In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.
The Islamic Banks including the Iraqi ones are often resorted to support their governance frameworks in order to improve its competitiveness in their communities. Where, those banks are looking for activities that enhance their governance; one of these activities is Shariah Audit that provided the auditing capabilities to face of developmental challenges and increase competitiveness. Therefore, the content of this paper, discusses know-how to use the Shariah Audit and its references in support of the Shariah Governance in the Iraqi Isla
... Show MoreIn this study, silver-tungsten oxide core–shell nanoparticles (Ag–WO3 NPs) were synthesized by pulsed laser ablation in liquid employing a (1.06 µm) Q-switched Nd:YAG laser, at different Ag colloidal concentration environment (different core concentration). The produced Ag–WO3 core–shell NPs were subjected to characterization using UV–visible spectrophotometry, X-ray diffraction (XRD), transmission electron microscopy (TEM), energy-dispersive spectroscopy, electrical analysis, and photoluminescence PL. The UV–visible spectra exhibited distinct absorption peaks at around 200 and 405 nm, which attributed to the occurrence of surface Plasmon reson
Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or
... Show MoreIn this research we study a variance component model, Which is the one of the most important models widely used in the analysis of the data, this model is one type of a multilevel models, and it is considered as linear models , there are three types of linear variance component models ,Fixed effect of linear variance component model, Random effect of linear variance component model and Mixed effect of linear variance component model . In this paper we will examine the model of mixed effect of linear variance component model with one –way random effect ,and the mixed model is a mixture of fixed effect and random effect in the same model, where it contains the parameter (μ) and treatment effect (τi ) which has
... Show MoreLongitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.
In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.
The longitudinal balanced data profile was compiled into subgroup
... Show MoreAutomatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t
... Show MoreThe objective of the study is to study how to employ performance evaluation in achieving organizational integrity and the impact of performance evaluation on achieving organizational integrity. In light of this, the following questions were raised:
Are the dimensions of organizational integrity available in the field in question?
In order to answer the research questions, a questionnaire questionnaire was distributed to the sample of 30 members of the teaching staff at the Technical Institute in Mosul. The three-dimensional Lycert scale was used. The statistical methods were used, ie, the frequency distribution, the computational circles, the standard deviations, Pearson), simple
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