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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
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Value added tax and its technical organization Lebanon Case Study
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Abstract

      Value Added Tax (VAT) is one of the most important types of indirect taxes because of its advantages in achieving financial, economic and financial objectives. The introduction of VAT is part of the reform of the structure of the Lebanese public tax system aimed at reducing the fiscal deficit and resulting inflation, which still lacks a general consumption tax. There is also an urgent need to increase treasury revenues , Because of its broad tax base, as it imposes on the consumption of locally produced and imported goods, in addition to the role played by this tax in support of the local product              &nbs

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Publication Date
Sun Dec 01 2019
Journal Name
Computers And Electronics In Agriculture
Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq
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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Retrieving Encrypted Images Using Convolution Neural Network and Fully Homomorphic Encryption
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A content-based image retrieval (CBIR) is a technique used to retrieve images from an image database. However, the CBIR process suffers from less accuracy to retrieve images from an extensive image database and ensure the privacy of images. This paper aims to address the issues of accuracy utilizing deep learning techniques as the CNN method. Also, it provides the necessary privacy for images using fully homomorphic encryption methods by Cheon, Kim, Kim, and Song (CKKS). To achieve these aims, a system has been proposed, namely RCNN_CKKS, that includes two parts. The first part (offline processing) extracts automated high-level features based on a flatting layer in a convolutional neural network (CNN) and then stores these features in a

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Publication Date
Sun Jan 08 2023
Journal Name
Journal Of Planner And Development
Design bases for waste recycling rules in cities/ Baghdad, a case study"
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Waste is one of the most important problems affecting the city’s environment and its urban landscape, which results from the activities and activities of man and the natural environment. Its sources have varied between residential, commercial, industrial, medical and hazardous, and its spread in cities, on roads and on abandoned open lands, has led to significant negative effects and risks to human health and the environment.

  Therefore, there were serious attempts to deal with waste and follow sequential steps that formed a waste management system such as (collection, sorting, transport, then treatment and disposal). Preventing and reducing waste, then recycling and recovering by composting or burning, and ending with bu

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
: financial fraud ,Audit risks ,inherent risk ,Detection risk, Data Mining .
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Abstract

The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The impact of structural economic imbalances on inflation Case Study of the Iraqi economy
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Abstract:

There is a close relationship between rigidity and distort structure of production and productivity and inflation rates. The effects of this relationship are distorted the contribution rate of the productive sectors and the disproportionate of exchange rate in foreign trade.

raising the general level of prices is one of the way that have been used by previous governments (inflationary financing or deficit financing) in order to speed up the process of capital formation, depending on the availability of economic resources idle.

The fabricating inflation for development does not represent a true understanding of the nature of the

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sat Dec 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
دور تنقيب البيانات Data Mining في زيادة أداء المنظمة (( دراسة تحليلية في المصرف الصناعي ))
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تمهيد

غالبا ما يكون تعامل المنظمات المالية والمصرفية مع الزبائن بشكل أساسي مما يتطلب منها جمع كميات هائلة من البيانات عن هؤلاء الزبائن هذا بالإضافة الى ما يرد اليها يوميا من بيانات يجعلها أمام أكداس كبيرة من البيانات تحتاج الى جهود جبارة تحسن التعامل معها والاستفادة منها بما يخدم المنظمة.

ان التعامل اليدوي مع مثل هذه البيانات دون استخدام تقنيات حديثة يبعد المنظمة عن التط

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