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Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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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 (26.24%), and (5.5%), and AA was (74%), and (94.5%), for cost and time model, respectively. The researcher concluded that the ANN model has a strong correlation and high accuracy, indicating that these models are characterized by high efficiency and good performance in predicting cost and time.

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Publication Date
Mon Mar 30 2026
Journal Name
Iraqi Journal Of Science
A modified time series model using conditional and unconditional estimations with applications to a real dataset
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Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
The Impact of Transfer Learning and Pre-trained Models on Model Performance
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Global Pharma Technology
Analytical Study for the Ability of Some Polymers to Gain Transitional Elements Ionsions in Different Temperature, PH Acidity Functional and Time Situations
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The compound [K1] was synthesized from the reaction of dichloromethane with linear alkyl benzene (Lab9) using ethanol as a solvent, and from(chloro methyl)-4-nonylbenzene) [K1] it was possible to synthesize the compound Z(4-(nonan-3-yl)phenyl) methane amine) [K2] containing the amine group by synthesized from [K2] reaction with appropriate phenolic aldehydes and using Ethanol as a solvent in the preparation of vinyl chloride4-(((4-nonylbenzyl)imino)methyl)phenol-4-(((4-nonylbenzyl)imino methyl)benzene-1,3diol) [K3-K4] bases has been used. Preparation of a number of Phenolic polymers4-(2- hydroxy-3.5-dimethylbenzyl)-2-methyl-6-(((4-4-(2hyroxy-3, 5-dimethylbenzyl)-2-methyl-6(((4 nonylbenzyl) imino) methyl) benzene-phenolnonylbenzyl) imino) me

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Publication Date
Fri Dec 29 2017
Journal Name
Al-khwarizmi Engineering Journal
Design and Implementation of a Proposal Network Firewall
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In today's world, most business, regardless of size, believe that access to Internet is imperative if they are going to complete effectively. Yet connecting a private computer (or a network) to the Internet can expose critical or confidential data to malicious attack from anywhere in the world since unprotected connections to the Internet (or any network topology) leaves the user computer vulnerable to hacker attacks and other Internet threats. Therefore, to provide high degree of protection to the network and network's user, Firewall need to be used.

Firewall provides a barrier between the user computer and the Internet (i.e. it prevents unauthor

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Mon Oct 31 2022
Journal Name
Journal Of Sustainability Science And Management
THE MEDIATING ROLE OF SUSTAINABLE DEVELOPMENT IN THE RELATIONSHIP BETWEEN PRODUCER COST EXPECTATIONS AND CUSTOMER DESIRES
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In this paper, customers’ expectations are continually shifting due to the business environment’s growing competition and substantial changes. As a result, organisations no longer viewed it as a static objective but as an ever-evolving aim. From this vantage point, the research has explored the accounting literature in search of novel approaches to addressing the strategic dimensions of quality, cost and time. Getting them to respond positively to the customer’s requests also requires recognising their needs and controlling their impact on these dimensions. With the removal of operations that do not contribute any value to the product’s value chain and a reduction in manufacturing costs through continuous improvement, the ou

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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
The role of business incubators in supporting and developing the international competitiveness of small projects in Iraq
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

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Publication Date
Sat Mar 26 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The theory of convergent between standard and optimal cost supporting actual cost in an Enterprise: بحث تطبيقي في معمل الألبسة الرجالية في النجف للفترة من 2007-2020
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The research aims to achieve proof of convergence between optimal costs and standard costs in calculating costs for the economic unit, support efforts aimed at adopting optimal costs in cost accounts and accounting thought in general, and achieve benefit from the theory of convergence between optimal costs and standard costs in the field of achieving actual costs in The economic unit in order to reduce and converge, and this came to address the possibility of adopting the concept of optimal costs in the production costs calculations for the purposes of rationalizing administrative decisions, and rationalizing the preparation of financial statements within management accounting.

The research concluded that

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Publication Date
Fri Jan 01 2021
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Electrochemical harvesting of microalgae꞉ Parametric and cost-effectivity comparative investigation
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The cost of microalgae harvesting constitutes a heavy burden on the commercialization of biofuel production. The present study addressed this problem through economic and parametric comparison of electrochemical harvesting using a sacrificial electrode (aluminum) and a nonsacrificial electrode (graphite). The harvesting efficiency, power consumption, and operation cost were collected as objective variables as a function of applied current and initial pH of the solution. The results indicated that high harvesting efficiency obtained by using aluminum anode is achieved in short electrolysis time. That harvesting efficiency can be enhanced by increasing the applied current or the electrolysis time for both electrode materials, where 98

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