يهدف هذا البحث إلى تحليل محتوى كتابي الحاسوب للمرحلة المتوسطة في العراق وفقاً لنظرية الذكاءات المتعددة عن طريق الإجابة عن السؤال الآتي: ما نسبة توافر الذكاءات المتعددة في محتوى كتابي الحاسوب المقرران على طلبة المرحلة المتوسطة (الصفين الأول والثاني) للعام الدراسي (2017-2018) م؟ ولتحقيق هدف البحث اتبعت الباحثة منهج البحث الوصفي التحليلي (تحليل المحتوى)، واعتمدت الفكرة الصريحة وحده للتسجيل، أما أداة البحث فهي أداة

Certainly there is a negative impact on development due to corruption in its corruption forms It is administrative and financial as well as direct impact on all sectors Including the health sector, which has seen in Iraq a marked setback in performance and services , The research aims at the possibility of demonstrating the negative effects of financial and administrative corruption on health institutions and Inability to meet health needs The extent to which Regulatory institutions and institutions manage to reduce financial and administrative corruption and ways of dealing with it The phenomenon of financial and administrative corruption is the most serious phenomenon because of its impact on economic growth, which in turn impedes the

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

In this work, watershed transform method was implemented to detect and extract tumors and abnormalities in MRI brain skull stripped images. An adaptive technique has been proposed to improve the performance of this method.Watershed transform algorithm based on clustering techniques: K-Means and FCM were implemented to reduce the oversegmentation problem. The K-Means and FCM clustered images were utilized as input images to the watershed algorithm as well as of the original image. The relative surface area of the extracted tumor region was calculated for each application. The results showed that watershed trnsform algorithm succeedeed to detect and extract the brain tumor regions very well according to the consult of a specialist doctor a

     The conventional procedures of clustering algorithms are incapable of overcoming the difficulty of managing and analyzing the rapid growth of generated data from different sources. Using the concept of parallel clustering is one of the robust solutions to this problem. Apache Hadoop architecture is one of the assortment ecosystems that provide the capability to store and process the data in a distributed and parallel fashion. In this paper, a parallel model is designed to process the k-means clustering algorithm in the Apache Hadoop ecosystem by connecting three nodes, one is for server (name) nodes and the other two are for clients (data) nodes. The aim is to speed up the time of managing the massive sc

Knowledge is a source of innovation, and innovation is the distinctive means of creating knowledge and achieving prosperity in the information age with the presence of information technology means and electronic platforms. The aim of the research is to introduce the most important specialized electronic knowledge platforms, and seek to answer questions that cover aspects of the subject and describe it as a source of information, guidance and training in the educational community. and electronic training and its importance in developing knowledge and innovation in the services of information institutions, The research dealt with two models of specialized electronic knowledge platforms in the field of information and libraries, the adoption o

Dans la langue française, une forme d'auxiliarité, composée de deux éléments cohérents l'auxiliant et l'auxilié, fournit, en effet, à la phrase une diversité significative et structurale. L'auxiliarité, renvoie à l'unification de deux éléments grammaticaux afin de localiser l'énoncé sur l'axe du temps, d'aspect ou de mode. É. Benveniste définit l'auxiliarité en : « Il s'agit d'une forme linguistique unitaire qui se réalise, à travers des paradigmes entiers, en  deux éléments, dont chacun assume une partie des fonctions grammaticales, et qui sont à la fois liés et autonomes, distincts et complémentaires »[1]. Ces deux éléments d'auxiliarité possèden

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

The future of the highly competitive global banking is electronic banking via internet. This trend of electronic delivery of banking products and services is necessitated by the customers' demanding more Internet-customized daily transaction. Hence, customer affecting-satisfaction factors need to be thoroughly investigated in order to deliver efficient electronic banking. Consequently, this paper reviewed three approaches to reach the most influential customer affecting-satisfaction factors. These customer affecting-satisfaction approaches are prioritizing based on cause and effect relationships, understanding with the use of a questionnaire survey and better communicating using e-mail and social media. The pool of customer affecting-sat

Speech encryption approaches are used to prevent eavesdropping, tracking, and other security concerns in speech communication. In this paper, a new cryptography algorithm is proposed to encrypt digital speech files. Initially, the digital speech files are rearranged as a cubic model with six sides to scatter speech data. Furthermore, each side is encrypted by random keys that are created by using two chaotic maps (Hénon and Gingerbread chaotic maps). Encryption for each side of the cube is achieved, using the based map vector that is generated randomly by using a simple random function. Map vector that consists of six bits, each bit refers to one of the specific chaotic maps that generate a random key to encrypt each face of the cube. R