Technological innovations

The design and construction of a tri-cable, planar robotic device for use in neurophysical rehabilitation is presented. The criteria for this system are based primarily on marketability factors, rather than ideal models or mathematical outcomes. The device is designed to be low cost and sufficiently safe for a somewhat disabled individual to use unsupervised at home, as well as in a therapist's office. The key features are the use of a barrier that inhibits the user from coming into contact with the cables as well as a "break-away" joystick that the user utilizes to perform the rehabilitation tasks. In addition, this device is portable, aesthetically acceptable and easy to operate. Other uses of this system include sports therapy, virtual reality and teleoperation of remote devices.

The design and construction of a tri-cable, planar robotic device for use in neurophysical rehabilitation is presented. The criteria for this system are based primarily on marketability factors, rather than ideal models or mathematical outcomes. The device is designed to be low cost and sufficiently safe for a somewhat disabled individual to use unsupervised at home, as well as in a therapist's office. The key features are the use of a barrier that inhibits the user from coming into contact with the cables as well as a "break-away" joystick that the user utilizes to perform the rehabilitation tasks. In addition, this device is portable, aesthetically acceptable and easy to operate. Other uses of this system include sports therapy, virtual reality and teleoperation of remote devices.

Individuals throughout time have had a desire to reach beyond their surrounding intellectual and physical environment and explore new territories. Throughout their lives they have continually acquired knowledge. Technology is the application of this knowledge to solve problems. As the knowledge base of humankind has grown at an exponential rate, the presence of technology has also grown. Today technology has surpassed controls and is moving at a rampant rate of speed permitting the introduction of new levels of knowledge in all different layers of society. This, however, permits the creation and expression of new thoughts without the acquisition of previously required knowledge. Creativity is progressing rapidly without controls and the objects being created are somewhat questionable.

This dissertation integrates knowledge from consumer behavior, diffusion research, strategy and MIS to investigate the effects of information cues such as price, brand equity, and technology on buyers' service evaluations and behavioral intentions. Specifically, the effects of these information cues on buyers' perceptions of service quality, value and purchase intentions are examined. In addition, this study examines the role of two intervening variables, namely, sacrifice (monetary costs) and ease of use (non-monetary costs) in buyers' service evaluations. Two interactive services, a home banking service (Citibank & Ameritech) and a home shopping service (Time Warner) were described in a concept test format to subjects in a 4 x 2 x 2 between-subjects factorial design experiment. The sample for the home banking service (281) was composed of undergraduate students drawn from the university while the sample for the home shopping service (409), was composed of individuals living in the South Florida area. The experimental treatments, manipulation checks, dependent and intervening variables were measured using multiple-item seven point Likert-type scales. The data was analyzed using econometric modeling techniques. In both experiments, service quality perceptions were found to be significantly influenced by technology and brand equity perceptions. Brand equity was the main determinant of service quality in both experiments. Service value perceptions were driven by direct effects from service quality, sacrifice and ease of use and indirectly driven by technology and price perceptions. The role of brand equity in value perceptions is ambiguous. Sacrifice was related positively to price perceptions in both studies. Purchase intentions were explained only by value perceptions in both studies. The results suggest that service quality and service value are very different. The value function is more complex than service quality. Service organizations that attempt to create customer value by maximizing service quality ratings at the lowest price need to emphasize other value based determinants such as technology and ease of use. The model suggests a crossfunctional approach should be employed for service design and development in order to maximize service quality and customer value. In addition, this study recommends a substantive pre-launch service concept development and delivery effort by service organizations before introducing new services.

This dissertation presents the results of research that led to the development of a novel reputation and trust-based monitoring paradigm for secure and reliable computing in Wireless Sensor Networks (WSNs). WSNs have undergone tremendous technological advances over the last few years. They have caused a giant leap toward "proactive computing," a paradigm where computers anticipate human needs and, when necessary, act on their behalf. Therefore, we cannot deploy such a critical technology without first addressing the security and privacy challenges to ensure that it does not turn against those whom it is meant to benefit. The core application of WSNs is to detect and report events, be it military or civilian applications. The building blocks of a WSN are small, battery-powered, lowcost, self-contained devices called "sensors" that measure factors like light, temperature, pressure, vibration, motion, etc. A WSN usually consists of hundreds of thousands of sensors that operate in unattended, hostile territories to monitor a given geographical area. Once deployed, the wireless sensors self-organize into ad-hoc wireless networks in order to cope with the dynamics of the surveillance field. During the post deployment phase, the wireless sensors aggregate data, then process and generate a report, which is subsequently relayed from one sensor to the next using secure multi-hop routing until the data reaches its desired destination, which is usually the sink. Since sensors operate in unattended and hostile territories, the adversary can capture a sensor node physically and extract all the information stored onboard, including cryptographic keying material. With this unique situation, WSNs are subject to a unique attack referred to as an "Insider Attack," in which the adversary becomes a legitimate member of the network being represented by the captured node.

