A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

Background: Osteoarthritis (OA) is a degenerative joint disease. It is one of the major causes of disability in developed and developing countries. Human leukocyte antigen (HLA) as part of immune system has a role in the disease process.Objectives: To investigate whether there is an association between HLA class II-DRB and OA.Methods: A case control study with 26 patients with osteoarthritis and 22 apparently healthy obese control persons matching in ethnicity were enrolled in this study during the period between October 2012 till March 2013. Direct interview was done with each patient and HLA typing was done by molecular method using Sequence Specific Primer (PCR-SSP) method using One Lambda Kit-USA. Results: The results showed that fem

Abstract (Iraq post – war reconstruction strategy: analytical study in fact and future prospects.) There search aims at identifying the causes of internal instability in Iraq from the political ,economic , social and security aspects , to diagnose the imbalance and to work towards finding real solutions to this . The study also aims at identifying the reconstruction proposals to completely eliminate the organizationof the terrorist advocate, as well as to know. theproblem of research lies in the ability of Iraqi political elites to achieve internal stability and to employ reconstruction proposals at all levels . The hypothesis of the research lies in the equation that the process of building stability (political – economic)and (socia

        This study highlights the problems of translating Shakespeare's food and drink-related insults (henceforth FDRIs) in (Henry IV, Parts I&II) into Arabic. It adopts (Vinay & Darbelnet's:1950s) model, namely (Direct& Oblique) to highlight the applicability of the different methods and procedures made by the two selected translators (Mashati:1990 & Habeeb:1905) .The present study tries to answer the following questions:(i) To what extent the FDRIs in Henry IV might pose a translational problem for the selected translators to find suitable cultural equivalents for them? (ii) Why do the translators, in many cases, resort to a literal procedure which is almost not worka

The bodies responsible for the organization of accounting in the world seek to keep abreast of repaid development, by provide the information required by users, which they need to make efficient decision that return them to the desired benefits, and avoid the risks they could face if they made their decision based on misleading information, or insufficient, or not accurate, Hence, the IASB has undertaken to review the standards, and make the necessary adjustment and clarifications to remove the ambiguities that some of the paragraphs may have in IFRS issued.

And the Iraqi Central Bank obliges banks to convert from local accounting standards to apply IFRS only a step towards keeping pace with developments

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t