The sensitive and important data are increased in the last decades rapidly, since the tremendous updating of networking infrastructure and communications. to secure this data becomes necessary with increasing volume of it, to satisfy securing for data, using different cipher techniques and methods to ensure goals of security that are integrity, confidentiality, and availability. This paper presented a proposed hybrid text cryptography method to encrypt a sensitive data by using different encryption algorithms such as: Caesar, Vigenère, Affine, and multiplicative. Using this hybrid text cryptography method aims to make the encryption process more secure and effective. The hybrid text cryptography method depends on circular queue. Using circular queue in this work allows to encrypt each character of plaintext by one of cipher methods which controlled by control key for selection process. The scheduling of above cipher methods implementation depends on control key. The experiment results of the proposed hybrid text cryptography method shows ability to cipher and decipher an important data with effectively and efficiently. Utilizing the properties of different cipher methods that are scheduled in circular queue (Caesar, Vigenère, Affine, and Multiplicative) leads to consume time less than other methods when they used alone, so, the important concepts in cryptography process such as complexity, integrity, execution time and security are meet in the proposed hybrid text cryptography method in ef ective manner.
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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The Iraqi government seeks to overcome the financial crisis by investing and privatizing some projects to achieve sustainable growth. Most of the investment projects in Iraq suffer from many constraints that greatly impact the success of these projects. A survey of the opinions of a group of experts was conducted to identify the most important constraints facing the investment process in Iraq. Then the experts' answers were arranged in a closed questionnaire and distributed to the research sample for which the statistical analysis was conducted. Through it, the most important (17) factors that had the greatest impact on the failure of investment projects in Iraq were reached. One of the main constraints was
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This study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen
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In this paper, a subspace identification method for bilinear systems is used . Wherein a " three-block " and " four-block " subspace algorithms are used. In this algorithms the input signal to the system does not have to be white . Simulation of these algorithms shows that the " four-block " gives fast convergence and the dimensions of the matrices involved are significantly smaller so that the computational complexity is lower as a comparison with " three-block " algorithm .
Cognitive stylistics also well-known as cognitive poetics is a cognitive approach to language. This study aims at examining literary language by showing how Schema Theory and Text World Theory can be useful in the interpretation of literary texts. Further, the study attempts to uncover how readers can connect between the text world and the real world. Putting it differently, the study aims at showing how the interaction between ‘discourse world’ and ‘text world’. How readers can bring their own experience as well as their background knowledge to interact with the text and make interpretive connections. Schema and text world theories are useful tools in cognitive stylistic studies. The reader's perception o
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Language as a means of communication has long been the concern of many conversation analysts in their studies such as: Sacks et al. (1974), Schegloff et al. (1977), Duncan (1972), Grice (1975) and Burton (1980). Burton has attempted analyzing the first ten transitions of the play “The Dumb Waiter” for mere a presentation of her approach. This paper aims at analyzing the conversational structure of forum on the subject of literary fiction and genre fiction by applying Burton’s model (1980) of analysis to answer the question to what extent this model is applicable in analyzing the presented text. The findings of the investigation have proved the applicability of the structure of conversation formulated by Burton (1980) in her model wit
... Show MoreCognitive stylistics also well-known as cognitive poetics is a cognitive approach to language. This study aims at examining literary language by showing how Schema Theory and Text World Theory can be useful in the interpretation of literary texts. Further, the study attempts to uncover how readers can connect between the text world and the real world. Putting it differently, the study aims at showing how the interaction between ‘discourse world’ and ‘text world’. How readers can bring their own experience as well as their background knowledge to interact with the text and make interpretive connections.
Schema and text world theories are useful tools in cognitive stylistic stud
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
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Although text document images authentication is difficult due to the binary nature and clear separation between the background and foreground but it is getting higher demand for many applications. Most previous researches in this field depend on insertion watermark in the document, the drawback in these techniques lie in the fact that changing pixel values in a binary document could introduce irregularities that are very visually noticeable. In this paper, a new method is proposed for object-based text document authentication, in which I propose a different approach where a text document is signed by shifting individual words slightly left or right from their original positions to make the center of gravity for each line fall in with the m
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