Preferred Language
Articles
/
gxeNapIBVTCNdQwCwK_L
Evaluating Roads Network Connectivity for Two Municipalities in Baghdad-Iraq
...Show More Authors

The road network serves as a hub for opportunities in production and consumption, resource extraction, and social cohabitation. In turn, this promotes a higher standard of living and the expansion of cities. This research explores the road network's spatial connectedness and its effects on travel and urban form in the Al-Kadhimiya and Al-Adhamiya municipalities. Satellite images and paper maps have been employed to extract information on the existing road network, including their kinds, conditions, density, and lengths. The spatial structure of the road network was then generated using the ArcGIS software environment. The road pattern connectivity was evaluated using graph theory indices. The study demands the abstraction and examination of the topological structure by choosing a few factors associated with the connection of the roads. These involved the cyclomatic number, Eta coefficient, Aggregate Transform Score (ATS), Beta, gamma, and Alpha indices. According to the findings, the Al-Adhamiya roads network is more developed, better linked, and has a higher overall connectivity value than the Al-Kadhimiya network. The two study areas, however, have minimal circuitry and high complexity. Due to the modifications and expansion of land use that the municipalities have seen, the research suggests that the transportation network should be developed to reach greater interconnectedness, particularly in locations outside the city center.

Scopus Crossref
Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Software Defined Network of Video Surveillance System Based on Enhanced Routing Algorithms
...Show More Authors

Software Defined Network (SDN) is a new technology that separate the ‎control plane from the data plane. SDN provides a choice in automation and ‎programmability faster than traditional network. It supports the ‎Quality of Service (QoS) for video surveillance application. One of most ‎significant issues in video surveillance is how to find the best path for routing the packets ‎between the source (IP cameras) and destination (monitoring center). The ‎video surveillance system requires fast transmission and reliable delivery ‎and high QoS. To improve the QoS and to achieve the optimal path, the ‎SDN architecture is used in this paper. In addition, different routing algorithms are ‎used with different steps. First, we eva

... Show More
View Publication Preview PDF
Scopus (6)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
...Show More Authors

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
...Show More Authors

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sat Dec 14 2019
Journal Name
International Journal On Emerging Technologies
Utilizing an Artificial Neural Network Model to Predict Bearing Capacity of Stone Columns
...Show More Authors

ABSTRACT: Ultimate bearing capacity of soft ground reinforced with stone column was recently predicted using various artificial intelligence technologies such as artificial neural network because of all the advantages that they can offer in minimizing time, effort and cost. As well as, most of applied theories or predicted formulas deduced analytically from previous studies were feasible only for a particular testing environment and do not match other field or laboratory datasets. However, the performance of such techniques depends largely on input parameters that really affect the target output and missing of any parameter can lead to inaccurate results and give a false indicator. In the current study, data were collected from previous rel

... Show More
View Publication
Scopus (4)
Scopus
Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
...Show More Authors

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
...Show More Authors

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

... Show More
View Publication Preview PDF
Scopus (7)
Crossref (5)
Scopus Crossref
Publication Date
Sun Mar 08 2015
Journal Name
All Days
Distribution of New Horizontal Wells by the Use of Artificial Neural Network Algorithm
...Show More Authors
Abstract<p>It is an established fact that substantial amounts of oil usually remain in a reservoir after primary and secondary processes. Therefore; there is an ongoing effort to sweep that remaining oil. Field optimization includes many techniques. Horizontal wells are one of the most motivating factors for field optimization. The selection of new horizontal wells must be accompanied with the right selection of the well locations. However, modeling horizontal well locations by a trial and error method is a time consuming method. Therefore; a method of Artificial Neural Network (ANN) has been employed which helps to predict the optimum performance via proposed new wells locations by incorporatin</p> ... Show More
View Publication
Scopus (4)
Scopus Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Desalination And Water Treatment
Combination of the artificial neural network and advection-dispersion equation for modeling of methylene blue dye removal from aqueous solution using olive stones as reactive bed
...Show More Authors

Scopus (16)
Crossref (15)
Scopus Clarivate Crossref
Publication Date
Wed Oct 02 2024
Journal Name
International Development Planning Review
EVALUATING THE EFFECTIVE CREATIVE LEADERSHIP ROLE OF THE DEAN AND HEADS OF SCIENTIFIC DEPARTMENTS IN THE COLLEGE OF PHYSICAL EDUCATION AND SPORTS SCIENCES AL-MUSTANSIRIYAUNIVERSITY
...Show More Authors

Publication Date
Wed Oct 02 2024
Journal Name
International Development Planning Review
EVALUATING THE EFFECTIVE CREATIVE LEADERSHIP ROLE OF THE DEAN AND HEADS OF SCIENTIFIC DEPARTMENTS IN THE COLLEGE OF PHYSICAL EDUCATION AND SPORTS SCIENCES AL-MUSTANSIRIYAUNIVERSITY
...Show More Authors