This research aims to know the effect of adopting IFRS 9 on the relevance of the value of the accounting information of the companies in the Iraqi Stock Exchange. Researchers relied on analyzing the financial statements of 10 listed companies for years 2016 – 2019. Researchers used the Ohlson price model to test the relationship between accounting information and value relevance. The research indicated that there is a significant relationship between the adoption of IFRS 9 and the relevance of the value of the earnings and the book value, but the earnings information is more relevance than the book value information, it is due to the interest of investors in the income statement in making investment decisions.

Urban land uses are in a dynamic state that varies over time, the city of Karbala in Iraq has experienced functional changes over the past 100 years, as the city is characterized by the presence of significant tourist and socio-economic activity represented by religious tourism, and it occur due to various reasons such as urbanization. The purpose of this study is to apply a Markov model to analyze and predict the behavior of transforming the use of land in Karbala city over time. This can include the conversion of agricultural land, or other areas into residential, commercial, industrial land uses. The process of urbanization is typically driven by population growth, economic development, based on a set of probabilities and transitions bet

Background: This study was conducted to evaluate the hard palate bone density and thickness during 3rd and 4th decades and their relationships with body mass index (BMI) and compositions, to allow more accurate mini-implant placement. Materials and method: Computed tomographic (CT) images were obtained for 60 patients (30 males and 30 females) with age range 20-39 years. The hard palate bone density and thickness were measured at 20 sites at the intersection of five anterioposterior and four mediolateral reference lines with 6 and 3 mm intervals from incisive foramen and mid-palatal suture respectively. Diagnostic scale operates according to the bioelectric impedance analysis principle was used to measure body weight; percentages of body fa

Knowledge of permeability is critical for developing an effective reservoir description. Permeability data may be calculated from well tests, cores and logs. Normally, using well log data to derive estimates of permeability is the lowest cost method. This paper will focus on the evaluation of formation permeability in un-cored intervals for Abughirab field/Asmari reservoir in Iraq from core and well log data. Hydraulic flow unit (HFU) concept is strongly related to the flow zone indicator (FZI) which is a function of the reservoir quality index (RQI). Both measures are based on porosity and permeability of cores. It is assumed that samples with similar FZI values belong to the same HFU. A generated method is also used to calculate permea

    Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was

In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

Free Space Optics (FSO) plays a vital role in modern wireless communications due to its advantages over fiber optics and RF techniques where a transmission of huge bandwidth and access to remote places become possible. The specific aim of this research is to analyze the Bit-Error Rate (BER) for FSO communication system when the signal is sent the over medium of turbulence channel, where the fading channel is described by the Gamma-Gamma model. The signal quality is improved by using Optical Space-Time Block- Code (OSTBC) and then the BER will be reduced. Optical 2×2 Alamouti scheme required 14 dB bit energy to noise ratio (Eb/N0) at 10-5 bit error rate (BER) which gives 3.5 dB gain as compared to no diversity scheme. Th

In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

Monthly rainfall data of Baghdad meteorological station were taken to study the time behavior of these data series. Significant fluctuation,very slight increasing trend and significant seasonality were noticed. Several ARIMA models were tested and the best one were checked for the adequacy. It is found that the SEASONAL ARIMA model of the orders SARIMA(2,1,3)x(0,1,1) is the best model where the residual of this model exhibits white noise property, uncorrelateness and they are normally distributed. According to this model, rainfall forecast for four years was also achieved and showing similar trend and extent of the original data.

Characteristic evolving is most serious move that deal with image discrimination. It makes the content of images as ideal as possible. Gaussian blur filter used to eliminate noise and add purity to images. Principal component analysis algorithm is a straightforward and active method to evolve feature vector and to minimize the dimensionality of data set, this paper proposed using the Gaussian blur filter to eliminate noise of images and improve the PCA for feature extraction. The traditional PCA result as total average of recall and precision are (93% ,97%) and for the improved PCA average recall and precision are (98% ,100%), this show that the improved PCA is more effective in recall and precision.