The objective of this research is to develop a method for applying financial derivatives in the local environment to reduce the risk of foreign exchange rate fluctuations to enhance quality of accounting profits through Financial reporting to local units In accordance with international financial reporting standards, To accomplish this objective was selected a sample of Iraqi units exposed to the risk of fluctuations in foreign currency rates, As the research found:

• many companies and banks in the local environment a lot of losses due to fluctuations in foreign currency exchange rates.
• that financial derivatives in the Iraqi environment represent

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

The last ten years observed a shift enormous scientific in the method and way that it deals professional with the cost accounting and reflected the result those shift enormous scientific of increase the competitive environmental that accompanied the emergence of a modern manufacturing environmental on surface the long roductive life and emergence advanced information technology that give a central focus of his important on client with growing global markets growth on a large scale.

        The research aim to define the concept of cost awareness, the concept and methods of  strategic cost management and the role of cost awareness for managers of industrial units in strategic of cost managem

Abstract:

                The aim of the current study lies in showing and demonstrating the effect of the independent variable of organizational integrity with its dimensions represented by (organizational optimism, organizational trust, organizational integrity, organizational sympathy) on the dependent variable of strategic drifts through its dimensions represented by (organizational culture, leadership, innovation, strategic planning) .The analytical descriptive approach has been adopted and the questionnaire has been used as a tool to obtain data and information from the sample of (57) people who are at the administrative levels (seni

Results showed that the optimum conditions for production of inulunase from isolate Kluyveromyces marxianus AY2 by submerged culture could be achieved by using inulin as carbon source at a concentration of 2% with mixture of yeast extract and ammonium sulphate in a ratio of 1:1 in a concentration of 1% at initial pH 5.5 after incubation for 42 hours at 30ºC.

The aim of the present study is to examine the effectiveness of a proposed unite in voluntary work in enhancing critical thinking skills and the attitudes towards responsible citizenship among eighth grade female students in the Sultanate of Oman. In order to collect the study data, the researchers employed a quasi-experimental research design with twenty female students from Al-Sideeqah bint Al-Sideeq for basic education school. The research data were collected via a critical thinking test that consisted of twenty-five items and a scale of twenty items under three different dimensions, which aimed to measure students' attitudes towards responsible citizenship. The researchers implemented these two instruments as pre- and post the experi