It is no secret to every researcher that the choice of a topic for research is not without positive reasons and selected goals, and in this context it seems to me that writing in the subject (testimony of God) is important in many ways; In many places to signify the oneness and sincerity of the Prophet and the prosecution of slaves for their actions in the Hereafter and the control of God Almighty them in the world, which indicates that the subject has to do with the faith and care and orientation towards his study leads to identify the meaning of this testimony and purposes in the context of its receipt and guide to the semantic faces that go to her.

The current research consists of four chapters, the first chapter of which is devoted to presenting the research problem, its importance, purpose and limitations as well as a definition of its terms, as the research was limited to knowing the effect of plant decoration in the Kufic script, while the second chapter included the theoretical framework of the research, which consisted of two topics, one of which is the plant decoration, The second relates to the Kufic script and the stages of its formation, development, and intonation. The third chapter includes the research methodology and mechanisms for analyzing the linear panels. The fourth chapter, during which the most important findings of the researcher were presented, are as follows

This work aims to introduce the concepts of left and right derivations in an AT-algebra and discuss some interesting theorems of these concepts. Also, a fuzzy derivation of an AT-subalgebra, a fuzzy right (left) derivation ideal, a fuzzy derivation of AT-subalgebra, and a fuzzy right (left) derivation ideal are studied. Finally, a level derivation of AT-algebras is defined and some propositions are achieved.

Dry gas is considered one of the most environmentally friendly sources of energy. As a result, developing an efficient strategy for storing this gas has become essential. In this work, MOF-199 was synthesized and characterized in order to investigate the MOF-199 in dry gas adsorption using a built-in volumetric system (methane, ethane, and propane from Basrah gas company). The MOF-199 (metal organic framework) was synthesized using the solvothermal method at 373K for 24h, and then it was characterized. The dry gas adsorption on MOF-199 was studied under various conditions (adsorbent dosage, contact time, temperature, and pressure). The isothermal adsorption of the dry gas had been studied on MOF-199 using two types of mo

The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

The present research aimed to test the imagination of children, and may build sample consisted of (400) a baby and child, selected by random way of four Directorates (first Resafe, second Resafe ,first alkarkh , second alkarkh), in order to achieve the objective of research the tow researchers have a test of imagination and extract the virtual and honesty plants distinguish paragraphs and paragraphs and difficulty factor became the test consists of (32), statistical methods were used (Pearson correlation coefficient, coefficient of difficult passages, highlight paragraphs, correlation equation, an equation wrong Standard) the tow researchers have a number of recommendations and proposals.

This research deals with a very important subject as it tries to change the theoretical and scientific heritage and some professional rules adopted in the newsroom. Most media students have difficulties in writing news for press correctly. The researcher tries to identify the compatibility of what is published in local news agencies with professional and academic standards.
The research finds detailed editorial rules for a number of news formats which will play an important role in writing news for press easily, especially for the beginners and newcomers. Also, it discovers a new fact denying the beliefs of some researchers and writers in not having news conclusion in news edited according to the inverted pyramid pattern.
The re

In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N