MR Younus, Alustath, 2011

An advertisement is a form of communication intended to promote the sale of a product or service, influence public opinion, gain political support, or to elicit some other response. It consists of various type, including style, target audience, geographic scope, medium, or purpose. An advertisement should catch a person's attention and quickly create a memorable impression. The main aim of the present paper is to investigate the phonological problems of translating English international TV advertisements into Arabic. It deals with the most common and popular TV advertisements. The importance of such advertisements lies not in its information content rather than in the achievement of the desired impact on the receivers. When translating such

Search came (the employment of Arabic calligraphy in gold jewelry styles) four chapters, the first chapter of which dealt:A/research problem B/importance of research C/targets search D/ Define termsAs the aim of the research (to identify the employment of different forms of Arabic calligraphy on gold jewelry styles).It came in the second quarter (the theoretical framework and previous studies), some of the topics reviewed in which diversities researcher aesthetic and functional, and various uses that filled Arabic calligraphy.The third chapter outlining the researcher methodology and the research community, has a special form for the analysis of the samples are designed as form is offered on a number of experts in the field of jurisdicti

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

This dissertation studies the application of equivalence theory developed by Mona Baker in translating Persian to Arabic. Among various translation methodologies, Mona Baker’s bottom-up equivalency approach is unique in several ways. Baker’s translation approach is a multistep process. It starts with studying the smallest linguistic unit, “the word”, and then evolves above the level of words leading to the translation of the entire text. Equivalence at the word level, i.e., word for word method, is the core point of Baker’s approach.

This study evaluates the use of Baker’s approach in translation from Persian to Arabic, mainly because finding the correct equivalence is a major challenge in this translation. Additionall

A New Spectrophotometric Methods are improved for determination Metronidazole (MTZ) and Metronidazolebenzoate (MTZB) depending on1STand 2nd derivative spectrum of the two drugs by using ethanol as a solvent. Many techniques were proportionated with concentration (peak high to base line, peak to peak and peak area). The linearity of the methodsranged between(1-25µg.ml-1) is obtained. The results were precise and accurate throw RSD% were between (0.041-0.751%) and (0.0331-0.452%), Rec% values between (97.78, 101.87%) and (98.033-102.39%) while the LOD between (0.051-0.231 µg.ml-1) and (0.074-1.04 µg.ml-1) and LOQ between (0.170-0.770µg.ml-1) and (0.074-0.313 µg.ml-1) of (MTZ) and of (MTZB) respectively. These Methods were successfully ap

In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined; also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic

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