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bsj-5928
Application of Data Mining Techniques on Tourist Expenses in Malaysia
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Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective data mining technology. Besides that, this paper implementation of 4 data mining classification techniques was experimented for extracting important insights from the tourism data set. The aims were to find out the best performing algorithm among the compared on the results to improve the business opportunities in the fields related to tourism. The results of the 4 classifiers correctly classifier the attributes were JRIP (84.09%), Random Tree (83.66%), J48 (85.50%), and REP Tree (82.47%). All the results will be analyzed and discussed in this paper.

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Physiological and Hormonal Effects of Titanium Dioxide Nanoparticles on Thyroid Function and the Impact on Bodyweight in Male Rats
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Fifty-four Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided into three subgroups each of six rats treated as follows; group (1) serve as normal control, group (2, and 3) intra-peritoneal treated with TiO2NPs (50,200) mg/kg respectively, body *weight of all rats was measured before and after the experiment, then rats were dissected at the end of each experiment and the weights of the thyroid was measured. The result showed a highly significant decrease (p<0.01) in thyroid gland weight, a highly significant increase (p<0.01) in body weights and TSH, while a highly significant decrease (p&

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of the Financial Reporting of Liabilities and Assets of Deferred Income Tax in the quality of Accounting Information
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Abstract

The research problem Focused about extent adoption of the financial reporting obligations and assets of the deferred income tax attributable to the concepts of accounting theory and whether the tax laws or accounting principles as well as local accounting rules to recognize the obligations and assets of deferred income tax in the financial statements, and what is the impact of the financial reporting of liabilities and assets Deferred tax in the quality of accounting information, and research aims to the statement of the accounting concepts of the theory of financial reporting obligations and assets of deferred income tax, view and analyze the differences in reporting, resulting from a discrepanc

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Publication Date
Tue Jun 23 2020
Journal Name
Annal S Of Tropical Medicine & Public Health
Histological Evaluation of local application of Phyllunthus amarus extracted powder and its combination with fibronectin protein on Wound Healing of rats
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Background: A wound is defined as a break or damage in the skin, resulting from physical or thermal damage or as a result of the presence of an underlying medical or physical condition. Herbal medicine can be called one of the branches of medicine in various forms.Phyllunthus amarus is a small herb well known for its medicinal properties and widely used worldwide. P. amarus is an important plant of Indian Ayurvedic system of medicine. Fibronectin is a major component of the extracellular matrix. It is secreted by various cells, primarily fibroblasts, as a soluble protein dimer and is then assembled into an insoluble matrix in a complex cell-mediated process. Materials and methods: Forty rats will be subjected for a surgical operation

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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of Exogenous Application of Nano Fertilizers and Seaweeds Extract on the Growth, Yield, and Total Alkaloids Content of Hyoscyamus niger
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Abstract<p>The study was conducted at the College of Agricultural Engineering Sciences - University of Baghdad in 2022. It aimed to improve the growth of the European black Henbane plant (<italic>Hyoscyamus niger</italic>), leaf yield, and its content of the total alkaloids as effective medicinal secondary metabolite compounds by spraying with three levels of nano-nitrogen (N=46%) and three levels of nano-potassium (K = 50%)) is 1 gm L<sup>-1</sup>, 2 gm L<sup>-1</sup>, and 3 gm L<sup>-1</sup>, respectively, for each of these fertilizers, in addition to spraying with two levels of seaweed extract (Acadian) at a concentration of 2 and 3 ml L<sup>-1</sup></p> ... Show More
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Publication Date
Mon Jul 09 2018
Journal Name
اتحاد الاحصائيين العربوقائع المؤتمر الدولي العلمي السادس لاتحاد الاحصائيين العرب
The Use of Markov Chain to reveal the reality of non- oil econ0miv indicators in Iraq
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The research mainly seeks to predict the amounts of non- oil Iraqi exports which concludes ) Food & Animals , Raw materials and non- tanned Leather and fur , Mineral fuels and Lubricating Oil , Chemical substances and amounts , Manufactured goods , Electrical and non - electrical machines , Supplies and Total non- Oil exports ) by using Markov Chain as one of Statistical approach to forecasting in future . In this search We estimate the transliteration probabilities matrix according to Maximum Likelihood on a data collected from central organization for Statistics and information technology represents an index numbers of non- Oil exports amount in Iraq from 2004 to 2015 depending on 2007 as a basic year . Results shown that trend of index

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Publication Date
Tue Feb 26 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Return Variation on Investment as a Function for the Difference of Market Share: An Applied Research on a Sample of Private Banks listed in Iraq Stock Exchange (ISX)
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    The research specified with study the relation  between the market share for the sample research banks and the amount of the achieved revenues from the investment, where the  dominated belief  that there potentiality enhancing the revenue on investment with the increase of the banks shares in their markets after their success in achieving rates of successive growth in their sales of sales and to a suitable achieve  market coverage for their products and they have dissemination and suitable  promotion activity, the  market share represented the competition  for the banks, and the markets pay attention to the  market share as a strategic objective and to maintain them also increasi

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Effect of Public Debt on The Trade Balance in Iraq For The Period (2003-2021)
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Despite the significant increase in public spending in Iraq, it was not directed toward the important sectors that have an important role in correcting the productive structure. Rather, most of the public expenditure was going to cover the required imports, or to face shocks, whether security or health, and this caused a continuous decrease in the volume of Iraq's exports of goods and services, as the aim of the study was to review the importance of public debt and its impact on the trade balance, as well as to know the economic policies that can contribute to strengthening the trade balance, as the study proved through the (ARDL) model that there is a direct relationship between the domestic debt and the net trade balance, and an invers

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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
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 Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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