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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
Sun Jul 01 2018
Journal Name
Agronomy Journal
Use of Rainfall Data to Improve Ground-Based Active Optical Sensors Yield Estimates
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Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl

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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Ten Years of OpenStreetMap Project: Have We Addressed Data Quality Appropriately? – Review Paper
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It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Eco-friendly and Secure Data Center to Detection Compromised Devices Utilizing Swarm Approach
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Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

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Scopus (5)
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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
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         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
A Modified 2D-Checksum Error Detecting Method for Data Transmission in Noisy Media
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In data transmission a change in single bit in the received data may lead to miss understanding or a disaster. Each bit in the sent information has high priority especially with information such as the address of the receiver. The importance of error detection with each single change is a key issue in data transmission field.
The ordinary single parity detection method can detect odd number of errors efficiently, but fails with even number of errors. Other detection methods such as two-dimensional and checksum showed better results and failed to cope with the increasing number of errors.
Two novel methods were suggested to detect the binary bit change errors when transmitting data in a noisy media.Those methods were: 2D-Checksum me

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Stability testing of time series data for CT Large industrial establishments in Iraq
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Abstract: -
The concept of joint integration of important concepts in macroeconomic application, the idea of ​​cointegration is due to the Granger (1981), and he explained it in detail in Granger and Engle in Econometrica (1987). The introduction of the joint analysis of integration in econometrics in the mid-eighties of the last century, is one of the most important developments in the experimental method for modeling, and the advantage is simply the account and use it only needs to familiarize them selves with ordinary least squares.

Cointegration seen relations equilibrium time series in the long run, even if it contained all the sequences on t

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
State-of-the-Art in Data Integrity and Privacy-Preserving in Cloud Computing
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Cloud computing (CC) is a fast-growing technology that offers computers, networking, and storage services that can be accessed and used over the internet. Cloud services save users money because they are pay-per-use, and they save time because they are on-demand and elastic, a unique aspect of cloud computing. However, several security issues must be addressed before users store data in the cloud. Because the user will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.), and will not know where the data is stored, the user must ensure that the cloud stores and maintains the outsourced data appropriately. The study's primary goals are to mak

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Publication Date
Sat Jan 05 2019
Journal Name
Journal Of Planner And Development
-تقنيات التجديد الحضري للتراث العمراني - حالة وادي مزاب
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Publication Date
Thu Mar 05 2020
Journal Name
مجلة العلوم الاقتصادية والإدارية
تقييم الاداء المنظمي مديرية ماء ميسان – دراسة حالة
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The research aims to improve the performance of the Directorate of Maysan water by reconciling the objectives of the employees of the directorate with the objectives of the Directorate itself, as well as to identify the strengths and weaknesses in the performance of the Directorate (Leadership - Individuals - Knowledge - Operations - Financial) and presented to experts and arbitrators of specialized, and the researchers have relied on the case study methodology as a descriptive approach is comprehensive analysis, and draws on more than one approach, method and scientific design, has been interviewed a number of experts in the Directorate Maysan's water Identify the weaknesses and strengths of the Directorate, the research has reached a numb

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