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Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources
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Publication Date
Sun Mar 01 2015
Journal Name
Journal Of Engineering
Multi-Sites Multi-Variables Forecasting Model for Hydrological Data using Genetic Algorithm Modeling
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A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

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Publication Date
Wed Jun 28 2023
Journal Name
Internet Technology Letters,
The Blockchain for Healthcare 4.0 Apply in Standard Secure Medical Data Processing Architecture
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Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Contemporary Challenges for Cloud Computing Data Governance in Information Centers: An analytical study
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Purpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Geological Journal
Evaluating Machine Learning Techniques for Carbonate Formation Permeability Prediction Using Well Log Data
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Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

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Publication Date
Wed Jul 01 2020
Journal Name
Proceedings Of The Institution Of Mechanical Engineers, Part H: Journal Of Engineering In Medicine
Comparison study of classification methods of intramuscular electromyography data for non-human primate model of traumatic spinal cord injury
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Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental

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Publication Date
Tue Nov 09 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of integration between the earned value management model and the value flow map in rationalizing the costs of construction projects: applied research in Al-Rasheed General Company for Construction Contracting
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The research problem is that most of the construction projects exceed the planned value, due to the failure to implement the plans on time. The current study aims to monitor the implementation of the project and for each of the executed tasks of the table of quantities in order to detect deviations at the time they occur, evaluate the time and cost performance, and then identify the areas of waste and analyze the implementation of each task in order to diagnose the underlying problems and find possible and applicable solutions in the environment Iraqi. The research was applied in one of the companies specialized in the field of construction projects, and one of the most important conclusions reached is the possibility of applying

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Impact of the Strategy of Cooperative Integration of Fragmented Information in the Acquisition of Physical Concepts and Science Processes among Fourth Scientific Students
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The current research aims to reveal the impact of the strategy of cooperative integration of fragmented information in the acquisition of physical concepts and science processes among fourth scientific students through the null hypotheses:

1- There is no statistically significant difference at the level of significance (0.05) between the average grades of female students of the experimental group studying physics according to the strategy of cooperative integration of fragmented information and those who follow the traditional method in the test of acquiring physical concepts.

2-There is no statistically significant difference at the level of indication (0.05) between the average grades of female students of the experimen

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Publication Date
Wed Sep 20 2023
Journal Name
Environmental Progress & Sustainable Energy
Production and characterization of composite activated carbon from potato peel waste for cyanide removal from aqueous solution
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Abstract<p>This research presents a response surface methodology (RSM) with I‐optimal method of DESIGN EXPERT (version 13 Stat‐Ease) for optimization and analysis of the adsorption process of the cyanide from aqueous solution by activated carbon (AC) and composite activated carbon (CuO/AC) produced by pyro carbonic acid microwave using potato peel waste as raw material. Pyrophosphate 60% (wt) was used for impregnation with an impregnation ratio 3:1, impregnation time of 4 h at 25°C, radiant power of 700 W, and activation time of 20 min. Batch experiments were conducted to determine the removal efficiency of cyanide from aqueous solution to evaluate the influences of various experimental parameters su</p> ... Show More
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of estimations methods of the entropy function to the random coefficients for two models: the general regression and swamy of the panel data
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In this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.

The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Assessing liquidity to improve bank’s profitability : An applied research - in a number of – Iraqi private banks
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The current research aims to evaluate liquidity (as an independent variable) to improve the bank’s profitability (as a dependent variable ), by the bank’s ability to maximize its profits from its business results without excessive bank’s  liquidity, so that may affect negatively affects the bank’s reputation and it’s dealers confidence in facing their financial obligations. and this may lead trying to come out among other recommendations including contributing to obtain, the bank’s ability to achieve liquidity balance to maximize its profits. This research has been applied to the sample induced intentionally by choosing three Iraqi private banks. The researcher used financial indicators to assess the bank’s liq

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