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Blindness and the Critique of Society: Dystopia in “Blindness” by José Saramago""
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This paper addresses the new coloring in the concept of dystopian society as represented by the positive role of one of the characters vs. the passive role of the government and its mutual effect on the people of the society. In addition, it describes how all men in the dystopian society victimize and degrade the other through unlawful acts, like: stealing, rape, and fear, which are the lowest points in a moral decay. However, it offers hope by illustrating a positive sense, as exemplified by the doctor's wife out of Saramago's optimistic view that men may be descended from good women. Accordingly, the paper aims to examine the effect of the government’s role in the lives of the people who have later turned into blind in a dystopian society and of people towards one other, and to clarify the positive sense as represented by the doctor’s wife. To meet this, the researcher is to adopt Tom Moylan’s (2000) concept of Dystopia when analyzing José Saramago’s novel, Blindness. This study has uncovered the erosion of trust in others and clarified the heinous injustices committed by both authority figures and laypeople. The troops' cruel treatment toward the blind has led to their sudden infection with that disease. Saramago expressed his upbeat belief that men can change just, they derived from good women as the doctor's wife. The study further has exposed the impact of the violent behavior of both the government and the people towards one another on the confusion and degradation of the humanity.

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
Specifying Quality of a Tight Oil Reservoir through 3-D Reservoir Modeling
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Increasing hydrocarbon recovery from tight reservoirs is an essential goal of oil industry in the recent years. Building real dynamic simulation models and selecting and designing suitable development strategies for such reservoirs need basically to construct accurate structural static model construction. The uncertainties in building 3-D reservoir models are a real challenge for such micro to nano pore scale structure. Based on data from 24 wells distributed throughout the Sadi tight formation. An application of building a 3-D static model for a tight limestone oil reservoir in Iraq is presented in this study. The most common uncertainties confronted while building the model were illustrated. Such as accurate estimations of cut-off

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
Diversity of design methods for global competitive advertising: عمار صباح شاكر ناجي
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As a result of the development and global openness and the possibility of companies providing their services outside their spatial boundaries that were determined by them, and the transformation of the world due to the development of the means of communication into a large global market that accommodates all products from different regions and of the same type and production field, competition resulted between companies, and the race to obtain the largest market share It ensures the largest amount of profits, and it is natural for the advertising promotion by companies for their product to shift from an advertisement for one product to a competitive advertisement that calls on the recipient to leave the competing product and switch to it

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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Effect of Cold Atmospheric Pressure Plasma on Fertility Hormones for Female Rats
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Abstract<p>The direct application of cold atmospheric plasma (CAP) is the main scope of plasma medicine in or on the organism for curative purposes. Cold plasma is both effective in disrupting a wide range of microorganisms including multiple drug resistant ones (MDRs) and to stimulate proliferation of mammalian cells. It has obtained by Floating Electrode Dielectric Barrier Discharge (FE-DBD) system. The present study aimed to show the effected of cold plasma on the fertility hormones LH, Prolactin, Estrogen, and Testosterone hormones for healthy adult female rats (Albino) / bulb c). There are divided into many groups according to time exposure of plasma (15, 30, 60, and 90 second) and a refere</p> ... Show More
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Publication Date
Thu Dec 27 2018
Journal Name
International Journal Of Hydrogen Energy
Compressional wave velocity of hydrate-bearing bentheimer sediments with varying pore fillings
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A potential alternative energy resource to meet energy demands is the vast amount of gas stored in hydrate reserves. However, major challenges in terms of exploration and production surround profitable and effective exploitation of these reserves. The measurement of acoustic velocity is a useful method for exploration of gas hydrate reserves and can be an efficient method to characterize the hydrate-bearing sediments. In this study, the compressional wave velocity (P-wave velocity) of consolidated sediments (Bentheimer) with and without tetrahydrofuran hydrate-bearing pore fillings were measured using the pulse transmission method. The study has found that the P-wave velocity of consolidated sediments increase with increasing hydrate format

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Publication Date
Mon Nov 01 2021
Journal Name
Chaos, Solitons &amp; Fractals
Dynamic analysis of a harvested fractional-order biological system with its discretization
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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Fri Jul 01 2022
Journal Name
Ieee Transactions On Systems, Man, And Cybernetics: Systems
Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot
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Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Engineering
Comparison of Seepage Trough Zoned Earth dam Using Improved Light-Textured Soils
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Seepage through earth dams is one of the most popular causes for earth dam collapse due to internal granule movement and seepage transfer. In earthen dams, the core plays a vital function in decreasing seepage through the dam body and lowering the phreatic line. In this research, an alternative soil to the clay soil used in the dam core has been proposed by conducting multiple experiments to test the permeability of silty and sandy soil with different additives materials. Then the selected sandy soil model was used to represent the dam experimentally, employing a permeability device to measure the amount of water that seeps through the dam's body and to represent the seepage line. A numerical model was adopted using Geo-Studio software i

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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