Abstract
The image of the soldier, as a hero who sacrifices everything to defend his
country and values, is no longer depicted in modern drama. With two World Wars
and many regional wars and civil wars, the soldier becomes a victim, not a hero.
Authors present the character of the soldier as a man who suffers a lot as he is
victimized by his own government and its politics that forces him to be in such a
position. Dramatists express their views about race, oppression and war through
their characters, such as the character of the soldier, as in the two selected plays for
this research: The Hostage by Brendan Behan and A Soldier's Play by Charles
Fuller.
The Hostage depicts, through its events, the Irish oppression which makes
both the Irish and the English victims for this conflict. A Soldier's Play presents the
oppression which the blacks face daily in their society, a matter which creates
among them the oppressed and the oppressor.
An oppressed people demand that all their resources be put to the
service of liberating them, no matter what these resources are. Certainly art and
culture must be seen in such a light. Literature, as part of art is sometimes the
mirror of its society and people. Dramatists, in general, and Brendan Behan and
Charles Fuller, in particular, are aware of the value of the theatre as a tool for social
discussion, therefore; their characters no more assume limited quality, as they
assume a universal one.1
Berndan Behan's The Hostage, which lies in three acts, was first
presented by Theatre Workshop in 1958. It takes place in an old house in Dublin. It
is owned by Monsewer, an Englishman by birth, who is more fanatically Irish than
his entourage; Pat, who served with Monsewer in the civil war, is no longer fanatic.
The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots. To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura
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Lowpass spatial filters are adopted to match the noise statistics of the degradation seeking
good quality smoothed images. This study imply different size and shape of smoothing
windows. The study shows that using a window square frame shape gives good quality
smoothing and at the same time preserving a certain level of high frequency components in
comparsion with standard smoothing filters.
In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.
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Background: Body image is one of the most important psychological factors that affects adolescents’ personality and behavior. Body image can be defined as the person’s perceptions, thoughts, and feelings about his or her body.
Objectives: to identify the prevalence of body image concerns among secondary school students and its relation to different factors.
Subjects and methods: A cross-sectional study conducted in which 796 secondary school students participated and body shape concerns was investigated using the body shape questionnaire (BSQ-34).
Results: The prevalence of moderate/marked concern was (21.6%). Moderate/ marked body shape concern was significantly associated
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This study explores the challenges in Artificial Intelligence (AI) systems in generating image captions, a task that requires effective integration of computer vision and natural language processing techniques. A comparative analysis between traditional approaches such as retrieval- based methods and linguistic templates) and modern approaches based on deep learning such as encoder-decoder models, attention mechanisms, and transformers). Theoretical results show that modern models perform better for the accuracy and the ability to generate more complex descriptions, while traditional methods outperform speed and simplicity. The paper proposes a hybrid framework that combines the advantages of both approaches, where conventional methods prod
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Many approaches of different complexity already exist to edge detection in
color images. Nevertheless, the question remains of how different are the results
when employing computational costly techniques instead of simple ones. This
paper presents a comparative study on two approaches to color edge detection to
reduce noise in image. The approaches are based on the Sobel operator and the
Laplace operator. Furthermore, an efficient algorithm for implementing the two
operators is presented. The operators have been applied to real images. The results
are presented in this paper. It is shown that the quality of the results increases by
using second derivative operator (Laplace operator). And noise reduced in a good
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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The aim of this study is to assess nurse's knowledge and role in the management of thalassemic patients in the Sulaimania Thalassemia Centre. Methodology: This study utilized a qualitative approach to explore nurses’ knowledge about thalassemia through semi structured group interviews. Questionnaire was synthesized through a comprehensive review of literature. Results: The results show that nurses in Kurdistan region of Iraq have a limited role in terms of decision making and there is lack of nursing documentation other than that of recording abnormal events, and a lack of knowledge about and engageme
Abstract
The main question raised in this paper is: Is it possible to translate the ‘genre’
of Quran? And if this ‘genre’ is Quran specific, a ‘genre’ of its own, i.e. a unique one,
how can the Quranic text be translated from Arabic into English or any other
language? This question has been raising a lot of controversy among translation
theorists, linguists, philosophers and scholars of Islam and specialists in the sciences
of Arabic language let alone Quran exegetes. Scholars of the Arabic language and
scholars of Islam have argued that because of the genre of Quran is the genre of (ijaz),
translatability can never be possible. Equivalence, thus, cannot be achieved especially
if we know that so far