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Accounting Mining Data Using Neural Networks (Case study)
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Business organizations have faced many challenges in recent times, most important of which is information technology, because it is widely spread and easy to use. Its use has led to an increase in the amount of data that business organizations deal with an unprecedented manner. The amount of data available through the internet is a problem that many parties seek to find solutions for. Why is it available there in this huge amount randomly? Many expectations have revealed that in 2017, there will be devices connected to the internet estimated at three times the population of the Earth, and in 2015 more than one and a half billion gigabytes of data was transferred every minute globally. Thus, the so-called data mining emerged as a technique that aims at extracting knowledge from huge amounts of data, based on mathematical algorithms, which are the basis for data mining. They are derived from many sciences such as statistics, mathematics, logic, learning science, artificial intelligence, expert systems, form-recognition science, and other sciences, which are considered smart and non-traditional.

The problem of the research states that the steady increase in the amount of data, as well as the emergence of many current areas that require different data due to the contemporary environment of business organizations today, make information systems unable to meet the needs of these current organizations, and this applies exactly to accounting information systems as they are the main system in business organizations today. These systems have been designed to meet specific needs that make it impossible today to meet the different needs according to the contemporary environment of business organizations today, as well as failing to deal with the amount of data generated by the information technologies.

The research proposes two main hypotheses. First, the adoption of accounting data mining leads to providing data that the accounting information system was unable to provide before, as well as to shortening the time and effort required to obtain it. Second, the adoption of accounting exploration of data enables the adoption of artificial intelligence methods in processing such data to provide useful information to rationalize decisions.

The research leads to a number of conclusions, including that the steady increase in the amount of data in general, and the accounting data in particular, makes dealing with traditional frameworks a very difficult issue and leads to loss of time and effort during extracting information. In addition, the emergence of many current variables as a result of changes in the work environment requires the presence of technical tools, which have enough flexibility to deal with them. Moreover, data mining tools have the ability to derive relationships based on their existing databases that were not available before.

The research presents a number of recommendations, most important of which is the need to adopt the model presented by the research, i.e., Multilayer Perception, a network that exists within the (SPSS) program, which allows the possibility to use this network easily in rationalizing the decision to choose implemented projects in the provincial councils

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Publication Date
Thu Jul 01 2021
Journal Name
University Of Northampton Pue
Validating a Proposed Data Mining Approach (SLDM) for Motion Wearable Sensors to Detect the Early Signs of Lameness in Sheep
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Extent of the Practice of Iraqi Banks to Manage Profits Using the (LLp it) Model and Its Reflection on the Tax Base, A Case Study of A Sample of Iraqi Private Banks Listed in The Iraqi Stock Exchange
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The research aims to identify the extent to which Iraqi private banks practice profit management motivated by reducing the taxable base by increasing the provision for loan losses by relying on the LLP it model, which consists of a main independent variable (net profit before tax) and independent sub-variables (bank size, total debts to total equity, loans granted to total obligations) under the name of the variables governing the banking business. (Colmgrove-Smirnov) was used to test the normal distribution of data for all banks during the period 2017-2020, and then find the correlation between the main independent variable sub and the dependent variable by means of the correlation coefficient person, and then using the multiple

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Accounting measurement of intangible assets (websites) within the framework of international financial reporting standards An applied study between a sample of Iraqi commercial banks)
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The websites over time have become one of the important tools for communication between individuals among themselves and between individuals and economic units, and they have emerged as one of the important intangible assets to achieve income, as they have become a competitive tool and a marketing outlet for these units and a main means of communication that it uses to exercise its various major activities and achieve potential economic benefits. Therefore, there was a need to measure and display the value of these sites in the financial statements as intangible assets.  Accordingly, the purpose of the research was to determine the costs of the websites owned by the economic unit by way purchase and sites that were created i

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Measuring the Use of Social Media Networks (SMNs) in Knowledge Sharing, by Using Social Cognitive Theory (SCT) A Study Conducted in Some of Iraqi Universities
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   SMNs like Facebook, YouTube, Twitter, WhatsApp,..etc. are among the most popular sites on the Internet. These sites can provide a powerful means of sharing, organizing, finding information and knowledge. The popularity of these sites provides an opportunity to measure the use them in knowledge sharing, which needs a special scale, but unfortunately, there is no special scale for that. Thus, this study supposes to use SCT as a scale to measure the use of SMNs in electronic knowledge sharing due to it has been used to measure knowledge sharing with its traditional form. This study can help the decision-makers to use these SMNs to share the academics’ knowledge in educational institutes to the communi

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Publication Date
Sat Oct 27 2018
Journal Name
Journal Of Planner And Development
دور سهولة الوصول في تعزيز ابعاد التنمية الحضرية شارع الرشيد حالة دراسية
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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Methods of using the periodic chart in the case of the missing values of the stable AR model (2)
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In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

 

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Publication Date
Mon Oct 01 2018
Journal Name
Al–bahith Al–a'alami
International News Agencies Treatment of the Great Return Marches A Case Study of Agence France Presse “AFP”
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This study examines Agence France Presse’s (AFP) media treatment of the Great Return Marches in order to identify its contents, the issues it gave attention to, its sources, attitude, techniques, objectives, the journalistic forms used in covering events and the typographic elements used to highlight them.

This descriptive study employed the survey methodology through the use of content analysis method, and the methodology of mutual relations through the use of the case study method. The data was collected by means of a content analysis form. The study was based on the Agenda Setting Theory in the analysis of the study results.
The study sample included (116) news texts from AFP collected during the period from 20/3/2018 to

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Publication Date
Tue Sep 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Thefts in hospitals and the factors affecting themA case study in the Department of Health Baghdad - Rusafa
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Employee Stealing or internal theft is considered from the passive practices that can’t be denied or be hidden, In spite of the hospital privacy as a serving organization that works 24\7 and deleing with human lives, they weren’t infallible from that kind of practice. To prevent or reduce this practice, it was important to search for the organizational and behavioral factors influencing internal thefts. The study problem briefly is to reach the most organizational and behavioral factors influencing internal theft, in governmental hospitals in Baghdad Rusafa Health district, this was done by analyzing (20) administrative cases of thefts occurred in the District, also a sample of (60) specialist Doctor’s opinion work, in (3) hospital

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Publication Date
Tue Oct 21 2025
Journal Name
Al–bahith Al–a'alami
THE CONSTRUCTION OF NEWS TICKERS IN THE ARABIC CHANNELS: ) Al Arabiya TV - study of the case - 2007(
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While providing important news information, News tickers ( also called sliders or crawlers ) have become one of the methods used daily by satellite channels, because it’s almost a continuous news coverage and as it seems, it has become today an addition to the news world. Hence, satellite channels need to look for a mechanism to build news tickers in order to develop them even though they are still today not recognisable and in need of being classified in a radio or television art, and that is not easy. This research sheds light on the construction of the slider of a news satellite channel, which is important according to our modest convictions, as it can be the beginning of a long scientific research in a new field of study. The probl

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Publication Date
Fri Nov 29 2024
Journal Name
The Iraqi Geological Journal
Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

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