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.

Abstract:

   The problem of poverty is one of the most important development challenges facing developing countries including Sudan for several decades. Although many efforts have been made to reduce poverty, however, its rates are increasing, and public policies adopted by the government in this regard remain elusive in achievinging its main objectives or making any significant progress. The purpose of the present study is to analyse poverty in Sudan by identifying its measurement, causes and the factors that have contributed to the increasing poverty rates over the past two decades. Also this study aims at investigating the interim poverty reduction strategy in Sudan as well as evaluates that strategy throug

        Throughout this paper, three concepts are introduced namely stable semisimple modules, stable t-semisimple modules and strongly stable t-semisimple. Many features co-related with these concepts are presented. Also many connections between these concepts are given. Moreover several relationships between these classes of modules and other co-related classes and other related concepts are introduced.

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

The current research is concerned with the prices of Goods and materials in the Iraqi slang a descriptive, lexicographic , and semantic study expressing the meanings of these names and their positions , as well as expressing the imaginations of Human mind , the popular mind in describing these goods with evaluating them besides the semantic of each word accordingly
The current research is divided into two parts , the first part is consisted of Vocalizations" words" That are arisen through cognitive naming that concentrate on the mental imaginations for the most important and sensitive such as colors , taste , shapes and forms impacts of Goods and materials according to users' ' taste for those words , on other hand, the second part of

STAG3 is the meiotic component of cohesin and a member of the Cancer Testis Antigen (CTA) family. This gene has been found to be overexpressed in many types of cancer, and recently, its variants have been implicated in other disorders and many human diseases. Therefore, this study aimed to analyze the major variants of STAG3. Western blot (WB) and immunoprecipitation (IP) assays were performed using two different anti-STAG3 antibodies that targeted the relevant protein in MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 breast cancer cells with Jurkat and MCF-10A cells as positive and negative controls, respectively. In silico analyses were searched to study the major isoforms. WB and IP assays revealed two abundant polypeptides < 191 kDa and

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