Desktops, laptops, smartphones, tablets, and the Kinect, oh my! With so many devices available to the average consumer, the limitations and pitfalls of each interface are becoming more apparent. Swimming in devices, users often have to stop and think about how to interact with each device to accomplish the current tasks at hand. The goal of this thesis is to minimize user cognitive effort in handling multiple devices by creating a context aware hybrid interface. The context aware system will be explored through the hybridization of gesture and touch interfaces using a multi-touch coffee table and the next-generation Microsoft Kinect. Coupling gesture and touch interfaces creates a novel multimodal interface that can leverage the benefits of both gestures and touch. The hybrid interface is able to utilize the more intuitive and dynamic use of gestures, while maintaining the precision of a tactile touch interface. Joining these two interfaces in an intuitive and context aware way will open up a new avenue for design and innovation.

Digital painting is the field of software designed to provide artists a virtual medium to emulate the experience and results of physical drawing. Several hardware and software components come together to form a whole workflow, ranging from the physical input devices, to the stroking process, to the texture content authorship. This thesis explores an artist-friendly approach to synthesize the textures that give life to digital brush strokes. Most painting software provides a limited library of predefined brush textures. They aim to offer styles approximating physical media like paintbrushes, pencils, markers, and airbrushes. Often these are static bitmap textures that are stamped onto the canvas at repeating intervals, causing discernible repetition artifacts. When more variety is desired, artists often download commercially available brush packs that expand the library of styles. However, included and supplemental brush packs are not easily artist-customizable. In recent years, a separate field of digital art tooling has seen the popular growth of node-based procedural content generation. 3D models, shaders, and materials are commonly authored by artists using functions that can be linked together in a visual programming environment called a node graph. In this work, the feasibility is tested of using a node graph to procedurally generate highly customizable brush textures. The system synthesizes textures that adapt to parameters like pen pressure and stretch along the full length of each brush stroke instead of stamping repetitively. The result is a more flexible and artist-friendly way to define, share, and tweak brush textures used in digital painting.

The popularity of MPI-based middleware and applications has led to their wide deployment. Such systems, however, are not inherently reliable and cannot tolerate external faults. This thesis presents a novel model-based approach for exploiting application features and other characteristics to categorize and create AEMs (Application Execution Model). This work realizes MPI/FT(tm), a middleware derived by selective incorporation of fault-tolerant features into MPI/Pro(tm) for two relevant AEMs. This thesis proves the following hypothesis: it is possible to successfully complete select MPI applications even in the presence of external faults, and such fault-tolerance can be achieved with acceptable performance overhead. This work defines parameters to measure the impact of this middleware on performance through faultree and fault-injected overheads. The hypothesis is validated through experimentation and measurement of sample MPI applications for two AEMs.

This work proposes a series of driver assistance technologies that enable blind persons to safely and independently operate an automobile on standard public roads. Such technology could additionally benefit sighted drivers by augmenting vision with suggestive cues during normal and low-visibility driving conditions. This work presents a non-visual human-computer interface system with passive and adaptive controlling software to realize this type of driver assistance technology. The research and development behind this work was made possible through the Blind Driver Challenge® initiative taken by the National Federation of the Blind. The instructional technologies proposed in this work enable blind drivers to operate an automobile through the provision of steering wheel angle and speed cues to the driver in a non-visual method. This paradigm imposes four principal functionality requirements: Perception, Motion Planning, Reference Transformations, and Communication. The Reference Transformation and Communication requirements are the focus of this work and convert motion planning trajectories into a series of non-visual stimuli that can be communicated to the human driver. This work proposes two separate algorithms to perform the necessary reference transformations described above. The first algorithm, called the Passive Non-Visual Interface Driver, converts the planned trajectory data into a form that can be understood and reliably interacted with by the blind driver. This passive algorithm performs the transformations through a method that is independent of the driver. The second algorithm, called the Adaptive Non-Visual Interface Driver, performs similar trajectory data conversions through methods that adapt to each particular driver. This algorithm uses Model Predictive Control supplemented with Artificial Neural Network driver models to generate non-visual stimuli that are predicted to induce optimal performance from the driver. The driver models are trained online and in real-time with a rapid training approach to continually adapt to changes in the driver's dynamics over time. The communication of calculated non-visual stimuli is subsequently performed through a Non-Visual Interface System proposed by this work. This system is comprised of two non-visual human computer interfaces that communicate driving information through haptic stimuli. The DriveGrip interface is pair of vibro-tactile gloves that communicate steering information through the driver's hands and fingers. The SpeedStrip interface is a vibro-tactile cushion fitted on the driver's seat that communicates speed information through the driver's legs and back. The two interfaces work simultaneously to provide a continuous stream of directions to the driver as he or she navigates the vehicle. / Ph. D.

