The forecast of pertinent project information, such as project costs, resource allocation, test case estimation and true software cost, is often needed early in the software development life cycle. Numerous sizing estimation models do exist to assist with obtaining (his type of data and currently the defacto standardization is the Function Point Analysis (FPA) model. This paper proposes an enhancement to FPA, referred to as the Function Point Environmental Analysis (FPEA), (0 address a specific FPA weakness identified by many experts within the field of software metrics. The component of the FPA model being questioned is the current estimation procedure of general system characteristics (GSC). It has been reported that the use of general system characteristics (GSC) within the FP A model does not add additional prediction accuracy to the unadjusted function point (UFP) count. By integrating environmental factors with GSCs, the UFP count could result in a more precise estimation procedure. If integrated successfully, this improvement will better equip information technology (IT) professionals to evaluate, plan, manage and control software production. The validation method of this proposal consists of a comparison of output from both the FP A and FPEA models obtained early within the software development life cycle

Literature indicates clear evidence that women are underrepresented in computer related fields of study and professions. This gender inequity can be attributed to women's lack of interest and participation in the use of technology (American Association of University Women, 2000). Since males and females display a similar interest in technology during their early school years, it is perplexing that such a large gender gap exists by high school (Oliveri, 2004). One of the major factors influencing technology acceptance is self-efficacy toward computing (Emurian, 2004). The purpose of this study was to investigate the role that a computer-enhanced curriculum played in influencing female students' self-efficacy beliefs toward computing. Literature indicates that female students enjoy working on tasks that are interdisciplinary in nature. This is especially true with regards to technology (Margolis & Fisher, 2003). If the computer-enhanced curriculum is linked to other subject areas, it is more likely to be appealing to young women (Clark, 2003). Traditional computer courses are typically taught as an isolated curriculum. If female students can understand that technology can be used for more than just programming, they may be more apt to become actively involved and increase their self-efficacy beliefs. The results of this study demonstrated that female students who participated in an integrated approach to computing had significantly higher self-efficacy beliefs toward computing than students who participated in a traditional computer class. The students using the integrated model of instruction became more engaged with technology. The female students in this group enjoyed learning about computers and developed confidence needed to complete technology tasks. The results of this study offer a possible solution for changing female students' decisions to enroll in computer courses.

The Electronic Classroom (ECR), developed at Nova Southeastern University and first used in 1985, was an inexpensive solution to the need for a real-time distance learning classroom, with rich functionality. However, its command-based interface placed requirements on students and instructors that reduced satisfaction. It was hypothesized that the implementation of a graphical user interface (GUI) for the ECR could help solve many of these problems. There is evidence that GUIs may improve the effectiveness of participants, including students, in collaborative tasks. However, this effectiveness depends on the quality of the user interface design. Recently a number of inexpensive GUI-based desktop teleconferencing products have appeared. However, preliminary evaluation of several of these products suggested that they would not meet the needs of students and faculty for the next-generation ECR. The goal of the researcher in this dissertation was to design a prototype for the graphical user interface component of an electronic classroom application. The first step was to analyze user needs and requirements. At the same time, this study included a competitive analysis of both existing products and existing technologies used by distance learning institutions. Results from the requirements step, the competitive analysis step, and an evaluation of a product called CompaLearn Manager were used to produce a mock-up for the user interface. A user evaluation was conducted, and modifications to the mock-up were identified. Two iterations of user evaluations and modifications to the mock-up were performed. Based on the mock-up evaluations, a web-based prototype was produced for the main electronic classroom window using the Java language. Then a usability test was conducted using the prototype. The feasibility of implementing the design in Java was demonstrated. Preliminary evidence suggested that the GUI-based prototype was easier to use than the next-generation ECR. This study resulted in several recommendations for the next generation ECR, such as the need to include a whiteboard. The results suggest that the proposed product design fills a niche for distance learning institutions like NSU that is not filled by other products.

