Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

The present research aims to design an electronic system based on cloud computing to develop electronic tasks for students of the University of Mosul. Achieving this goal required designing an electronic system that includes all theoretical information, applied procedures, instructions, orders for computer programs, and identifying its effectiveness in developing Electronic tasks for students of the University of Mosul. Accordingly, the researchers formulated three hypotheses related to the cognitive and performance aspects of the electronic tasks. To verify the research hypotheses, a sample of (91) students is intentionally chosen from the research community, represented by the students of the college of education for humanities and col

Let R be a commutative ring with identity, and let M be a unitary left R-module. M is called special selfgenerator or weak multiplication module if for each cyclic submodule Ra of M (equivalently, for each submodule N of M) there exists a family {fi} of endomorphism of M such that Ra = ∑_i▒f_i (M) (equivalently N = ∑_i▒f_i (M)). In this paper we introduce a class of modules properly contained in selfgenerator modules called special selfgenerator modules, and we study some of properties of these modules.

Directional Compact Geographic Forwarding (DCGF) routing protocol promises a minimal overhead generation by utilizing a smart antenna and Quality of Service (QoS) aware aggregation. However, DCGF was tested only in the attack-free scenario without involving the security elements. Therefore, an investigation was conducted to examine the routing protocol algorithm whether it is secure against attack-based networks in the presence of Denial-of-Service (DoS) attack. This analysis on DoS attack was carried out using a single optimal attacker, A1, to investigate the impact of DoS attack on DCGF in a communication link. The study showed that DCGF does not perform efficiently in terms of packet delivery ratio and energy consumption even on a sin

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

         استأثرت ظاهرة هجرة العقول او (الكفاءات العلمية) خلال العقدين الاخيرين باهتمام البلدان المتقدمة والنامية على حد سواء ، وذلك نسبة لاثارها السلبية والايجابية ، على الواقع الاجتماعي والتنموي في الدول المرسلة والمستقبلة ، وزاد الاهتمام بهذه الظاهرة في البلدان النامية لما ينجم عن هجرة العقول من خسارة البلدان المرسلة للموارد البشرية العالية التاهيل ، واللازمة لتحقيق النمو الاقتصادي ذ

Objective: To know the impact of social networks on the mental health of adolescents in the city of Diwaniyah.
Methodology: A descriptive cross-sectional study was conducted on adolescents in preparatory schools in ALDiwaniyah
City Center, for the period from Jun 26, 2015 through to October 20, 2015. The schools were
selected from using Probability sampling (240 random samples) six schools were selected from 32 schools (20 %
from total number) the schools were chosen by writing the names of all schools on a pieces of paper and put in
bags. Then, selected six schools random, three boys schools (2 preparatory and 1 secondary) three girls schools
(2 preparatory and 1 secondary), then I chose the sample the students in grad