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jeasiq-2351
Semi parametric Estimators for Quantile Model via LASSO and SCAD with Missing Data
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In this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
A Security and Privacy Aware Computing Approach on Data Sharing in Cloud Environment
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Today, the role of cloud computing in our day-to-day lives is very prominent. The cloud computing paradigm makes it possible to provide demand-based resources. Cloud computing has changed the way that organizations manage resources due to their robustness, low cost, and pervasive nature. Data security is usually realized using different methods such as encryption. However, the privacy of data is another important challenge that should be considered when transporting, storing, and analyzing data in the public cloud. In this paper, a new method is proposed to track malicious users who use their private key to decrypt data in a system, share it with others and cause system information leakage. Security policies are also considered to be int

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of big data analytics in measuring and analyzing the quality costs of economic units : applied research in the Iraqi company for seed production
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                The research aims to explain the role of huge data analyzes in measuring quality costs in the Iraqi company for the production of seed, and the research problem was diagnosed with the weakness of the approved method to measure quality costs, and the weak traditional systems of data analyzes, the researcher in the theoretical aspect relied on collecting sources and previous studies, as well as Adoption of the applied analytical approach in the practical aspect, as a set of financial analyzes were applied within the measurement of quality costs and a statement of the role of data analyzes in the practical side, the research concluded to a set of conc

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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

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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
Sun Oct 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy aggregate production planning by using fuzzy Goal programming with practical application
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Research summarized in applying the model  of fuzzy goal programming for aggregate production planning , in General Company for hydraulic industries / plastic factory to get an optimal production plan  trying to cope with the impact that fluctuations in demand and  employs all available resources using two strategies where they are available   inventories  strategy and  the strategy of  change in the level of the workforce, these   strategies  costs are usually imprecise/fuzzy. The plant administration trying to minimize total production costs, minimize carrying costs and minimize changes in labour levels. depending on the gained data from th

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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
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 p

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Publication Date
Thu Jun 02 2011
Journal Name
Ibn Al-haithem Journal For Pure And Applied Sciences
On modified pr-test double stage shrinkage estimators for estimate the parameters of simple linear regression model
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Publication Date
Mon Dec 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology (jatit)
Factors and Model for Sensitive Data Management and Protection in Information Systems’ Decision of Cloud Environment
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Journal of Theoretical and Applied Information Technology is a peer-reviewed electronic research papers & review papers journal with aim of promoting and publishing original high quality research dealing with theoretical and scientific aspects in all disciplines of IT (Informaiton Technology

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Publication Date
Sat Sep 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Efficient S.brunken Estimators For The Mean Of Normal Population With Kuown Variance
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This  article  co;nsiders a shrunken  estimator  Â·Of  Al-Hermyari·   and

AI Gobuii (.1) to estimate  the mean (8) of a normal clistributicm N (8 cr4)  with  known variance  (cr+),  when  <:I    guess value (So) av11il ble about the mean (B) as· an initial estrmate. This estimator is shown to be

more efficient tl1an the class-ical estimators  especially when 8 is close to 8•. General expressions .for bias and MSE -of considered  estitnator are gi 'en, witeh  some examples.  Nut.nerical cresdlts, comparisons  and

conclusions ate reported.

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