The study aims to demonstrate the importance of instructional methods in teaching Arabic language as a second language or teaching the Arabic language to non-native speakers. The study is in line with the tremendous development in the field of knowledge, especially in the field of technology and communication, and the emergence of many electronic media in education in general and language teaching in particular. It employs an image in teaching vocabulary and presenting the experience of the Arabic Language Institute for Non-Speakers-King Abdul-Aziz University. The study follows the descriptive approach to solve the problem represented by the lack of interest in the educational methods when teaching Arabic as a second language. Accordingly, the study is to answer the following questions: What is the importance of using teaching aids when teaching Arabic to non-Arabic speakers?What are the methods of employing (an image) as an instructional tool in teaching vocabulary? The study has reached that teaching aids are of great importance in studying the Arabic language for the non-native, the image of the audio and visual aids plays a great role in teaching vocabulary to the beginners. In its modern version, it helps directly in teaching the language from a distance and thus fulfills the hopes of many in teaching Arabic language and covers the acute shortage of a language teacher.
In the present study, a total of 272 freshwater fishes belonging to three species namely: Cyprinus carpio, Barbus xanthopterus and Aspius vorax, were collected from Euphrates river at Al-Haklania distrct, Al-Anbar province during the period from August 2008 till the end of July 2009, by using gill nets and cast nets. Fishes were survyed for intestinal parasitic worms. The investigation revealed the infectation of these fishes with four parasitic species: the digenetic trematode Aspidogaster limacoides from the intestine of C. carpio, B. xanthopterus and A. vorax, larval nematode Contracaecum spp. from the body cavity of C. carpio and the external surface of intestine of B
... Show MoreThree-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and construc
... Show MoreAngle of arrival (AOA) estimation for wideband signal becomes more necessary for modern communication systems like Global System for Mobile (GSM), satellite, military applications and spread spectrum (frequency hopping and direct sequence). Most of the researchers are focusing on how to cancel the effects of signal bandwidth on AOA estimation performance by using a transversal filter (tap delay line) (TDL). Most of the researchers were using two elements array antenna to study these effects. In this research, a general case of proposed (M) array elements is used. A transversal filter (TDL) in phase adaptive array antenna system is used to calculate the optimum number of taps required to compensate these effect. The propo
... Show MoreTwo series of 1,3,4-oxadiazole derivatives at the sixth position of the 2,4-di-
paper
Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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