of hospitals . A development questionnaire was structured and is adopted of WHO quality of life qu
Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
... Show MoreIt is believed that Organizations around the world should be prepared for the transition to IPv6 and make sure they have the " know how" to be able to succeed in choosing the right migration to start time. This paper focuses on the transition to IPv6 mechanisms. Also, this paper proposes and tests a deployment of IPv6 prototype within the intranet of the University of Baghdad (BUniv) using virtualization software. Also, it deals with security issues, improvements and extensions of IPv6 network using firewalls, Virtual Private Network ( VPN), Access list ( ACLs). Finally, the performance of the obtainable intrusion detection model is assessed and compared with three approaches.
Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c
... Show MoreThe present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w
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