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Deterioration Model for Sewer Network Asset Management in Baghdad City (case study Zeppelin line)
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Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques were used based on statistical methods such as discriminant, and artificial neural network (ANN) which were used to build the deterioration models. The results of the discriminant model gave correct classification of 68.9% for the condition class of this line. The main significant influencing variables that play an important role in sewer networks were: sewer age, planning, performance and maintenance which is known as the Management function. From ANN model the confusion matrix gave correct classification of 76.7% and MSE 0.128.This study providing a good source of information for future planning.

   

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Publication Date
Fri Mar 01 2013
Journal Name
Applied Mechanics And Materials
Measure and Analyze the Problems of Concrete Mixture Production via Six Sigma DMAIC Tools: Central Concrete Mix Plant as a Case Study
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The aims of this study are to measure the defect rate and analyze the problems of production of ready concrete mixture plant by using Six Sigma methodology which is a business strategy for operations improvement depending basically on the application of its sub-methodology DMAIC improvement cycle and the basic statistical tools where the process sigma level of concrete production in the case study was 2.41 σ.

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Role of SMEs in Economic Development in Jordan: The Case of Al Hassan Industrial Estate
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This study aimed at highlighting the role of small and medium enterprises in bringing about economic development in Jordan. The study examined the impact of the number, size of investment and the number of jobs provided by these enterprises on the rate of growth in gross domestic product (GDP) as an indicator for economic development. To achieve its objectives, the study adopted descriptive and quantitative analysis. A linear multi regression model was developed with a growth rate of GDP as dependent variable and the number of institutions, size of investment, and the number of job opportunities as independent variables. The study concluded that each increase by one small or medium enterprise lead to an increase in the rate of gr

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Publication Date
Wed Feb 27 2019
Journal Name
Journal Of Nano Research
A Specific NH<sub>3</sub> Gas Sensor of a Thick MWCNTs-OH Network for Detection at Room Temperature
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NH3 gas sensor was fabricated based on deposited of Functionalized Multi-Walled Carbon Nanotubes (MWCNTs-OH) suspension on filter paper substrates using suspension filtration method. The structural, morphological and optical properties of the MWCNTs film were characterized by XRD, AFM and FTIR techniques. XRD measurement confirmed that the structure of MWCNTs is not affected by the preparation method. The AFM images reflected highly ordered network in the form of a mat. The functional groups and types of bonding have appeared in the FTIR spectra. The fingerprint (C-C stretch) of MWCNTs appears in 1365 cm-1, and the backbone of CNTs observed at 1645 cm-1. A homemade sensi

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology & Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Tue Feb 01 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Finger Vein Recognition Based on PCA and Fusion Convolutional Neural Network
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Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network

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Publication Date
Tue Jan 01 2013
Journal Name
Communications And Network
Link and Cost Optimization of FTTH Network Implementation through GPON Technology
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Sat May 16 2009
Journal Name
Journal Of Planner And Development
Quantitative analysis of the economic characteristics of the land transport network
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Highway network could be considered as a function of the developmental level of the region, that it is representing the sensitive nerve of the economic activity and the corner stone for the implementation of development plans and developing the spatial structure. The main theme of this thesis is to show the characteristics of the regional highway network of Anbar and to determine the most important effective spatial characteristics and the dimension of that effect negatively or positively. Further this thesis tries to draw an imagination for the connection between highway network as a spatial phenomenon and the surrounded natural and human variables within the spatial structure of the region. This thesis aiming also to determine the natu

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Publication Date
Tue Dec 31 2024
Journal Name
Journal Of Emergency Medicine, Trauma And Acute Care
Histological variety analysis for pleomorphic adenoma in salivary glands: Retrospective study
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Pleomorphic adenoma (PA) is the most frequent benign epithelial neoplasm of salivary glands, displaying a remarkable degree of morphological variety. The aim of the study is to illustrate the clinicopathological characteristics of PA with particular emphases on epithelial cell morphology and mesenchymal elements. Materials and Methods: A total of 132 PA collected between 2002 and 2017 were recruited from Al Shahid Ghazi Al Hariri Hospital and the Department of Oral Pathology, College of Dentistry, Baghdad University, Baghdad, Iraq, and analyzed for their demographic and histopathological features. All data were analyzed using descriptive statistics. A slightly higher incidence of PA was detected in females (52.3%) compared to male subject

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