This research addresses communication security in the highly constrained wireless sensor environment. The goal of the research is twofold: (1) to develop a key management scheme that provides these constrained systems with the basic security requirements and evaluate its effectiveness in terms of scalability, efficiency, resiliency, connectivity, and flexibility, and (2) to implement this scheme on an appropriate routing platform and measure its efficiency.

Machine learning techniques allow useful insight to be distilled from the increasingly massive repositories of data being stored. As these data mining techniques can only learn patterns actually present in the data, it is important that the desired knowledge be faithfully and discernibly contained therein. Two common data quality issues that often affect important real life classification applications are class noise and class imbalance. Class noise, where dependent attribute values are recorded erroneously, misleads a classifier and reduces predictive performance. Class imbalance occurs when one class represents only a small portion of the examples in a dataset, and, in such cases, classifiers often display poor accuracy on the minority class. The reduction in classification performance becomes even worse when the two issues occur simultaneously. To address the magnified difficulty caused by this interaction, this dissertation performs thorough empirical investigations of several techniques for dealing with class noise and imbalanced data. Comprehensive experiments are performed to assess the effects of the classification techniques on classifier performance, as well as how the level of class imbalance, level of class noise, and distribution of class noise among the classes affects results. An empirical analysis of classifier based noise detection efficiency appears first. Subsequently, an intelligent data sampling technique, based on noise detection, is proposed and tested. Several hybrid classifier ensemble techniques for addressing class noise and imbalance are introduced. Finally, a detailed empirical investigation of classification filtering is performed to determine best practices.

Fidgeting and otherwise constant movements in individuals can be beneficial in those who suffer from Attention Deficit/Hyperactivity Disorder or Generalized Anxiety Disorder as well as others. However this constant movement can also be a distraction to others as well as protrude an air of no self confidence. It is the drawbacks from these actions that we wish to address. By developing an intelligent system that can detect these motions and alert the user, it will allow the wearer of the device to self correct. It is in this self control that one may exhibit more confidence or simply reduce the level of irritation experienced by those in the immediate vicinity. We have designed and built a low cost, mobile, lightweight, untethered, wearable prototype device. It will detect these actions and deliver user selectable biofeedback through a light emitting diode, buzzer, vibromotor or an electric shock to allow for self control.

Research, tests and analysis are presented on several reinforcements placed in the asphalt overlay of a roadway built over soft organic soils. Non-destructive Evaluation (NDE) methods and statistical analysis were used to characterize the pavement before and after rehabilitative construction. Before reconstruction, falling weight deflectometer, rut and ride tests were conducted to evaluate the existing pavement and determine the statistical variability of critical site characteristics. Twenty-four 500ft. test sections were constructed on the roadway including sixteen reinforced asphalt and eight control sections at two test locations that possessed significantly different subsoil characteristics. NDE tests were repeated after reconstruction to characterize the improvements of the test sections. Test results were employed to quantify the stiffness properties of the pavement based on load-deflection data to evaluate the relative performance of the reinforced sections. Statistical analysis of the data showed the stiffness of the reinforced sections was consistently higher than the control sections.

Radar rainfall estimates have become a decision making tool for scientists, engineers and water managers in their tasks for developing hydrologic models, water supply planning, restoration of ecosystems, and flood control. In the present study, the utility of a power function for linking the rain gauge and radar estimates has been assessed. Mean daily rainfall data from 163 rain gauges installed within the South Florida Water Management District network have been used and their records from January 1st, 2002 to October 31st, 2007 analyzed. Results indicate that the power function coefficients and exponents obtained by using a non-linear optimization formulation, show spatial variability mostly affected by type of rainfall events occurring in the dry or wet seasons, and that the linear distance from the radar location to the rain gauge has a significant effect on the computed values of the coefficients and exponents.