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jih-2972
Estimation of a Parallel Stress-strength Model Based on the Inverse Kumaraswamy Distribution
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 The reliability of the stress-strength model attracted many statisticians for several years owing to its applicability in different and diverse parts such as engineering, quality control, and economics. In this paper, the system reliability estimation in the stress-strength model containing Kth parallel components will be offered by four types of shrinkage methods: constant Shrinkage Estimation Method, Shrinkage Function Estimator, Modified Thompson Type Shrinkage Estimator, Squared Shrinkage Estimator. The Monte Carlo simulation study is compared among proposed estimators using the mean squared error. The result analyses of the shrinkage estimation methods showed that the shrinkage functions estimator was the best since it has a minor mean squared error than the other methods followed by the additional shrinkage estimator. The stress and strength belong to the In


verse Kumaraswamy distribution

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Publication Date
Fri Dec 30 2022
Journal Name
Journal Of Mathematics
Estimation of Parameters of Finite Mixture of Rayleigh Distribution by the Expectation-Maximization Algorithm
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In the lifetime process in some systems, most data cannot belong to one single population. In fact, it can represent several subpopulations. In such a case, the known distribution cannot be used to model data. Instead, a mixture of distribution is used to modulate the data and classify them into several subgroups. The mixture of Rayleigh distribution is best to be used with the lifetime process. This paper aims to infer model parameters by the expectation-maximization (EM) algorithm through the maximum likelihood function. The technique is applied to simulated data by following several scenarios. The accuracy of estimation has been examined by the average mean square error (AMSE) and the average classification success rate (ACSR). T

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Publication Date
Tue Nov 01 2022
Journal Name
Aci Structural Journal
Stress at Ultimate in Internally Unbonded Steel Based on Genetic Expression Programming
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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Smartphone -Based Model for Human Activity Recognition
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Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif

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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
Tue Feb 13 2024
Journal Name
Iraqi Journal Of Science
Suggested method of Estimation for the Two Parameters of Weibull Distribution Using Simulation Technique
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In this paper, suggested method as well as the conventional methods (probability
plot-(p.p.) for estimations of the two-parameters (shape and scale) of the Weibull
distribution had proposed and the estimators had been implemented for different
sample sizes small, medium, and large of size 20, 50, and 100 respectively by
simulation technique. The comparisons were carried out between different methods
and sample sizes. It was observed from the results that suggested method which
were performed for the first time (as far as we know), by using MSE indicator, the
comparisons between the studied and suggested methods can be summarized
through extremely asymptotic for indicator (MSE) results by generating random
error

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Estimation of Survival and Hazard Rate Functions of Exponential Rayleigh Distribution
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In this paper, we used the maximum likelihood estimation method to find the estimation values ​​for survival and hazard rate functions of the Exponential Rayleigh distribution based on a sample of the real data for lung cancer and stomach cancer obtained from the Iraqi Ministry of Health and Environment, Department of Medical City, Tumor Teaching Hospital, depending on patients' diagnosis records and number of days the patient remains in the hospital until his death.

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Publication Date
Fri Jan 26 2024
Journal Name
Iraqi Journal Of Science
Monthly Carbone Monoxide (CO) Distribution Based on the 2010 MOPITT Satellite Data in Iraq
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Carbon monoxide (CO) plays an important indirect greenhouse gases due to its influences on the budgets of hydroxyl radicals (OH) and Ozone (O3). The atmospheric carbon monoxide (CO) observations can only be made on global and continental scales by remote sensing instruments situated in space. One of instrument is the Measurements of Pollution in the Troposphere (MOPITT), which is designed to measure troposphere CO and CH4 by use of a nadir-viewing geometry and was launched aboard the Earth Observing System (EOS) Terra spacecraft on 18 December 1999. Results from the analysis of the retrieved monthly (1ºх1º) spatial grid resolution, from the MOPITT data were utilized to analyze the distribution of CO surface mixing ratio in Iraq for th

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Publication Date
Wed Sep 30 2020
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Estimation of Minimum Miscibility Pressure for Hydrocarbon Gas Injection Based on EOS
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The important parameter used for determining the probable application of miscible displacement is the MMP (minimum miscibility pressure). In enhanced oil recovery, the injection of hydrocarbon gases can be a highly efficient method to improve the productivity of the well especially if miscibility developed through the displacement process. There are a lot of experiments for measuring the value of the miscibility pressure, but they are expensive and take a lot of time, so it's better to use the mathematical equations because of it inexpensive and fast. This study focused on calculating MMP required to inject hydrocarbon gases into two reservoirs namely Sadi and Tanomaa/ East Baghdad field. Modified Peng Robenson Equation of State was

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Publication Date
Sat Mar 31 2018
Journal Name
Journal Of Engineering
Estimation of Minimum Miscibility Pressure for 〖CO〗_2 Flood Based on EOS
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CO2 Gas is considered one of the unfavorable gases and it causes great air pollution. It’s possible to decrease this pollution by injecting  gas in the oil reservoirs to provide a good miscibility and to increase the oil recovery factor. MMP was estimated by Peng Robinson equation of state (PR-EOS). South Rumila-63 (SULIAY) is involved for which the miscible displacement by  is achievable based on the standard criteria for success EOR processes. A PVT report was available for the reservoir under study. It contains deferential liberation (DL) and constant composition expansion (CCE) tests.  PVTi software is one of the (Eclipse V.2010) software’s packages, it has been used to achieve the goal.  Many trials have been done to ma

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Publication Date
Mon Sep 03 2012
Journal Name
The International Archives Of The Photogrammetry, Remote Sensing And Spatial Information Sciences
CALIBRATION OF FULL-WAVEFORM ALS DATA BASED ON ROBUST INCIDENCE ANGLE ESTIMATION
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Abstract. Full-waveform airborne laser scanning data has shown its potential to enhance available segmentation and classification approaches through the additional information it can provide. However, this additional information is unable to directly provide a valid physical representation of surface features due to many variables affecting the backscattered energy during travel between the sensor and the target. Effectively, this delivers a mis-match between signals from overlapping flightlines. Therefore direct use of this information is not recommended without the adoption of a comprehensive radiometric calibration strategy that accounts for all these effects. This paper presents a practical and reliable radiometric calibration r

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