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Feminist Lament and its Representations in Contemporary Arab Theatrical Text " Al-Khansaa' Play- A Model": نزار شبيب كريم-زينب نوري هاشم
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  The research addresses the feminist lament and its representations in the contemporary Arab theatrical text as one of the purposes of the Arabic poetry and its images, samples, and reasons developed and its incentives multiplied through different time periods in which a dramatic image and representations have been manifested that harmonized with the art of theatre. In order to shed light on these representations, this study has come to look for the representations of lament phenomenon in the Arab theatre texts.
The study consists of an introduction in which the two researchers put forward the research problem, significance and objectives, and a theoretical framework which tackles a theoretical foundation for the research consisting of two sections: the feminist lament a historical view and the second section: lament in the theatre. The two researchers came up with a set of indicators adopted in the analysis of the research sample which was determined by (Al-Khansaa') play by the writer (Mohamed Saleh Ramadan) which agrees with the research objective. After the analysis, the researchers reached at a set of results among them: most of Al-Khansaa' lament is represented by mourning the dead and embodying them through images of sadness and grief.

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Four Level Prior Distributions
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Abstract:

      In this research we discussed the parameter estimation and variable selection in Tobit quantile regression model in present of multicollinearity problem. We used elastic net technique as an important technique for dealing with both multicollinearity and variable selection. Depending on the data we proposed Bayesian Tobit hierarchical model with four level prior distributions . We assumed both tuning parameter are random variable and estimated them with the other unknown parameter in the model .Simulation study was used for explain the efficiency of the proposed method and then we compared our approach with (Alhamzwi 2014 & standard QR) .The result illustrated that our approach

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Publication Date
Thu May 28 2026
Journal Name
Journal Of Engineering
Drag Reduction Using Passive Methods on KIA PRIDE Car Model
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An experimental study on a KIA pride (SAIPA 131) car model with scale of 1:14 in the wind tunnel was made beside the real car tests. Some of the modifications to passive flow control which are (vortex generator, spoiler and slice diffuser) were added to the car to reduce the drag force which its undesirable characteristic that increase fuel consumption and exhaust toxic gases. Two types of calculations were used to determine the drag force acting on the car body. Firstly, is by the integrating the values of pressure recorded along the pressure taps (for the wind tunnel and the real car testing), secondly, is by using one component balance device (wind tunnel testing) to measure the force. The results show that, the average drag estimated on

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Publication Date
Fri Aug 23 2013
Journal Name
International Journal Of Computer Applications
Lossless Compression of Medical Images using Multiresolution Polynomial Approximation Model
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In this paper, a simple fast lossless image compression method is introduced for compressing medical images, it is based on integrates multiresolution coding along with polynomial approximation of linear based to decompose image signal followed by efficient coding. The test results indicate that the suggested method can lead to promising performance due to flexibility in overcoming the limitations or restrictions of the model order length and extra overhead information required compared to traditional predictive coding techniques.

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Publication Date
Wed Dec 30 2015
Journal Name
Mathematical Theory And Modeling
On the stability of an SIS epidemic model involving treatment
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The objective of this paper is to study the stability of SIS epidemic model involving treatment. Two types of such eco-epidemiological models are introduced and analyzed. Boundedness of the system is established. The local and global dynamical behaviors are performed. The conditions of persistence of the models are derived.

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Publication Date
Mon Jul 01 2013
Journal Name
Journal Of Engineering
Behavior of Reinforced Gypseous Soil Embankment Model under Cyclic Loading
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The construction of embankment for roadway interchange system at urban area is restricted due to the large geometry requirements, since the value of land required for such construction is high, and the area available is limited as compared to rural area. One of the optimum solutions to such problem is the earth reinforcement technique which requires a limited area for embankment construction. Gypseous soil from Al-Anbar governorate area was obtained and subjected to various physical and chemical analysis to determine it is properties. A laboratory model box of 50x50x25 cm was used as a representative embankment; soil has been compacted in five layers at maximum dry density (modified compaction) and an aluminum reinforcement strips we

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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Computer Science
Peer-to-Peer Video Conferencing Using Hybrid Content Distribution Model
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Publication Date
Fri Nov 02 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Inducing the Health Promotion Model for Nursing Practice: Qualitative Study
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Objective: To generate a model that conceptualizes the phenomenon of health promotion and its related factors.
Methodology: A grounded theory methodology is used as qualitative method to explore the health promotion as
phenomenon of interest and its other related factors from the perspectives of specialists in this field. The study is
carried out from January 2002 through September 2004. A sample of (20) specialists in health sciences are
selected and interviewed as experts in the area of health promotion. The investigators conducted intensive and
structured interviews with the specialists to collect the data. These interviews were transcribed verbatim,
analyzed and interpreted.
Results: Findings of the study indicat

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Tue Nov 27 2018
Journal Name
The Iraqi Geological Journal
CHRONOSTRATIGRAPHICALLY BASED RESERVOIR MODEL FOR CENOMANIAN CARBONATES, SOUTHEASTERN IRAQ OILFIELDS
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The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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