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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
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 Sep 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
مقارنة طرائق تقدير معلمات توزيع كاما ذي المعلمتين في حالة البيانات المفقودة باستخدام المحاكاة
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The estimation of the parameters of Two Parameters Gamma Distribution in case of missing data has been made by using two important methods: the Maximum Likelihood Method and the Shrinkage Method. The former one consists of three methods to solve the MLE non-linear equation by which the estimators of the maximum likelihood can be obtained: Newton-Raphson, Thom and Sinha methods. Thom and Sinha methods are developed by the researcher to be suitable in case of missing data. Furthermore, the Bowman, Shenton and Lam Method, which depends on the Three Parameters Gamma Distribution to get the maximum likelihood estimators, has been developed. A comparison has been made between the methods in the experimental aspect to find the best meth

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Publication Date
Wed Mar 01 2006
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
أهمية ودور و ملائمة البيانات المحاسبية في صنع و اتخاذ و ترشيد القرارات الادارية
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Publication Date
Wed Oct 08 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Elevation in surface temperature of root canals obturated with different thermoplasticized gutta-percha obturation techniques-an in vitro study
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Background: Many studies have been conducted to evaluate the effect of using a hot material in the root canal and its potential for causing damage to the tooth supporting structure. Materials and methods: thirty permanent premolars were obturated with thermoplasticized Gutta-Percha using three different obturation techniques: soft core, Thermafil, and obtura to evaluate the rise in temperature on the root surface using a multipurpose digital thermometer. Results: temperature increases was significantly greater for Obtura versus Soft core (p<0.003), not significant for Thermafil versus Soft core (p<0.087), and Thermafil versus Obtura (p<0.125). Conclusions: temperatures rise on the root surface were below the critical level and, therefore, s

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
Inverting Gravity Data to Density and Velocity Models for Selected Area in Southwestern Iraq
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The gravity method is a measurement of relatively noticeable variations in the Earth’s gravitational field caused by lateral variations in rock's density. In the current research, a new technique is applied on the previous Bouguer map of gravity surveys (conducted from 1940–1950) of the last century, by selecting certain areas in the South-Western desert of Iraqi-territory within the provinces' administrative boundary of Najaf and Anbar. Depending on the theory of gravity inversion where gravity values could be reflected to density-contrast variations with the depths; so, gravity data inversion can be utilized to calculate the models of density and velocity from four selected depth-slices 9.63 Km, 1.1 Km, 0.682 Km and 0.407 Km.

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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Knowledge value added methodology between theory and application Comparative filed research in some of the Iraqi private banks
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Abstract

        The research to have a clear perceptions about the knowledge value added to assess the knowledge resources of the Iraqi private banks, depending on the value added methodology of the proposed defined (Housel & Bell, 2001), which assumes that the  knowledge value added come through synergetic relationship between knowledge resource and information technology, trying to the possibility of mainstream theory and its application in the Iraqi environment and interpretation of results, and on this basis was launched search of a research problem took root synergetic nature of the relationship between knowledge (human)  resource and

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Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Problems Facing University Students in Distance Learning
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The current study aims to examine the level of problems faced by university students in distance learning, in addition to identify the differences in these problems in terms of the availability of internet services, gender, college, GPA, interactions, academic cohort, and family economic status. The study sample consisted of (3172) students (57.3% females). The researchers developed a questionnaire with (32) items to measure distance learning problems in four areas: Psychological (9 items), academic (10 items), technological (7 items), and study environment (6 items). The responses are scored on a (5) point Likert Scale ranging from 1 (strongly disagree) to 5 (strongly agree). Means, standard deviations, and Multivariate Analysis of Vari

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