This work aims to see the positive association rules and negative association rules in the Apriori algorithm by using cosine correlation analysis. The default and the modified Association Rule Mining algorithm are implemented against the mushroom database to find out the difference of the results. The experimental results showed that the modified Association Rule Mining algorithm could generate negative association rules. The addition of cosine correlation analysis returns a smaller amount of association rules than the amounts of the default Association Rule Mining algorithm. From the top ten association rules, it can be seen that there are different rules between the default and the modified Apriori algorithm. The difference of the obtained rules from positive association rules and negative association rules strengthens to each other with a pretty good confidence score.
Abstract
The current research aims to identify mental health and its role in promoting self-confidence and positive behavior of female university students. The researcher adopted the descriptive analytical approach in this research. The researcher depended on the availability of sources and references, literature, and previous field studies to analyze and study all aspects related to mental health and its role in promoting self-confidence and positive behavior of university students and then expand its importance and identify the areas of mental health, self-confidence, positive behavior, and university. The second chapter included the concept of mental health, the importance of the study, the most important factors of health and psyc
The study included evaluation of cell surface charge and hydrophobicity of Escherichia coli, Klebsilla aerogenes, Proteus spp, Bacillus cereus, Staphylococcus epidermidis, Staphylococcus aureus(1) and Staphylococcus aureus(2) were determined by hydrocarbon adherence and hydrophobic interaction chromatography. The results showed that the negative charge of cell surface of gram negative bacteria was much higher than on gram positive once when these bacteria were grown on nutrient agar at 37 c for 18 h . E.coli was more negative charged than Klebsilla aerogenes and Proteus spp. The hydrophobicity of gram positive bacteria was much
... Show MoreSeveral attempts have been made to modify the quasi-Newton condition in order to obtain rapid convergence with complete properties (symmetric and positive definite) of the inverse of Hessian matrix (second derivative of the objective function). There are many unconstrained optimization methods that do not generate positive definiteness of the inverse of Hessian matrix. One of those methods is the symmetric rank 1( H-version) update (SR1 update), where this update satisfies the quasi-Newton condition and the symmetric property of inverse of Hessian matrix, but does not preserve the positive definite property of the inverse of Hessian matrix where the initial inverse of Hessian matrix is positive definiteness. The positive definite prope
... Show MoreThe main topic of this study is central around the independence of Jordanian central bank and the extent of the effectiveness at the bank in leading the monetary policy without interferences or pressures from side of the government. the degree of independence of Jordanian central bank was based on the following based hypothesis following ,there is relationship between the independence of the central bank and the legislative and economical indices. the most important recommendations are degree of independence of the Jordan central bank 43.5% is a good one, but it possible to reach a higher degree than this one by to making some modification on the Jordanian central bank law and by the central bank should be more rigid
... Show MoreAssociation rules mining (ARM) is a fundamental and widely used data mining technique to achieve useful information about data. The traditional ARM algorithms are degrading computation efficiency by mining too many association rules which are not appropriate for a given user. Recent research in (ARM) is investigating the use of metaheuristic algorithms which are looking for only a subset of high-quality rules. In this paper, a modified discrete cuckoo search algorithm for association rules mining DCS-ARM is proposed for this purpose. The effectiveness of our algorithm is tested against a set of well-known transactional databases. Results indicate that the proposed algorithm outperforms the existing metaheuristic methods.
We have studied Bayesian method in this paper by using the modified exponential growth model, where this model is more using to represent the growth phenomena. We focus on three of prior functions (Informative, Natural Conjugate, and the function that depends on previous experiments) to use it in the Bayesian method. Where almost of observations for the growth phenomena are depended on one another, which in turn leads to a correlation between those observations, which calls to treat such this problem, called Autocorrelation, and to verified this has been used Bayesian method.
The goal of this study is to knowledge the effect of Autocorrelation on the estimation by using Bayesian method. F
... Show MoreThis research aim to exploring the positive psychological capital concept (PsyCap) which drawn from positive psychology and applying it at workplace. PsyCap emerged as extending for recent another types of capital, such as human capital and social capital. It has been defined as “an individual’s positive psychological state of development". The PsyCap consist of four core constructs (self- efficacy, optimism, hope, and resilience). Each of the four components has considerable theorizing and researching that can contribute to developing an integrative theoretical foundation for PsyCap. But their combined motivational effects will be broader and more impactful than any one of t
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Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison
... Show MoreObesity is a risk factor for a number of chronic conditions. Obesity is clinically defined using the body mass index (BMI) as weight in kg divided by (height)2 in m2 correlated with obesity. Currently, genetic markers of obesity are being studied. This study focused on the association between the angiotensin II receptor AGTR1 gene (A1166C) and fat mass and obesity-associated protein also known as alpha-ketoglutarate-dependent dioxygenase (FTO) (rs9939609) in obese children and adolescents patients in Rostov region, Russia. Five-hundreds of Russian nationality child and adolescent were recruited for the obesity-control studies. The relationship between the A1166C polymorphism of the AGTR1 gene in
... Show MoreThe background subtraction is a leading technique adopted for detecting the moving objects in video surveillance systems. Various background subtraction models have been applied to tackle different challenges in many surveillance environments. In this paper, we propose a model of pixel-based color-histogram and Fuzzy C-means (FCM) to obtain the background model using cosine similarity (CS) to measure the closeness between the current pixel and the background model and eventually determine the background and foreground pixel according to a tuned threshold. The performance of this model is benchmarked on CDnet2014 dynamic scenes dataset using statistical metrics. The results show a better performance against the state-of the art
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