Management of Foreign Exchange Rate Exposure by Using Financial Hedging An Analytical Empirical Study The main purpose of this Research is to investigate the ability to reduce the  effect  of exchange rate fluctuation on firm value , by usage appropriate hedging strategies to provide the firms force to adopted with complex and highly uncertainty conditions , characteristic of the most of the financial markets  . The field of this study is the giant five Multinational on the world. Nokia, Toyota Motor, Intel , Coca Cola, Microsoft. practical analysis is provide the truth of all study's  hypothesis , and it is reach to many of conclusion, the most important of them is  Stem from unexpected fluctuation on nominal ex

The large number of failure in electrical power plant leads to the sudden stopping of work. In some cases, the necessary reserve materials are not available for maintenance which leads to interrupt of power generation in the electrical power plant unit. The present study, deals with the determination of availability aspects of generator in unit 5 of Al-Dourra electric power plant. In order to evaluate this generator's availability performance, a wide range of studies have been conducted to gather accurate information at the level of detail considered suitable to achieve the availability analysis aim. The Weibull Distribution is used to perform the reliability analysis via Minitab 17, and Artificial Neural Networks (ANNs) by approaching o

This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

This paper presents an efficient methodology to design modified evaporative air-cooler for winter air-conditioning in Baghdad city as well as using it for summer air-conditioning by adding a heating process after the humidification process. laboratory tests were performed on a direct evaporative cooler (DEC) followed by passing the air on hot water through heat exchanger placed in the coolers air duct exit. The tests were conducted on the 2nd of December /2011 when the ambient temperature was 8.1°C and the relative humidity was  (68%). The air flow rate is assumed to vary between 0.069 to 0.209 kg/s with constant water flow rate of 0.03 kg/s in the heat exchanger. The performance is reported in terms of effectiveness of DEC, satura

The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv