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Improved Weighted 0-1 Knapsack Method (WKM) to Optimize Resource Allocation
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In this paper an improved weighted 0-1 knapsack method (WKM) is proposed to optimize the resource allocation process when the sum of items' weight exceeds the knapsack total capacity .The improved method depends on a modified weight for each item to ensure the allocation of the required resources for all the involved items. The results of the improved WKM are compared to the traditional 0-1 Knapsack Problem (KP). The proposed method dominates on the other one in term of the total optimal solution value of the knapsack .

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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Composition operator induced by ?(z) = sz + t for which |s|?1, |t|<1 and |s|+|t|?1
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We study in this paper the composition operator that is induced by ?(z) = sz + t. We give a characterization of the adjoint of composiotion operators generated by self-maps of the unit ball of form ?(z) = sz + t for which |s|?1, |t|<1 and |s|+|t|?1. In fact we prove that the adjoint is a product of toeplitz operators and composition operator. Also, we have studied the compactness of C? and give some other partial results.

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the empirical bayes method with moments method to estimate the affiliation parameter in the clinical trials using simulation
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In this research the Empirical Bayes method is used to Estimate the affiliation parameter in the clinical trials and then we compare this with the Moment Estimates for this parameter using Monte Carlo stimulation , we assumed that the distribution of the observation is binomial distribution while the distribution with the unknown random parameters is beta distribution ,finally we conclude that the Empirical bayes method for the random affiliation parameter is efficient using Mean Squares Error (MSE) and for different Sample size .

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function
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This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

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Publication Date
Sat Nov 28 2020
Journal Name
Iraqi Journal Of Science
Non Bayesian estimation for survival and hazard function of weighted Rayleigh distribution (b)
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In this paper, we proposed a new class of Weighted Rayleigh Distribution based on two parameters, one is scale parameter and the other is shape parameter which introduced in Rayleigh distribution. The main properties of this class are derived and investigated in . The moment method and maximum likelihood method are used to obtain estimators of parameters, survival function and hazard function. Real data sets are collected to investigate two methods which depend it in this study. A comparison was made between two methods of estimation.

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate AR(3) by Using Levinson-Durbin Recurrence & Weighted Least Squares Error Methods
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In this study, we investigate about the estimation improvement for Autoregressive model of the third order, by using Levinson-Durbin Recurrence (LDR) and Weighted Least Squares Error ( WLSE ).By generating time series from AR(3) model when the error term for AR(3) is normally and Non normally distributed and when the error term has ARCH(q) model with order q=1,2.We used different samples sizes and the results are obtained by using simulation. In general, we concluded that the estimation improvement for Autoregressive model for both estimation methods (LDR&WLSE), would be by increasing sample size, for all distributions which are considered for the error term , except the lognormal distribution. Also we see that the estimation improve

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Bayesian Estimation for Two Parameters of Weibull Distribution under Generalized Weighted Loss Function
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In this paper, Bayes estimators for the shape and scale parameters of Weibull distribution have been obtained using the generalized weighted loss function, based on Exponential priors. Lindley’s approximation has been used effectively in Bayesian estimation. Based on theMonte Carlo simulation method, those estimators are compared depending on the mean squared errors (MSE’s).

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Publication Date
Sun May 26 2019
Journal Name
Iraqi Journal Of Science
Bayesian Estimation for Two Parameters of Gamma Distribution under Generalized Weighted Loss Function
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This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

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Scopus (6)
Crossref (4)
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Publication Date
Tue Sep 29 2020
Journal Name
Iraqi Journal Of Science
Applying the Shrinkage Technique for Estimating the Scale Parameter of Weighted Rayleigh Distribution
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This paper includes the estimation of the scale parameter of weighted Rayleigh distribution using well-known methods of estimation (classical and Bayesian). The proposed estimators were compared using Monte Carlo simulation based on mean squared error (MSE) criteria. Then, all the results of simulation and comparisons were demonstrated in tables. 

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Scopus (1)
Crossref (1)
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Publication Date
Tue Jan 25 2022
Journal Name
Iraqi Journal Of Science
Semi (1, 2)*-Maximal Soft (1, 2)*-Pre-Open Sets and Semi (1, 2)*-Minimal Soft (1, 2)*-Pre-Closed Sets In Soft Bitopological Spaces
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In this paper, we introduce and study new types of soft open sets and soft closed
sets in soft bitopological spaces (X,~ ,~ ,E) 1 2   , namely, (1,2)*-maximal soft open
sets, (1,2)*-maximal soft (1,2)*-pre-open sets, semi (1,2)*-maximal soft (1,2)*-preopen
sets, (1,2)*-maximal soft closed sets, (1,2)*-maximal soft (1,2)*-pre-closed
sets, (1,2)*-minimal soft open sets, (1,2)*-minimal soft (1,2)*-pre-open sets, (1,2)*-
minimal soft closed sets, (1,2)*-minimal soft (1,2)*-pre-closed sets, and semi (1,2)*-
minimal soft (1,2)*-pre-closed sets. Also, properties and the relation among these
concepts have been studied.

 

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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Synthesis and Characterization of 1, 3-Oxazepine and Benz [1, 2-e][1, 3] Oxazepine-4, 7-Diones
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N-Benzylidene m-nitrobenzeneamines (Schiff bases) were prepared by condensation of m-nitroaniline with aromatic aldehydes. These Schiff bases were found to react with maleic anhydride to give 2-Aryl-3-(m-nitrophenyl)-2, 3-dihydro [1, 3] oxazepine–4, 7–diones and with phthalic anhydride to give 2-Aryl-3–(m-nitrophenyl)–2, 3–dihydrobenz|| 1, 2-e|||| 1, 3] oxazepine–4, 7-diones which were reacted with pyrrolidine to give the anilide–pyrrolidides of maleic acid and phthalic acid.