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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
Sun Sep 30 2018
Journal Name
Scientific Journal Of Silesian University Of Technology. Series Transport
Measuring the relative importance of applying engineering solutions to urban traffic intersections: a planning perspective
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the application of total quality management in Karkh Maternity Hospital from the perspective of health staff
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 Quality is the key to success in today's world, which is based mainly on competition in the provision of high quality services through the application of the modern management method which is called  total  quality management in organizations. This includes describing the provision of health services and satisfaction of patients .              .                                                 &nbsp

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Re-engineering management processes and its impact on the strategic decision-making process Field study on the College of Education / University of Mustansiriya / Iraq
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The aim of the research is to identify both the re-engineering of management processes and the strategic decision-making process in the research community and determine the nature of the correlation between the two variables and know the relationship between them to achieve the research goal. The researcher used a descriptive and analytical method. The research community consists of a group of professors and staff of the College of Education affiliated to the University of Mustansiriya in Baghdad, which their number were (45),  the researcher has distributed the forms to all members of the sample,  only (3) forms were excluded for invalidity and thus the number of forms approved in the analysis were (42) forms. The rese

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Publication Date
Sun Jan 01 2023
Journal Name
E3s Web Of Conferences
Comparing the Design Alternatives Using Building Information Model (BIM) and Constructability in Iraqi Construction Projects
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The Iraqi construction industry suffers from many issues that lead to many design errors, clashes, delays and cost overruns. Therefore, applying constructability will prevent these issues from happening, as it has proven its positive effect in different projects around the world. The goal of this paper is to use building information modelling (BIM) to assess the constructability, provide the opportunities for the project stakeholders to choose the best constructable design alternative and find the affection of applying constructability on project cost. The practical side of this research consists of two parts: in the first part, 37 factors are collected from the literature review as factors that effect on constructability. After tha

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Publication Date
Sat Jun 01 2024
Journal Name
Pakistan Journal Of Criminology
Artificial Intelligence Technology in the Field of Modern Forensic Evidence: Brain Fingerprinting as a Model
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Brain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining

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Publication Date
Thu Aug 01 2019
Journal Name
Transylvanian Review
POSSIBILITY OF APPLICATION THE BALANCED SCORECARD IN THE IRAQI INDUSTRIAL COMPANIES: A PROPOSED MODEL
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POSSIBILITY OF APPLICATION THE BALANCED SCORECARD IN THE IRAQI INDUSTRIAL COMPANIES: A PROPOSED MODEL

Publication Date
Fri Apr 22 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Developing models to predicting the effect of crises on construction projects using MLR technique
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Publication Date
Mon Apr 09 2018
Journal Name
Al-khwarizmi Engineering Journal
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

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