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

In this work, an important sugar alkynyl ether has been synthesized in two subsequent steps starting from commercially available D-galactose (3). This kind of compounds is highly significant in the synthesis of biologically active molecules such as 1,2,3-triazole and isoxazoles. In the first step, galactose (3) was reacted with acetone in the presence of anhydrous copper (II) sulfate to produce 1,2:3,4-di-O-isopropylidene-α-D-galactose (4) in good yield. The latter was reacted with excess of 3-bromoprop-1-yne in DMF in the presence of NaOH pellets to afford the target molecule 5 in a very good yield. The temperature of this step is crucial in determining the reaction yi

In light of Chaos, the members of societies' general feeling of the system's importance often increases because they believe that they will lose all forms of security and safety if it does not exist. That is why they attribute such a high value to it, and the fear of the system's absence makes it inevitable for it to have continuity, for we live in a world full of surprises, rapid changes, confusion, and confusing

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Mobile Ad hoc Networks (MANETs) is a wireless technology that plays an important role in several modern applications which include military, civil, health and real-time applications. Providing Quality of Service (QoS) for this application with network characterized by node mobility, infrastructure-less, limitation resource is a critical issue and takes greater attention. However, transport protocols effected influential on the performance of MANET application. This study provides an analysis and evaluation of the performance for TFRC, UDP and TCP transport protocols in MANET environment. In order to achieve high accuracy results, the three transport protocols are implemented and simulated with four different network topology which are 5, 10

     The existence of the Internet, networking, and cloud computing support a wide range of new technologies. Blockchain is one of these technologies; this increases the interest of researchers who are concerned with providing a safe environment for the circulation of important information via the Internet. Maintaining solidity and integrity of a blockchain’s transactions is an important issue, which must always be borne in mind. Transactions in blockchain are based on use of public and private keys asymmetric cryptography. This work proposes usage of users’ DNA as a supporting technology for storing and recovering their keys in case those keys are lost — as an effective bio-cryptographic recovery method. The RSA private key is

Image classification can be defined as one of the most important tasks in the area of machine learning. Recently, deep neural networks, especially deep convolution networks, have participated greatly in end-to-end learning which reduce need for human designed features in the image recognition like Convolution Neural Network. It is offers the computation models which are made up of several processing layers for learning data representations with several abstraction levels. In this work, a pre-trained deep CNN is utilized according to some parameters like filter size, no of convolution, pooling, fully connected and type of activation function which includes 300 images for training and predict 100 image gender using probability measures. Re

This research presents a model for surveying networks configuration which is designed and called a Computerized Integrated System for Triangulation Network Modeling (CISTNM). It focuses on the strength of figure as a concept then on estimating the relative error (RE) for the computed side (base line) triangulation element. The CISTNM can compute the maximum elevations of the highest
obstacles of the line of sight, the observational signal tower height, the contribution of each triangulation station with their intervisibility test and analysis. The model is characterized by the flexibility to select either a single figure or a combined figures network option. Each option includes three other implicit options such as: triangles, quadri

In the current research work, a method to reduce the color levels of the pixels within digital images was proposed. The recent strategy was based on self organization map neural network method (SOM). The efficiency of recent method was compared with the well known logarithmic methods like Floyd-Steinberg (Halftone) dithering and Octtrees (Quadtrees) methods. Experimental results have shown that by adjusting the sampling factor can produce higher-quality images with no much longer run times, or some better quality with shorter running times than existing methods. This observation refutes the repeated neural networks is necessarily slow but have best results. The generated quantization map can be exploited for color image compression, clas

 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.