The purpose of this investigation was to measure the direction community colleges across the United States and Canada have been taking in the development of technology based facilities and how the evolutional changes in the use and access of computers, multimedia, video and information resources for education has had an impact on facility development. To gain an insight on technology based facilities remodeling and/or development, an instrument of forty questions was developed and mailed to the facility offices and technology developers at the fifty-five (N=55) community colleges that are members of the League for Innovation in the Community College. The thirty-four (34) responses from the survey were tabulated using a Modified-Delphi Technique to determine a consensus of direction on seven conceptual issues: facility function, funding, human resources, educational activities, equipment, benefits and critical issues. The results of the investigation suggested: I) developing facilities for broad use; 2) the design for most new facilities should consider future modification possibilities; 3) there is an insignificant change in the number of newly constructed or planned joint-use, multipurpose technology based facilities; 4) most institutions fund technology at a rate between 5% and 9% of the institutions total operating budget; 5) there is no common strategy for developing the human resources needed for new facilities; 6) almost all community colleges do not require any form of technology literacy for employees; 7) the most innovative facilities developed include: open curriculum support centers, joint use facilities, computer courtyards, expanded libraries, instructional learning centers, facilitated learning centers, and technology support centers; 8) most community colleges have strategic plans and operational plans to support them; 9) very few empirical studies have been conducted at community colleges on the value of technology based facilities; and, 10) only two-thirds of facility development projects are based on using new methods of instruction or learning paradigms.

Educators, legislators, parents, and others with a stake in public education need reliable evidence that the investment of time and money in instruction with technology results in measurable gains leading to higher student achievement. Students making the transition from elementary to middle school are especially sensitive to changes in the learning environment and are at risk for school failure. This study investigated the relationships between student participation in elementary self-contained fifth grade multimedia classrooms and achievement and adjustment to the middle school setting. Grade point averages, average daily attendance, and scores on a standardized achievement test were compared for students attending multimedia fifth grade classrooms and all other students after the transition to sixth grade at one middle school in Orlando, Florida. Findings were compared using a one-tailed independent t-test for independent samples, and the Mann Whitney U-test, the non-parametric analogue of the t-test for data sets which are not normally distributed. Two surveys of student technology use and satisfaction with learning in a technology rich environment were administered. Sixth grade teachers were also surveyed about their levels of use and comfort with teaching with technology. Although the means for grade point averages, average daily attendance, and selected subtests of the Stanford-8 Achievement Test were higher for the students attending multimedia fifth grades, the results were not statistically significant. Student survey results were discussed, which indicated that students valued opportunities to use technology and were motivated to complete learning tasks that involved technology. The small number of middle school teachers who were surveyed indicated that while their interest in using technology in the classroom was high, the average 50-minute class period was too short to accomplish much with technology. Additional studies were recommended, to include studies that defined more clearly the conditions in which technology is used to support effective and efficient learning and problem solving.

Web applications are collections of files for the purpose of responding to user requests in client-server mode over the World Wide Web. Most web applications have a connection to one or more databases for storing and delivering data as required by user requests. Some include a web server extension. There are a number of such systems, each belonging to a set of archetypes. Important factors in selecting a web application include conformance to principles of software engineering, ability to enforce application-level security, and resource conservation or high performance. Existing experimental studies do not provide the required data, owing to variations in configuration, aggregated, statistically mixed workloads, and lack of numerical performance criteria for the application alone. This research gained important insights from the application of scientific methods and numerical, objective criteria to the comparison of web applications. This project conducted architectural analyses, security tests and performance measurements of selected archetypes. This work assessed state saving, separation of concerns, security and performance with standardized tests administered in an invariant environment, i.e., host hardware, operating system, web server and database server. Architectural analysis was applied to state maintenance and separation of concerns. Interactive simulations tested abilities of archetypes to enforce security and to protect themselves from hacker attacks. Automated load tests measured resources consumed and application latency as a function of HTML request traffic. HTML page requests consisted of a standard set of queries against the same dataset. A load test application was developed to manage the testing and data-recording automatically. Results consist of rankings of web application archetypes according to a metric developed for this purpose. Supporting data consist of graphs of latency vs. time and page request traffic vs. resources consumed. Results show the capability of archetypes to enforce security, maintain data integrity, conserve server resources, and to make timely and efficient delivery of client-requested data

Computer network attacks seek to achieve one or more objectives against the targeted system. The attack may be designed to gain access to sensitive data, modify records, or conduct activities designed to deny authorized users access to system resources. An effective defense against these incidents requires both the timely and accurate detection of the events and a response to the incident that mitigates the damage caused by the attack. While there is an increasing need for a system capable of accurately identifying network attacks there are very few effective methods capable of detecting these incidents. The constantly changing nature of network attacks requires a flexible defensive system that is capable of analyzing the enormous amount of network traffic and identifying attacks from the available data. The ability to effectively respond to an attack after it has been detected is also very limited. As a result, a rapid and well-organized attack can result in substantial damage to a targeted system before defensive measures can be activated. The goal of this research was the design of an innovative approach to the protection of computer networks that used adaptive neural network techniques to identify and respond to attempts to deny authorized users access to system resources. Since it is impossible to represent all of the possible system states and types of attacks that could occur the ability of the neural network-based system to adapt to changes in the network environment depended upon an incremental learning capability that was developed as part of this research. The adaptive neural network system incorporated a modified reinforcement learning approach to enhance the identification of new network attacks. This capability allowed the intrusion detection system to autonomously improve its analytical ability in response to changes in the threats against the protected network and then take an action that minimized the damage to the protected system. A prototype adaptive neural network architecture was implemented and evaluated in a simulated computer network environment.