Brain Machine Interfaces (BMI) are a rapidly developing technology that raise unique ethical issues that demand review. They have demonstrated impressive restorative potential, particularly for individuals living with epilepsy, and those who are locked in. Although BMIs have the potential to provide significant benefit to millions of users, further advancement of the technology should proceed cautiously, according to the guidelines outlined in this paper. Failure to adhere to ethical guidelines could lead to severe privacy concerns, and would violate moral principles of beneficence, virtue ethics, care ethics, and utilitarianism. Despite the moral risks, BMIs hold promise for reshaping future healthcare delivery.

Parallelism can use existing technology in computer communications network design to provide higher data rates and a greater degree of flexibility than monolithic systems. This research investigates the design of a high-speed Parallel Local Area Network (PLAN) interface. It defines the goals of a PLAN interface as low data latency, high data throughput, scalability, and low cost. Three fundamental PLAN interface categories are proposed to meet these goals. These categories are single-bus, dual-bus, and bus-free adaptors. The relative merits of each category are discussed in terms of suitability to several adaptor applications. Each category is further explored by developing a VHDL model of a representative system. The latency, throughput, and component utilization of each model is measured. For medium to large data sets, the dual-bus design provides slightly greater throughput when transmitting encoded data. When transmitting medium to large unencoded data sets, the bus-free design yields marginally higher throughput. In nearly all cases the bus-free design has a greater latency than either of the bus-based design options. Other insights gained from the models regarding physical construction of each adaptor type are also presented. / Master of Science

In recent years, brain computer interfaces (BCIs) have gained popularity in non-medical domains such as the gaming, entertainment, personal health, and marketing industries. A growing number of companies offer various inexpensive consumer grade BCIs and some of these companies have recently introduced the concept of BCI "App stores" in order to facilitate the expansion of BCI applications and provide software development kits (SDKs) for other developers to create new applications for their devices. The BCI applications access to users' unique brainwave signals, which consequently allows them to make inferences about users' thoughts and mental processes. Since there are no specific standards that govern the development of BCI applications, its users are at the risk of privacy breaches. In this work, we perform first comprehensive analysis of BCI App stores including software development kits (SDKs), application programming interfaces (APIs), and BCI applications w.r.t privacy issues. The goal is to understand the way brainwave signals are handled by BCI applications and what threats to the privacy of users exist. Our findings show that most applications have unrestricted access to users' brainwave signals and can easily extract private information about their users without them even noticing. We discuss potential privacy threats posed by current practices used in BCI App stores and then describe some countermeasures that could be used to mitigate the privacy threats. Also, develop a prototype which gives the BCI app users a choice to restrict their brain signal dynamically.

