Microarray data plays a major role in diagnosing and treating cancer. In several microarray data sets, many gene fragments are not associated with the target diseases. A solution to the gene selection problem might become important when analyzing large gene datasets. The key task is to better represent genes through optimum accuracy in classifying the samples. Different gene classification algorithms have been provided in past studies; after all, they suffered due to the selection of several genes mostly in high-dimensional microarray data. This paper aims to review classification and feature selection with different microarray datasets focused on swarm intelligence algorithms. We explain microarray data and its types in this paper briefly. Moreover, our paper presents an introduction to most common swarm intelligence algorithms. A review on swarm intelligence algorithms in gene selection profile based on classification of Microarray Data is presented in this paper.

The cooperation becomes an important requirement in distributed Healthcare Information Systems (HISs). It is used to provide patients with a good and fast treatment. To achieve the cooperation feature, a fractal approach has been proposed by many researchers in different areas. Also, many approaches have been proposed in cooperative HISs to share patients’ information between different healthcare centres in order to provide a good treatment. However, most of these researches did not address the required improvement on physician skills and the possible enhancement on the healthcare services. This empirical study proposes a way to adjust fractal approach in HISs in order to improve the cooperation feature among physicians which may enhance both physician skills and healthcare services. The analysis of the collected data shows there are problems that associated with current system and therefore a set of requirements have been initiated. It has been found that there is a need to adapt the fractal features in current HIS environment.

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Students' information in higher education institutions increases yearly. It is hard for them to extract meaningful information from the huge amount of data manually. Such information can support academic staff to stop students from dropping out at the end of courses. This can be done by evaluating the students' performance for the course and also by predicting their performance in the final exam early by using classification algorithms. Four classification algorithms, which are Decision Tree C4.5, Random Forest, Support Vector Machine (SVM) and Naive Bayes, were used in this research in order to classify and predict the students' performance. Furthermore, this research aimed at improving the Decision Tree C4.5 algorithm by adding a grid search function in order to improve prediction accuracy in classifying and predicting the students' performance. Also, the features of this evaluation have been extracted through the interviews with academic staff of three universities (

The strategic planning of developing any information system is the key factor of progress any organization. Hence, SWOT (Strength, weakness, opportunities and threats) analysis for the strategic planning of developing information system has proved to be a good analysis tool for further development and progress of the universities/organization. Further, the implementation of computerized student information management system has become an important issue within the university campus to exchange such information between students and staff. Many studies have developed student information system through the converting of paper-based system to computer-based system in order to facilitate the work of staff. However, none of these studies focused on the development of such systems based on the strategic planning using SWOT technique. Therefore, this research focuses on the requirements needed to develop student information system based on the aforementioned strategic planning technique. Some universities located in the Kurdistan Region, Iraq have been tacking to do the investigation. Moreover, SWOT technique was selected to find strengths, weaknesses, opportunities and threats of developing such system. The findings of this research were processed as matching strengths with opportunities and converting weaknesses or threats to strengths or opportunities. Based on the results, it has been found that the need to address student information systems is of utmost importance now more than ever in order to survive and continue in the competition environment.