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The Prospective of Artificial Neural Network (ANN’s) Model Application to Ameliorate Management of Post Disaster Engineering Projects
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Currently and under the COVID-19 which is considered as a kind of disaster or even any other natural or manmade disasters, this study was confirmed to be important especially when the society is proceeding to recover and reduce the risks of as possible as injuries. These disasters are leading somehow to paralyze the activities of society as what happened in the period of COVID-19, therefore, more efforts were to be focused for the management of disasters in different ways to reduce their risks such as working from distance or planning solutions digitally and send them to the source of control and hence how most countries overcame this stage of disaster (COVID-19) and collapse. Artificial intelligence should be used when there is no practical solution for a problem occurring in a projects starting from individual self-development ending to the adaptation to information technology sector with a continuous posting in this world of information industry where as metaphor “needs is a cause of creativity”. This study focuses on the use of artificial neural networks ANN to find a solution to issues in projects delays and furthermore when there is no physical or mathematical solution found so far. ANN’s were used to build a model that helps in finding a solution for delays in some selected projects in Baghdad (as case study), and discussing the strategies of rebuilding plus delays in time and cost due to delay factors. 35 construction projects were chosen in Baghdad greater area, vary in sizes and types. Crew and laborers were targeted in sampling collection methodology basically throughout questionnaire forms of field survey as they were filled by them. ANN’s helped in modelling delays factors to help decision makers in an appropriate management of projects. External factors which includes disasters mentioning COVID-19 as the most important disaster ever happened in the last decades, were the most important factor that caused delay in time and cost of projects implementation processes where this factor was controlling the other major factors such as contractor failure, redesigning, changing orders, security issues, low prices, besides weather issues and owner failure.

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Publication Date
Sat Jan 19 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
EVALUATION MANAGEMENT BROILER PRODUCTION PROJECTS AT BAGHDAD PROVINCE USING MANAGEMENT CRITERIA
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This research aims were to evaluate management of broiler production projects in Baghdad province via using the criteria of management, included production index and economic figure (PI and EF) that specified to those projects. in addition to criteria of economic efficiency also applied (INME) index number of management efficiency, in order to the research requirements, data were obtained based on a questionnaire prepared for this purpose, which was collected by personal interview of (60) projects of the broiler production projects from (516) projects representing 11.6% of the research community in Baghdad province  in 2016. The results show that mean of PI and EF was (338). The increase in these two criteria is generally due to co

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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Obstacles to the application of total quality management program in a number of iraqi service organizations
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The research aims to statement the main obstacles that prevent the application of total quality management (TQM) in a number of Iraqi service organizations, and by one organization in each of the sectors (health, finance, education, higher education, tourism), which are, (Al-Yarmouk Teaching Hospital, Rafidain Bank/ Branch of Hay Al-Arabi Al-Jadid, Al-Karkh/1 Directorate of Education, College of administration and Economics/ Baghdad University, International Palestine Hotel). The research also, tries to classify the priority of the obstacles depending on the type of service organization surveyed. And diagnoses the extent to which or the difference of the research sample members views on the order of obstacles of TQM, and also proposes a

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Publication Date
Sun Jan 01 2017
Journal Name
Dissertation/thesis
A Model To Evaluate the Online Training for Global Virtual Teams in Global Software Projects
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Publication Date
Tue Jun 18 2024
Journal Name
2023 Asee Annual Conference & Exposition Proceedings
Study of Artificial Intelligence Computing Devices for Undergraduate Computer Science and Engineering Labs
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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Clinical And Experimental Dentistry
Resistance of bonded premolars to four artificial ageing models post enamel conditioning with a novel calcium-phosphate paste
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Background: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Estimation and Improvement of Routing Protocol Mobile Ad-Hoc Network Using Fuzzy Neural Network
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Ad-Hoc Networks are a generation of networks that are truly wireless, and can be easily constructed without any operator. There are protocols for management of these networks, in which the effectiveness and the important elements in these networks are the Quality of Service (QoS). In this work the evaluation of QoS performance of MANETs is done by comparing the results of using AODV, DSR, OLSR and TORA routing protocols using the Op-Net Modeler, then conduct an extensive set of performance experiments for these protocols with a wide variety of settings. The results show that the best protocol depends on QoS using two types of applications (+ve and –ve QoS in the FIS evaluation). QoS of the protocol varies from one prot

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Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
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Scopus (12)
Crossref (7)
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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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