The research deals with Environmental Management and how to develop its programs with the use of Knowledge Management, the environmental programs that integrate with processes can add strategic value to business through improving rates of resource utilization , efficiencies , reduce waste, use risk management, cut costs, avoid fines and reduce insurance. All these activities and processes can improve it through knowledge management, the optimal usage for all organizations information , employ it in high value and share it among all organizations members who involves in modify its strategy . Choosing suitable environmental management information system, develop it and modify it with organization processes, can greatly serve the en

In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

This work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent I_ph, saturation current I_s, shunt resistance R_sh, series resistance R_s, ideality factor A at stander test condition (STC) by an ite

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

conventional FCM algorithm does not fully utilize the spatial information in the image. In this research, we use a FCM algorithm that incorporates spatial information into the membership function for clustering. The spatial function is the summation of the membership functions in the neighborhood of each pixel under consideration. The advantages of the method are that it is less
sensitive to noise than other techniques, and it yields regions more homogeneous than those of other methods. This technique is a powerful method for noisy image segmentation. 

Companies seek to enhance investor confidence by achieving the highest level of transparency in disclosure of financial and non-financial information (SASB standards) for Iraqi insurance companies listed on the financial market. The aim of the research is to identify the extent of the ability of financial and non-financial information to enhance transparency in reporting, which is reflected in Investor confidence. And the standards of sustainability development accounting issued by (SASB) through the electronic questionnaire that was distributed. Companies seek to achieve a set of goals, the most important of which is to enhance investor confidence by improving transparency in disclosure. Concerning the employment of financial an

The study aims to study the geographical distribution of electricpower plants in Iraq, except the governorates of Kurdistan Region (Dohuk, Erbil, Sulaymaniyah) due to lack of data.

In order to reach the goal of the research was based on some mathematical equations and statistical methods to determine how the geographical distribution of these stations (gas, hydropower, steam, diesel) within the provinces and the concentration of them as well as the possibility of the classification of power plants in Iraq to facilitate understanding of distribution in a scientific manner is characterized by objectively.

The most important results of the research are that there are a number of factors that led to the irregular distribution

XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.