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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
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimal Indicators to Select the Engineering Consultancy Office For Higher Education Institutions in Iraq
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Expansion the engineering consultancy offices in the universities of Iraq, about (14) offices, leading to increas the competition between them, especially after the great trends of Iraqi government agencies to use the academic experiences and their efficiencies in general, due to non-existence of the engineering qualification in the government institutions to do the engineering designs ,supervision of projects and other engineering works which are practicing by the engineering consultancy offices in order to get the best performance of the work.Within this serious competition, needing a specific approach to enable government agencies to choose the optimal and alternative consultancy office to meet specific project and not rely on cronyis

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Publication Date
Wed Oct 17 2018
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
ESTIMATION OF MUNICIPAL SOLID WASTE GENERATION AND LANDFILL VOLUME GENERATION AND LANDFILL VOLUME USING ARTIFICIAL NEURAL NETWORKS
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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
PATTERN OF INVESTMENT PROJECTS IN THE INVESTMENT ENVIRONMENT: PATTERN OF INVESTMENT PROJECTS IN THE INVESTMENT ENVIRONMENT
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That the building of the national economy depends on the extent of the possibility of transition from the rent economy seeking to increase GDP (GDP1), and the tendency to manage projects with external sources of funding, or allow projects with foreign capital is a necessity. The strategic challenges faced by the economy in countries that have experience in investment projects have faced several factors internal and external for a period of time and not a few and the pressures and difficulties and failures have affected in one way or another on the development work in that country. On this basis, the stakeholders have a role to pay attention to the issue of the feasibility of the pattern of foreign investment in the investment environment

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Publication Date
Thu Jun 01 2023
Journal Name
Journal Of Engineering
Automatic Spike Neural Technique for Slicing Bandwidth Estimated Virtual Buffer-Size in Network Environment
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The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modifie

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Mon Jul 15 2024
Journal Name
2024 46th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Automatic COVID-19 Detection from Chest X-ray using Deep MobileNet Convolutional Neural Network
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Publication Date
Thu Oct 30 2025
Journal Name
Iraqi Journal Of Science
Postmortem Panoramic Dental Radiography: Human Identification Based on Convolution Neural Network and Contourlet Transform
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Human identification is crucial in forensics for the investigation of large-scale disasters such as fires, epidemics, earthquakes, and tsunamis. Even though biometric identification using panoramic dental radiography (PDR) has been the subject of several studies in the literature, further study remains a necessary and challenging issue. In this research, a human identification system was developed based on a convolutional neural network (CNN) and contour transform (CT). The proposed system was implemented on a total of 1540 PDR from 302 individuals. The preprocessing applied to PDRs for enhancing and taking the Region of Interest (ROI). The features were extracted using CT transform. These features were fused with features extracted

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering & Science (iconmeas 2019)
New application of pervaporation to enhance the conversion of consecutive reaction
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This study investigates consecutive reaction assisted by pervaporation for the first time. It studies the saponification of diethyladipate DA with sodium hydroxide NaOH solution synchronous with separating ethanol from the reaction mixture through an aqueous – organic membrane. The effect of time on some variables such as: permeated ethanol concentration EtOH wt%, separation factor (α), concentration of NaOH solution CB in the reaction medium and the conversion of DA to monoethyladipate (the intermediate product) was studied. It was shown that EtOH wt% and the conversion increased with increasing time unlike CB but (α) showed the existence of maximum value during the time of experiment. The process of reaction assisted by pervaporation

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
A Modified Approach by Using Prediction to Build a Best Threshold in ARX Model with Practical Application
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

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