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Bayesian Inference for Reliability Function of Gompertz Distribution
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Abstract<p>In this paper, some Bayes estimators of the reliability function of Gompertz distribution have been derived based on generalized weighted loss function. In order to get a best understanding of the behaviour of Bayesian estimators, a non-informative prior as well as an informative prior represented by exponential distribution is considered. Monte-Carlo simulation have been employed to compare the performance of different estimates for the reliability function of Gompertz distribution based on Integrated mean squared errors. It was found that Bayes estimators with exponential prior information under the generalized weighted loss function were generally better than the estimators based on Jeffreys prior information.</p>
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Publication Date
Fri Dec 22 2006
Journal Name
Journal Of Planner And Development
The productive partnership in development communication is an effective strategy for change
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This study can be considered as un introduction to the idioms and the strategy about the productive partnership development connection, that helps the researcher and the organization in their work in to activate development and the natural sources,manegment,to improve the two sides active connected to the local society, and to use it as easier and smoother participation of the people who work in development field and the natural sources management research, That connection depends mostly upon the capability of researcher and the development worker to increase the ability of individual and local society to specify and analyzing their problems and to try solutions to make their life better with good income.   

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Publication Date
Fri Sep 09 2022
Journal Name
Revista Mexicana De Oftalmología (english Edition)
Posterior subtenon triamcinolone acetonide combined with phacoemulsification for patients with diabetic maculopathy
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Publication Date
Thu Dec 13 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Psychological Well-being for Elderly People at Geriatric Centers in Baghdad City
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Objective: To evaluate the levels of Psychological well-being among elderly people and To find out the relationship between socio-demographic characteristics and psychological well-being among elderly people who live in Geriatric centers. Methodology: A descriptive study in which evaluation approach is applied to achieve the objectives of the study the period of the study was from 29 December 2014 to 25 may 2015, The sample is non-probability (purposive sample) of 60 elderly people and selecte according to criteria of sample and for the purpose of the study , ( 40 ) are from Al Rashad and ( 20 ) Sleek

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Publication Date
Wed Mar 01 2023
Journal Name
Results In Engineering
Low-cost autonomous car level 2: Design and implementation for conventional vehicles
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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Wed Sep 01 2021
Journal Name
Expert Systems With Applications
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
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Publication Date
Mon Aug 01 2022
Journal Name
Water, Air, & Soil Pollution
Cladophora Algae Modified with CuO Nanoparticles for Tetracycline Removal from Aqueous Solutions
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Modified algae with nano copper oxide (CuO) were used as adsorption media to remove tetracycline (TEC) from aqueous solutions. Functional groups, morphology, structure, and percentages of surfactants before and after adsorption were characterised through Fourier-transform infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS). Several variables, including pH, connection time, dosage, initial concentrations, and temperature, were controlled to obtain the optimum condition. Thermodynamic studies, adsorption isotherm, and kinetics models were examined to describe and recognise the type of interactions involved. Resultantly, the best operation conditions were at pH 7, contact time

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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Tue Sep 29 2020
Journal Name
Journal Of Settlements And Spatial Planning
Regional Development Prospects for Sustainable Urbanization. Case Study – Qalaat Salih in Iraq
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The importance of regional development resides in the provision of aid and other assistance to regions that are less economically developed. The purpose of this research is to identify the development possibilities and resources at the regional level, which can be tapped for the development of secondary cities. This research aims to shed light on the importance of urban planning in creating regional balance and relieving population and service pressure on major cities. The research answers the question relative to how urban planners can work towards the idea of creating development corridors including the cities located within them, whilst focusing more on the regional dimension and the topic of sustainable urbanization. This research assum

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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