Computation of marginal probabilities in Bayesian Belief Networks is central to many probabilistic reasoning systems and automatic decision making systems. The process of belief updating in Bayesian Belief Networks (BBN) is a well-known computationally hard problem that has recently been approximated by several deterministic algorithms and by various randomized approximation algorithms. Although the deterministic algorithms usually provide probability bounds, they have exponential runtimes. Some of the randomized schemes have a polynomial runtime, but do not exploit the causal independence in BBNs to reduce the complexity of the problem. This dissertation presents a computationally efficient and deterministic approximation scheme for this NP-hard problem that recovers approximate posterior probabilities given a large multiply connected BBN. The scheme presented utilizes recent work in belief updating for BBNs by Santos and Shimony (1998) and Bloemeke (1998). The scheme employs the Independence-based (IB) assignments proposed by Santos and Shimony to reduce the graph connectivity and the number of variables in the BBN by exploiting causal independence. It recovers the desired posterior probabilities by means of Netica™, a commercially available application for Belief Networks and Influence Diagrams.

Tactical asset allocation (T AA) is an investment strategy that switches an investment among different types of asset classes such as stocks, bonds or cash. The strategy consists of identifying the assets with the best performance potential within a defined short period of time. Artificial neural networks (ANN) have been successfully used to model nonlinear systems such as stock and bond price series. ANN have been used to forecast stock and bonds prices. The goal of most investment managers is to beat the market. This means to outperform an index representative of a specific overall market. The objective of T AA is to switch an investment to the asset class that will yield the best performance during the upcoming period. The success of TAA depends on the accuracy of the prediction of which asset class will yield the best performance. The purpose of this dissertation project was to investigate the effectiveness of artificial neural networks in forecasting the probability that one asset class would outperform two others by the end of a 30-day period. The asset classes considered were stocks, bonds and money market in the United States. An ANN was trained with fundamental and technical historical data. ANNs with different topologies were trained before arriving at an optimal configuration. A three-layer feedforward neural network offered the lowest generalization error. The selected ANN was trained to forecast the probabilities of each of the three investment asset classes outperforming the other two. With the forecast probabilities two TAA portfolios were created. The first portfolio was 100% invested on the asset class with the highest probability of outperforming the other two. The second portfolio followed a risk-neutral tactical asset allocation strategy based on the forecast probabilities. The accumulated returns at the end of the test period were compared to four benchmarks that represented buy-and-hold strategies. The first T AA portfolio outperformed all benchmarks. The risk-neutral portfolio outperformed all but the accumulated returns of the S&P500 index. The tests proved that an ANN is effective in forecasting the probabilities of one asset class outperforming others. Also, the results were used to create portfolios that outperformed the benchmarks.

This research provides an advance in the application of wireless, ad hoc networks to the domain of distributed, real-time applications. Traditionally, wireless communications are not deployed within real-time systems, the attributes of wireless protocols tend to run counter to the temporal requirements of real-time systems. When wireless protocols have been used in real-time systems, the application tends to be limited to systems for which there exists a priori knowledge of the network structure or the network communication. This research provides a model (or methodology) for evaluating the extent by which Bluetooth supports deterministic communication, thus allowing system engineers the ability to validate Bluetooth's ability to support real-time deadlines within software applications based on asynchronous communication. This research consisted primarily of an evaluation of the applicability of Bluetooth protocols to asynchronous real-time communication. The research methodology consisted of three distinct stages of research and development. The first stage of the study comprised the development of an analytical model describing the expected behavior of Bluetooth's ACL transmissions and the ability of ACL data packets to meet real-time deadlines. During the second stage of the study, the focus turned to the implementation of the Bluetooth HCI and L2CAP protocol layers. This implementation served as a test harness to gather actual performance data using commercial Bluetooth radios. The final stage of the study consisted of a comparative analysis of the predicted behavior established during the first stage of the study and the actual behavior experienced using the Bluetooth implementation from the second stage of the study. The analysis demonstrates the effectiveness of the model (from the first stage) by measuring the model's ability to accurately predict a piconet's ability to meet real-time deadlines for asynchronous communication when measured at the HCI-L2CAP protocol layer boundary.