The term e-Government refers to providing citizens a series of services that can be conveniently conducted over the Internet. However, the potential to redefine and transform e-Government increasingly relies on citizens successfully establishing and managing a user account profile online. E-Government has not adequately addressed user-centric designs for social inclusion of all citizens on e-Government websites. There is a lack of research on the usability of user account management, and a clear lack of innovation in incorporating user-friendly authentication interfaces to accommodate a diverse user population given the wealth of existing research in web authentication techniques within Identity Management. The problem is e-Government has no standardized approach to evaluate and compare the usability of user account interfaces to accommodate a diverse user population and encourage improvements in making user account interfaces more user-friendly and accessible to citizens online. This study proposed extending a well-established usability evaluation methodology called GOMS to evaluate e-Government security interfaces for usability. GOMS, which comprises of Goals, Operations, Methods, and Selection, was used to compare the task time users took to complete similar goals on different websites. GOMS was extended to include Security Cases, which are security related goals users desire to accomplish along with the selected link and trail necessary to satisfy those goals. An observational study was conducted to capture the task time 31 users took to complete similar Security Cases on three popular e-Government websites (DMV.CA.gov, HealthCare.gov, and USPS.com). The study initially defined a catalog of six Security Cases specific to user account management and then established benchmark time predictions for each of the Security Cases using CogTool. The six Security Cases selected were as follows: Registration, Login, Change Settings, Forgot Password, Change Password, and Logout. The task time to complete each of the six Security Case on the three websites, along with statistical analysis and CogTool’s benchmark time predications, were used to quantify and compare the usability of these three websites. In order to capture demographic data and assess participant’s satisfaction using the website, the study conducted a post evaluation survey using the System Usability Scale (SUS). The survey captured age, gender, education, user satisfaction, and computer/security knowledge for each participant to assess design considerations to accommodate a diverse population. Finally, a library of Security Cases was established to compare and highlight the more effective user account interface designs on the three selected e-Government websites. This study found task time data from similar Security Cases could be categorized and used to successfully compare and highlight more effective user account interface designs. The study revealed gender and education had no distinctions in task time when performing user account management related tasks. The study also revealed seniors took significantly longer than any other age group to complete complex user account management interfaces. Additionally, CogTool did not prove to be effective in establishing reliable task time predictions to establish as benchmarks. The study concluded the GOMS method could successfully be used to establish a set of task time metrics in a catalog of Security Cases that can be used to evaluate and compare the usability of user account interfaces to accommodate a diverse user population on e-Government websites. Future usability research should be conducted to evaluate if there is a performance relationship between age and security interface complexity. Future research should also further evaluate GOMS as a viable methodology to evaluate other security interfaces not limited to e-Government and expand upon the library of Security Cases to highlight effective security interfaces designs on other websites to accommodate a diverse user population.

Mobile technologies present an opportunity for scholars and practitioners to extend the application of instructional design theories and models to a mobile learning environment. The goal was to examine mobile learning design and development issues, validate and extend the instructional design theory, Component Display Theory (CDT), to the development of mobile learning activities, and recommend guiding principles for mobile learning system development. Using a formative research approach, which focuses on improving design theory for instructional practices and processes, CDT was used to design a tutorial mobile application targeting faculty professional development. This design instance was formatively evaluated to determine how CDT can be used to guide the design and development of a mobile learning environment; the key processes that are pertinent to translating instructional design plans into mobile learning lessons; and the challenges and issues in designing instruction for a mobile learning environment. The findings resulted in the identification of variables and factors related to the instructional strategies, design variables, and the learning system that affected the application of the CDT. Recommendations and further research opportunities are presented to increase practitioner use of the theory and to address learner and organizational readiness. This research contributes to the field of instructional design and development by examining how underlying theories, principles, and frameworks can be applied to the design and development of mobile learning systems.

Diabetes is the seventh leading cause of death in the United States. With the population rapidly aging, it is expected that 1 out of 3 Americans will have diabetes by 2050. Mobile devices and mobile applications have the potential to contribute to diabetes self-care by allowing users to manage their diabetes by keeping track of their blood glucose levels. Usability is important for systems that help people self-manage conditions such as diabetes. Age and diabetes-related cognitive decline might intensify the impact of usability issues for the users who need these mobile applications the most. As highlighted by usability researchers, the context of use (i.e. environment, user, task, and technology) has a significant impact on usability. The environment (lighting, temperature, audio and visual distractions, etc.) is of special interest to the mobile usability arena since in the case of mobile devices, is always changing. This dissertation aims to support the claim that context and more specifically environmental distraction such as semantic auditory distractions impact the usability of mobile applications. In doing so, it attempts to answer the following research questions: 1) Does semantic auditory distractions reduce the effectiveness of a blood glucose tracking mobile application? 2) Does semantic auditory distractions reduce the efficiency of a blood glucose tracking mobile application? 3) Does semantic auditory distractions reduce the user satisfaction of a blood glucose tracking mobile application? To answer the study research questions, a true experimental design was performed involving 30 adults with type 2 diabetes. Participants were paired based on their age and experience with smartphones and randomly assigned to the control (no semantic auditory distractions) or experimental (semantic auditory distractions) group. Research questions were tested using the general linear model. The results of this study confirmed that semantic auditory distractions have a significant effect on efficiency and effectiveness, and hence they need to be taken into account when evaluating mobile usability. This study also showed that semantic auditory distractions have no significant effect on user satisfaction. This dissertation enhances the current knowledge about the impact of semantic auditory distractions on the usability of mobile applications within the diabetic senior population.