Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

يعد الاقتصاد الياباني احد اكبر الاقتصادات الرأسمالية المتقدمة ويحتل المرتبة الثالثة بعد الاقتصاد الأمريكي واقتصاد الاتحاد الاوربي من حيث حجم الناتج المحلي الإجمالي والذي يكاد يقترب من (5) تريليون دولار سنويا.

لقد ادت التطورات المتلاحقة التي شهدها الاقتصاد العالمي وخاصة في حقل التمويل الدولي خلال العشرين سنة الاخيرة الى تصاعد وارتفاع في حجم وحركه رؤوس الاموال الدولية على اوسع نطاق بحيث ا

An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive co

Background: Dental caries is one of the most prevalent chronic diseases of people worldwide that lead to the pain and disability across all age groups and still consider as a major cause of tooth loss. The aim of this study was to assess the prevalence and severity of dental caries and treatment needs among school children in Heet city. Materiales and methods: The sample included all school children at age of (12 years old) males and females from urban areas in Heet city. Diagnosis and recording of dental caries and treatment needs were done according to the criteria of WHO. Results: The prevalence of dental caries was (90.2%). The DMFS/dmfs values were (5.85±0.168, 1.57±0.146) respectively for the total sample. Females were foun

The aim of this paper, is to design multilayer Feed Forward Neural Network(FFNN)to find the approximate solution of the second order linear Volterraintegro-differential equations with boundary conditions. The designer utilized to reduce the computation of solution, computationally attractive, and the applications are demonstrated through illustrative examples.

Background: Patients requiring renal biopsies have various glomerular diseases according to their demographic characteristics.
Objective: To study types of glomerular disease among adult Iraqi patients in a single center in Baghdad/Iraq
Material and Methods: A total of 120 native kidney biopsies were studied. All biopsies were adequate and were processed for Light Microscopy.
The age range of the study patients was 17-67 years, with a mean of 38.5 years. The mean follow up period was 28 weeks (4-52 weeks)
Indication for biopsy included: Nephrotic syndrome (N=72; 60%), Asymptomatic proteinuria (N=21; 17.5%), acute nephritic presentation (N=17; 14.16%), asymptomatic haematuria (N=10; 8.33%).
Results: Primary glomerulonephrit

The aim of present work is to improve mechanical and fatigue properties for Aluminum alloy7049 by using Nano composites technique. The ZrO₂ with an average grain diameter of 30-40 nm, was selected as Nano particles, to reinforce Aluminum alloy7049 with different percentage as, 2, 4, 6 and 7 %. The Stir casting method was used to fabricate the Nano composites materials due to economical route for improvement and processing of metal matrix composites. The experimental results were shown that the adding of zirconium oxide (ZrO₂) as reinforced material leads to improve mechanical properties. The best percentage of improvement of mechanical properties of 7049 AA was with 4% wt. of ZrO₂ about (7.76% ) for ultim

     An experimental study was carried out to improve the surface roughness quality of the stainless steel 420 using magnetic abrasive finishing method (MAF). Four independent operation parameters were studied (working gap, coil current, feed rate, and table stroke), and their effects on the MAF process were introduced. A rotating coil electromagnet was designed and implemented to use with plane surfaces. The magnetic abrasive powder used was formed from 33%Fe and 67% Quartz of (250µm mesh size). The lubricant type SAE 20W was used as a binder for the powder contents. Taguchi method was used for designing the experiments and the optimal values of the selected parameters were found. An empirical equation representing the r

Strategic decision making is considered one of the important processes for senior management in contemporary business organizations and service organizations due to the properties of the service such as intangibility, concomitance and mortality. Decision-making has three approaches according to the opinions of most of the writers and researchers in the administrative area: an analytical approach, intuitive approach and behavioral approach. This research is trying to discover the nature of the relationship in terms of the link between the impact of each of these approaches and efficiency of marketing services by selecting an intentional sample of 58 researches from the Directorate General of Traffic, one of the Iraqi Interior Ministry ins

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed