Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequency squares method by "Kalman filter" and "forgetting factor" to obtain the best predictable way for the future using data from the Social Security Department for workers and from the period 1/2013 to 6/2019 where The method of least squares "OLS" was compared with the method of iterative least squares "RLS" by "Karman Filter" and found that "OLS" method is the best according to the comparison measures "RMSE, MAPE" and it gave accurate results close to the real values
This study aimed at an analytical comparison of the Internal Auditing Standards issued by the Institute of Internal Auditors (IIA) and the Guidance Manual for Audit Units issued by the Federal Audit Bureau to show the compatibility and differences between them and the possibility of applying the IIA standards to economic units in Iraq. The guideline was generally not covered by all the internal audit units. There is a lack of keeping pace with changes in internal auditing at the international level and there is a need to strengthen the Guideline on Internal Auditing Standards II A), which is characterized by the preparation of an internal document containing the objectives, powers and responsibilities of the internal audit work as well a
... Show MoreThe present work is qualitative descriptive. It aims to examine the idiosyncratic schema when deciphering the selected violence-based panel from Nasser Ibrahim’s caricatures. The researchers accordingly adopted part of Sharifian’s (2011) Cultural Schema model, particularly that part that is concerned with the examining the micro/idiosyncratic level of understanding. The study has revealed that the participants have not only differed among themselves regarding the way a figure is being denotatively conceptualized, they also highlighted different exact conceptualizations for the same figure, such as: using various adjectives that reflect various levels of intensity, emphasizing the behavioral aspect or the appearance of the figure, ado
... Show MoreDiversity has become one of the required phenomena to be available within public organizations, in light of the changes taking place in the global and international environment and in various fields. Therefore, it was imperative to study the impact of this phenomenon in various institutions, especially public ones, in most developing countries, including Iraq. The current research aims to analyze the relationship between The demographic diversity and institutional effectiveness of a sample of workers in public institutions included (500) respondents. The questionnaires were distributed to them randomly. Diversity is considered an independent variable and institutional effectiveness a dependent variable. The researcher used interview tools a
... Show MoreFinancial markets play an important role in the economy, as it contributes to the financial and economic system of the state stability, as it reduces the adoption of the companies on the loans granted by the banks, as financial markets contribute to attracting and channeling savings to small savers who will be able to buy a number of shares proportional to their savings, It also provides them the place of exchange, and play technology and information systems an important role in facilitating exchanges and increased market activity, in this research touched on the importance of information technology in effect on the activity of the financial markets. Research is divided into three demands of the first concept of eating and the importance
... Show MoreThis paper deals the prediction of the process of random spatial data of two properties, the first is called Primary variables and the second is called secondary variables , the method that were used in the prediction process for this type of data is technique Co-kriging , the method is usually used when the number of primary variables meant to predict for one of its elements is measured in a particular location a few (because of the cost or difficulty of obtaining them) compare with secondary variable which is the number of elements are available and highly correlated with primary variables, as was the&nbs
... Show MoreBiodiversity is one of the important biological factors in determining water quality and maintaining the
ecological balance. In this study, there are 223 species of phytoplankton were identified, and they are as
follows: 88 species of Bacillariophyta and were at 44%,70 species of Chlorophyta and they were at 29 %, 39
species of Cyanophyta and they were at 16 %, 12 species of Euglenozoa and they were at 4 %, four species of
Miozoa and they were at 3 %, and, Phylum Charophyta and Ochrophyta were only eight and two species,
respectively and both of them were at 2%. The common phytoplankton recorded in the sites studied
include Nitzschia palea, Scenedesmus quadricauda, Oscillatoria princeps, and Peridinium
The time series of statistical methods mission followed in this area analysis method, Figuring certain displayed on a certain period of time and analysis we can identify the pattern and the factors affecting them and use them to predict the future of the phenomenon of values, which helps to develop a way of predicting the development of the economic development of sound
The research aims to select the best model to predict the number of infections with hepatitis Alvairose models using Box - Jenkins non-seasonal forecasting in the future.
Data were collected from the Ministry of Health / Department of Health Statistics for the period (from January 2009 until December 2013) was used
... Show MoreThe speaker identification is one of the fundamental problems in speech processing and voice modeling. The speaker identification applications include authentication in critical security systems and the accuracy of the selection. Large-scale voice recognition applications are a major challenge. Quick search in the speaker database requires fast, modern techniques and relies on artificial intelligence to achieve the desired results from the system. Many efforts are made to achieve this through the establishment of variable-based systems and the development of new methodologies for speaker identification. Speaker identification is the process of recognizing who is speaking using the characteristics extracted from the speech's waves like pi
... Show MoreSocial Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation. Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota
... Show MoreIn the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial
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