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State-of-the-Art in Data Integrity and Privacy-Preserving in Cloud Computing
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Cloud computing (CC) is a fast-growing technology that offers computers, networking, and storage services that can be accessed and used over the internet. Cloud services save users money because they are pay-per-use, and they save time because they are on-demand and elastic, a unique aspect of cloud computing. However, several security issues must be addressed before users store data in the cloud. Because the user will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.), and will not know where the data is stored, the user must ensure that the cloud stores and maintains the outsourced data appropriately. The study's primary goals are to make the cloud and data security challenges more understandable, to briefly explain the techniques used to achieve privacy and data integrity, to compare various recent studies in both pre-quantum and post-quantum, and to focus on current gaps in solving privacy and data integrity issues.

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Publication Date
Fri Jun 01 2007
Journal Name
Al-khwarizmi Engineering Journal
Correlation for fitting multicomponent vapor-liquid equilibria data and prediction of azeotropic behavior
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Correlation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.

            In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –

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Publication Date
Sun Jan 14 2024
Journal Name
Journal Of Al-rafidain University College For Sciences ( Print Issn: 1681-6870 ,online Issn: 2790-2293 )
Using Nonparametric Procedure to Develop an OCMT Estimator for Big Data Linear Regression Model with Application Chemical Pollution in the Tigris River
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Chemical pollution is a very important issue that people suffer from and it often affects the nature of health of society and the future of the health of future generations. Consequently, it must be considered in order to discover suitable models and find descriptions to predict the performance of it in the forthcoming years. Chemical pollution data in Iraq take a great scope and manifold sources and kinds, which brands it as Big Data that need to be studied using novel statistical methods. The research object on using Proposed Nonparametric Procedure NP Method to develop an (OCMT) test procedure to estimate parameters of linear regression model with large size of data (Big Data) which comprises many indicators associated with chemi

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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
Thu Nov 21 2019
Journal Name
Journal Of Engineering
Comparative Permeability Estimation Method and Identification of Rock Types using Cluster Analysis from Well Logs and Core Analysis Data in Tertiary Carbonate Reservoir-Khabaz Oil Field
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Characterization of the heterogonous reservoir is complex representation and evaluation of petrophysical properties and application of the relationships between porosity-permeability within the framework of hydraulic flow units is used to estimate permeability in un-cored wells. Techniques of flow unit or hydraulic flow unit (HFU) divided the reservoir into zones laterally and vertically which can be managed and control fluid flow within flow unit and considerably is entirely different with other flow units through reservoir. Each flow unit can be distinguished by applying the relationships of flow zone indicator (FZI) method. Supporting the relationship between porosity and permeability by using flow zone indictor is ca

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between the logistic regression model and Linear Discriminant analysis using Principal Component unemployment data for the province of Baghdad
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     The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.

     Was conducted to compare the two methods above and it became clear by comparing the  logistic regression model best of a Linear Discriminant  function written

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Crisis management according to the strategic leadership - the interactive role of decision support systems. (An exploratory study at the Ministry of Industry and Minerals / the State Company for Steel Industries)
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The researcher aims to Diagnose the reality of research variables, strategic leadership and decision support systems, and their impact on crisis management in the General Company for Steel Industries because of their important role in preventing crises and reducing their occurrence for the research company in particular and other companies in general affiliated with the Ministry of Industry and Minerals, as well as clarifying theoretical concepts of research variables As it included the answer to questions related to the research problem, including (Is there an impact of the strategic leadership in managing crises if decision support systems are used), and the researcher adopted the descriptive and analytical approach in its comp

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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardn</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Data And Network Science
The effects of big data, artificial intelligence, and business intelligence on e-learning and business performance: Evidence from Jordanian telecommunication firms
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This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Numerical Solution for Linear State Space Systems using Haar Wavelets Method
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In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

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