South African Computer Journal - Volume 49, Issue 1, 2012
Volumes & issues
Volume 49, Issue 1, 2012
Strategic business-IT alignment of application software packages : bridging the information technology gapAuthor Wandi KrugerSource: South African Computer Journal 49, pp 1 –11 (2012)More Less
An application software package implementation is a complex endeavour, and as such it requires the proper understanding, evaluation and redefining of the current business processes of an organisation to ensure that the implementation delivers on the objectives set at the start of the project.
Numerous factors exist that may contribute to the unsuccessful implementation of application software packages. However, the most significant contributor to the failure of an application software package implementation lies in the misalignment of the organisation's business processes with the end functionality of the application software package implemented. Misalignment is attributed to a gap that exists between the business processes of an organisation and the functionality the application software package has to offer to translate the business processes of an organisation into digital form when implementing and configuring an application software package. This gap is commonly referred to as the information technology (IT) gap.
Based on an extensive literature study, this article proposes to define and discuss the IT gap that specifically exists between the business processes of an organisation and application software packages acquired from a software supplier. Furthermore, this article makes recommendations for aligning the business processes of an organisation with the functionality of the application software package implemented. The end result of adopting these recommendations will be more successful application software package implementations for organisations.
Source: South African Computer Journal 49, pp 12 –24 (2012)More Less
Social networking sites are extremely popular online destinations that offer users easy ways to build and maintain relationships with each other, and to disseminate information in an activity referred to as social networking. Students, lecturers, teachers, parents and businesses, in increasing numbers, use tools available on social networking sites to communicate with each other in a fast and cost-effective manner. The use of social networking sites to support educational initiatives has received much attention. However, the full potential of social network sites has yet to be achieved as users continue to strive for optimal ways of using these sites, as well as battle to overcome the negative characteristics (for example, privacy, security, governance, user behaviour, information quality) of these sites. This paper proposes factors for successful use of social networking sites in higher educational institutions. These success factors need to be adopted by users in order to develop the positive aspects of social networking, while at the same time mitigating the negative characteristics. An initial set of factors for successful use of social networking sites, as well as measures to test successful use of social networking sites were derived from the literature. These factors were tested by means of an online survey of students at a university, the results of which informed the final factors for successful use of social networking sites. The factors enable users to overcome the negative characteristics associated with social networking sites. If used successfully, social networking sites can offer lecturers and students a useful tool with which to develop their relationship and contribute to their learning experience.
Author Nelishia PillaySource: South African Computer Journal 49, pp 25 –34 (2012)More Less
Sudoku is a logical puzzle that has achieved international popularity. Given this, there have been a number of computer solvers developed for this puzzle. Various methods including genetic algorithms, simulated annealing, particle swarm optimization and harmony search have been evaluated for this purpose. The approach described in this paper combines human intuition and optimization to solve Sudoku problems. The main contribution of this paper is a set of heuristic moves, incorporating human expertise, to solve Sudoku puzzles. The paper investigates the use of genetic programming to optimize a space of programs composed of these heuristics moves, with the aim of evolving a program that can produce a solution to the Sudoku problem instance. Each program is a combination of randomly selected moves. The approach was tested on 1800 Sudoku puzzles of differing difficulty. The approach presented was able to solve all 1800 problems, with a majority of these problems being solved in under a second. For a majority of the puzzles evolution was not needed and random combinations of the moves created during the initial population produced solutions. For the more difficult problems at least one generation of evolution was needed to find a solution. Further analysis revealed that solution programs for the more difficult problems could be found by enumerating random combinations of the move operators, however at a cost of higher runtimes. The performance of the approach presented was found to be comparable to other methods used to solve Sudoku problems and in a number of cases produced better results.
A heuristic image search algorithm for Active Shape Model segmentation of the caudate nucleus and hippocampus in brain MR images of children with FASDSource: South African Computer Journal 49, pp 35 –53 (2012)More Less
Magnetic Resonance Imaging provides a non-invasive means to study the neural correlates of Fetal Alcohol Spectrum Disorder (FASD) - the most common form of preventable mental retardation worldwide. One approach aims to detect brain abnormalities through an assessment of volume and shape of two sub-cortical structures, the caudate nucleus and hippocampus. We present a method for automatically segmenting these structures from high-resolution MR images captured as part of an ongoing study into the neural correlates of FASD.
Our method incorporates an Active Shape Model, which is used to learn shape variation from manually segmented training data. A modified discrete Geometrically Deformable Model is used to generate point correspondence between training models. An ASM is then created from the landmark points. Experiments were conducted on the image search phase of ASM segmentation, in order to find the technique best suited to segmentation of the hippocampus and caudate nucleus. Various popular image search techniques were tested, including an edge detection method and a method based on grey profile Mahalanobis distance measurement. A novel heuristic image search method was also developed and tested. This heuristic method improves image segmentation by taking advantage of characteristics specific to the target data, such as a relatively homogeneous tissue colour in target structures.
Results show that ASMs that use the heuristic image search technique produce the most accurate segmentations. An ASM constructed using this technique will enable researchers to quickly, reliably, and automatically segment test data for use in the FASD study.