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Master students in the Information Technology Degree Program at SPSU complete a Thesis as part of their graduation requirements. Below are select Thesis abstracts from our graduates.
By Donna R. Hutcheson
December, 2004
Business organizations have embraced Knowledge Management (KM) for the last several years as a way to remain competitive and viable in an ever-changing global marketplace. Higher Education has begun to move toward a more formal knowledge management structure.
The author examined the relationship between KM and organizational culture and the how organizational learning might influence the KM endeavor. This thesis considers Kennesaw State University (KSU), and how the concepts of KM are being addressed. The Chief Information Officer at KSU uses KM and organizational learning as the basis for organizational change and decision-making within his unit. This methodology has proven to provide a solid foundation on which to make decisions and document organizational memory. Assessment results and recommendations for change should be made widely and easily accessible to constituents as evidence of continuous improvement for accreditation procedures, national association activities, governance structures, quality improvement initiatives, and program review. It is the author's hope that the reader of this thesis will have a better understanding of KM and organizational learning in general, but especially as these concepts apply to higher education.
By Abdul- Lateef Yussiff
Dr. Patrick Bobbie, Advisor
August, 2004
The widespread use of wide-range Wireless-based Local Area Network (WLAN) and its counterpart, the short-range Bluetooth piconet, has put a tremendous pressure on designers of wireless protocols to assure fidelity and reliability within the freely available 2.4 GHz Industrial Scientific and Medical (ISM) bandwidth. The proximity of wireless devices with one another often results in interference in the unlicensed 2.4 GHz ISM bandwidth. Interference has been recognized as a major problem in estimating signal power at a particular distance from the transmitter for wireless network performance and improvement. Also due to stochastic behavior of the wireless medium, interference has become a major problem in formulating a general mathematical model for radio channel estimation. Research techniques often combine empirical and analytical techniques to model radio channels.
The thesis focuses on developing an Interference Range Model (IRM), a set of equations for determining the acceptable range of interference in a given environment. Interference is directly related to the transmission signal power-a high signal power increases the probability of interference among signals using the same frequency band. Signal power is the signal strength at a particular point in time. Related to interference is path loss - the rate at which the transmitted signal power decreases with distance. The estimation of path loss is therefore critical since it embraces the signal power and acceptable distance of separation or range of interference. Also path loss is a function of different environments, and its estimation depends on the environment the signal is passing through. To include the effect of environments, we included different environmental conditions in the IRM for the analysis of path loss. A simulation tool set was developed in a Java environment for modeling, simulating, and analyzing path loss and acceptable/cutoff ranges of interference based on the IRM.
By Vaisheshi Jalajam
August, 2003
Businesses both large and small have been accumulating data about customers, about products, services, sales, discounts and supply-chain facilitation etc. so as to generate meaningful information and re-use it profitably. Information systems have worked with various issues concerning data such as efficient data storage, data consistency, reducing redundancy, and handling large volumes of data. However, analyzing data has always been challenged by various factors such as dispersed location of data, diversity of data formats etc. Data warehouse methodology has provided a solution to the challenges imposed by the availability of data for analytical purposes. As an environment a data warehouse has in itself the ability to extract data, transform it and provide a framework for analytical reasoning.
I decided to explore this environment, trace its best prospects and its weaknesses. In this process, I realized the success of data warehousing depended on its unique data modeling structure known as dimensional modeling. Dimensional modeling methodology visualized and modeled the data in terms of business dimensions. This model worked on the constraints that the Entity Relationship model imposed. Therefore, this thesis attempts to distinguish and highlight the different areas that these most popular data modeling techniques have to offer. It is with this twin objective that I began exploring this field:
This work presents the complete overview of data warehouse environment. It discusses the differences between the traditional transactional processing and the new dynamic multi-dimensional analytical processing with a comparison of entity relationship approach and the dimensional approach. This work also discusses the two popular reporting techniques known as Online Analytical Processing and Data mining.
The work can be divided into three distinct parts:
This work began with a hypothesis that data warehouse environment is a critical for today's analytical processing needs and secondly, it believes that dimensional model is more suitable for a data warehouse rather than an entity relationship model.
The study revealed that data warehouse in fact is growing in popularity in all sectors of industries and that most data warehouses are built on the dimensional model.
Comments and suggestions: Please contact 678-915-4292 or jwang@spsu.edu.
