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Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
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Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to develop the model of multiple linear regression (MLR) with the stepwise regression technique in the SPSS v25 software. The results indicate that the model of trip generation is related to family size and composition, gender, students’ number in the family, workers’ number in the family, and car ownership. The ANN prediction model is more accurate than the MLR predicted model: the average accuracy (AA) was 83.72% in the ANN model but only 72.46% in the MLR model.</p>
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Publication Date
Sun Mar 01 2015
Journal Name
Sust Journal Of Engineering And Computer Science (jecs)
Virtual failure influence of Roseires dam on Khartoum city using HEC-RAS Hydraulic simulation modeling
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Dam break is series phenomenon that can result in fatal consequences and loss of properties. Unfortunately, the observed consequences can only be available after the dam breaks. Therefore, it is important to anticipate what will happen prior to dam break to issue suitable warning and locate the possible risk areas. This study attempts to simulate the case of dam break in Blue Nile at Roseires dam and see its consequences downstream. Roseires dam lies at a distance of 630 km south of Khartoum, Sennar dam lies at about 260 km downstream of Roseires dam. In this study hydraulic model is developed based of Hydraulic Engineering Centre (HEC), River Analysis System (RAS), and HEC- RAS. The HEC-RAS based model is calibrated and validated usi

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Physics: Conference Series
Using Spatial Analysis Methods to Evaluate the Soil Contamination of Baghdad City, Iraq
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Abstract<p>The current study aims to identify soil pollutants from heavy metals The study utilized 40 topsoil (5 cm) samples, which adapted and divided into seven regions lies in Baghdad governorate, included (Al-Husainya,(Hs) Al-Doura (Do), Sharie Al-Matar (SM), Al-Waziria (Wz), Nharawan (Nh), Abu Ghraib (Abu) and Al-Mahmoodyia (Mh)). Spatial distribution maps of Nickel (Ni), Manganese (Mn), Lead (Pb) and Zinc (Zn) were created for Baghdad city using Geographic Information Systems (GIS). The concentrations of four heavy metals in the soil of different area of Baghdad were measured and observed using XRF instrument. The result found highest values of Pb and Zn at the middle of the Baghdad in (Wz</p> ... Show More
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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Link Failure Recovery for a Large-Scale Video Surveillance System using a Software-Defined Network
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The software-defined network (SDN) is a new technology that separates the control plane from data plane for the network devices. One of the most significant issues in the video surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the video from the cameras. In this paper, two methods are proposed to solve this problem.  The first method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

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Publication Date
Tue Jan 01 2008
Journal Name
2008 15th Asia-pacific Software Engineering Conference
G2Way A Backtracking Strategy for Pairwise Test Data Generation
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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EXPOSURE TO TELEVISION PROMOTION OF PHARMACEUTICAL PRODUCTS AND TRENDS TOWARDS THEM / FIELD RESEARCH FOR A SAMPLE OF THE AUDIENCE IN THE CITY OF BAGHDAD: EXPOSURE TO TELEVISION PROMOTION OF PHARMACEUTICAL PRODUCTS AND TRENDS TOWARDS THEM / FIELD RESEARCH FOR A SAMPLE OF THE AUDIENCE IN THE CITY OF BAGHDAD
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A field study was conducted on a sample of the public in Baghdad to study the audience's exposure to the television promotion of pharmaceutical products and their trends in order to determine the rate of exposure of the public to the television promotion of pharmaceutical products according to the theory of uses and rumors and to determine the public's attitudes towards television promotion of pharmaceutical products. A survey of (25) a questions was distributed to a sample of the audience of 150 people. The statistical program SPSS was used to unload the data and for the calculation of frequencies and percentages and correlation coefficients. The research reached several results, Most importantly, the television promotion is well receiv

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Publication Date
Mon Jan 01 2024
Journal Name
Communications In Computer And Information Science
Automatic Identification of Ear Patterns Based on Convolutional Neural Network
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Biometrics represent the most practical method for swiftly and reliably verifying and identifying individuals based on their unique biological traits. This study addresses the increasing demand for dependable biometric identification systems by introducing an efficient approach to automatically recognize ear patterns using Convolutional Neural Networks (CNNs). Despite the widespread adoption of facial recognition technologies, the distinct features and consistency inherent in ear patterns provide a compelling alternative for biometric applications. Employing CNNs in our research automates the identification process, enhancing accuracy and adaptability across various ear shapes and orientations. The ear, being visible and easily captured in

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Measuring the concentration of uranium for adults teeth in adjacent areas of Tigris river in Baghdad city using nuclear track detector CR-39
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In this study, the fission track registration technique with the CR-39 detector are using to determination the uranium concentrations for seventeen samples of teeth distributed in four districts in Baghdad City .Five samples taken from both Al-Durra District and Al-Jadiriyia District, Four samples taken from Al-Karrda (Alaatar street) Taken four samples and three samples taken from Al-Zuafrania and by 0.5gm in weight and 1.5 mm in thickness. The uranium concentrations in teeth samples measured by using fission tracks registration in (CR-39) track detector that caused by the bombardment of (U) with thermal neutrons from (241 Am-Be) neutron source that has flux of (5 ×103 n cm-2 s-1). The concen

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Publication Date
Wed Aug 05 2015
Journal Name
International Journal Of Current Engineering And Technology
Water Quality Index Assessment using GIS Case study: Tigris River in Baghdad City
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In this study water quality index (WQI) was calculated to classify the flowing water in the Tigris River in Baghdad city. GIS was used to develop colored water quality maps indicating the classification of the river for drinking water purposes. Water quality parameters including: Turbidity, pH, Alkalinity, Total hardness, Calcium, Magnesium, Iron, Chloride, Sulfate, Nitrite, Nitrate, Ammonia, Orthophosphate and Total dissolved solids were used for WQI determination. These parameters were recorded at the intakes of the WTPs in Baghdad for the period 2004 to 2011. The results from the annual average WQI analysis classified the Tigris River very poor to polluted at the north of Baghdad (Alkarkh WTP) while it was very poor to very polluted in t

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