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The Factors Affecting on Managing Sensitive Data in Cloud Computing
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Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of proposed framework, a pilot study by using a structured questionnaire was conducted. Framework using multilevel to enhance management information system on sensitive data in cloud environment.

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Publication Date
Wed Mar 12 2025
Journal Name
The Alarba'een Journal
Analyzing and tracking the data of the millions sized gatherings for the Arba'in visit and proposing alternative ways to relieve congestion using spatial analysis algorithms
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The city of Karbala is one of the most important holy places for visitors and pilgrims from the Islamic faith, especially through the Arabian visit, when crowds of millions gather to commemorate the martyrdom of Imam Hussein. Offering services and medical treatments during this time is very important, especially when the crowds head to their destination (the holy shrine of Imam Hussein (a.s)). In recent years, the Arba'in visit has witnessed an obvious growth in the number of participants. The biggest challenge is the health risks, and the preventive measures for both organizers and visitors. Researchers identified various challenges and factors to facilitating the Arba'in visit. The purpose of this research is to deal with the religious an

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Publication Date
Mon Jan 01 2018
Journal Name
Biochem. Cell. Arch.
Studying of different factors affected in production of amylase enzyme from a local isolate of B. Subtillis A4 bacteria
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The present study aims to detection optimal conditions of production of amylase enzyme from isolate of B. subtillis A4. Nine carbonic sources were represented by starch, maltose, fructose, sucrose, glucose, arabinose, xylose, sorbitol and mannitol) at concentration of 1% for each source. It was found that the best was represented by starch carbonic, which showed higher activity and qualitative activity of 7.647 Unit/ ml and 461.56 Unit/ mg. Ten nitrogen sources were selected, including yeast extract, peptone, trypton, gelatin, urea and meat extract as organic sources Ammonium sulphate, Sodium nitrate, Potassium nitrate and Ammonium chloride as inorganic sources. These sources were added at aconcentration of 0.5% to the production medium. Th

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Publication Date
Wed Apr 01 2020
Journal Name
Iraqi Journal Of Agricultural Sciences
Study of different factors effected in production of dextranase enzyme from a local isolate of b. Subtilis Z2 bacteria
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Publication Date
Thu Jun 11 2020
Journal Name
American Journal Of Infectious Diseases
Prevalence of Urinary Tract Infections and Associated Risk Factors Among Patients Attending Medical City Hospital in Baghdad City, Iraq
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Abstract: Urinary Tract Infections (UTIs) are the most common bacterial infection in humans and a major cause of morbidity and they are the most common cause of hospital visits worldwide. Proper knowledge in identifying factors associated with urinary tract infection may allow the intervention to easily control of the disease in a timely manner. Therefore, the purpose of the study is determining the prevalence of UTI, diagnosis of causative bacterial agents and identifying the factors associated to the urinary tract infection among patients attending Medical City Hospital in Baghdad, Iraq. A total of 237, morning mid-stream urine samples were collected aseptically and the samples were diagnosed according to the standard methods. I

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Publication Date
Thu Oct 25 2018
Journal Name
Al-kindy College Medical Journal
Prevalence and risk factors for hepatitis C virus in Beta thalassemic patients attending blood diseases center in Ibn- AL -Baladi Hospital, Baghdad
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Background: Thalassemias are a group of heterogeneous genetic disorders, in which the rate of production of hemoglobin is partially or completely suppressed due to reduced rate of synthesis of α or β- chain

Objectives: to estimate the prevalence of Hepatitis C infection among B thalassemia patients attending Ibn-AL-Baladi center of blood diseases in AL-Sader city, in AL-Resafa Quarter of Baghdad and to determine the possible risk factors.

Type of the study: Cross- sectional study.

Methods: A cross sectional study conducted on B Thalassemia patients attending the blood diseases center in Ibn-AL-Baladi hospital during the period from 1st

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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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
Tue Jan 01 2019
Journal Name
Journal Of Southwest Jiaotong University
Recognizing Job Apathy Patterns of Iraqi Higher Education Employees Using Data Mining Techniques
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Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from

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Publication Date
Wed Jan 01 2020
Journal Name
Advances In Science, Technology And Engineering Systems Journal
Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
Analytical Approach for Load Capacity of Large Diameter Bored Piles Using Field Data
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An analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.

               Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95

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