This study seeks to identify the possibility of achieving the property of faithful representation of accounting information and measure it by using the standard approach based on mathematical and statistical equations by comparing two financial periods before and after the application of (IFRS-15) Revenue from contracts with customers, during the period. (2014-2018), for the financial statements of the mixed joint stock companies listed on the Iraq Stock Exchange, which is one of the main pillars of the economic structure of the country, as a joint investment between the state and the private sector, and has importance in many aspects, including support for projects of public companies, S Absorption and employment of labor, as well as ra

The main object of the current work was to determine the antifungal efficiency of secondary metabolites product called synephrine that extracted from Citrus sinesis peels and the ability of synephrine to biosynthesis gold nanoparticles from HAucl4 which consider environmentally favourable method, then determine their activity against pathogenic human dermatophyte. The identification of synephrine done by Thin layer chromatography (TLC), High Performance Liquid Chromatography (HPLC) and The Fourier Transform Infrared (FTIR). The characterization of gold nanoparticles by using Ultra Violet-Visible Spectroscopy (UV-Vis), Field – Emission Scanning Electron Microscopy (FESEM) and Fourier Transform Infrared (FTIR), confirmed the biosynt

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

Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

This paper presents a new design of a nonlinear multi-input multi-output PID neural controller of the active brake steering force and the active front steering angle for a 2-DOF vehicle model based on modified Elman recurrent neural. The goal of this work is to achieve the stability and to improve the vehicle dynamic’s performance through achieving the desired yaw rate and reducing the lateral velocity of the vehicle in a minimum time period for preventing the vehicle from slipping out the road curvature by using two active control actions: the front steering angle and the brake steering force. Bacterial forging optimization algorithm is used to adjust the parameters weights of the proposed controller. Simulation resul

The steganography (text in image hiding) methods still considered important issues to the researchers at the present time. The steganography methods were varied in its hiding styles from a simple to complex techniques that are resistant to potential attacks. In current research the attack on the host's secret text problem didn’t considered, but an improved text hiding within the image have highly confidential was proposed and implemented companied with a strong password method, so as to ensure no change will be made in the pixel values of the host image after text hiding. The phrase “highly confidential” denoted to the low suspicious it has been performed may be found in the covered image. The Experimental results show that the covere

The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w