In this thesis, an activity classification algorithm is developed to support a human ambulatory monitoring system. This algorithm, to be deployed on an e-textile garment, represents the enabling step in creating a wide range of garments that can use the same classifier without having to re-train for different sensor types. This flexible operation is made possible by basing the classifier on an abstract model of the human body that is the same across all sensor types and subject bodies. In order to support low power devices inherent for wearable systems, the algorithm utilizes regular expressions along with a tree search during classification. To validate the approach, a user study was conducted using video motion capture to record subjects performing a variety of activities. The subjects were randomly placed into two groups, one used to generate the activities known by the classifier and another to be used as observation to the classifier. These two sets were used to gain insight on the performance of the algorithm. The results of the study demonstrate that the algorithm can successfully classify observations, so as long as precautions are taken to prevent the activities known by the classifier to become too large. It is also shown that the tree search performed by the classification can be utilized to partially classify observations that would otherwise be rejected by the classifier. The user study additionally included subjects that performed activities purely used for observations to the classifier. With this set of recordings, it was demonstrated that the classifier does not over-fit and is capable of halting the classification of an observation. / Master of Science

The global COVID-19 pandemic dramatically altered learning experiences for children, parents, and teachers worldwide. For very young children, the scrambled introduction of complex virtual tools as a proxy for the classroom experience has been particularly challenging. I conducted interviews with kindergarten teachers and parents with young children to better understand their experiences navigating virtual learning during a stressful time. Insights from those discussions informed the iterative design process I used to generate alternative interactive interfaces for online kindergarten instruction. In this thesis, I present findings from the interviews, the multi-stage interface design process, participant responses to the interface design, and promising directions for future work. / Master of Science / The global COVID-19 pandemic dramatically altered learning experiences for children, parents, and teachers worldwide. For very young children, the scrambled introduction of complex virtual tools as a proxy for the classroom experience has been particularly challenging. I conducted interviews with kindergarten teachers and parents with young children to better understand their experiences navigating virtual learning during a stressful time. Insights from those discussions informed the iterative design process I used to generate alternative interactive interfaces for online kindergarten instruction. In this thesis, I present findings from the interviews, the multi-stage interface design process, participant responses to the interface design, and promising directions for future work.

The goal for this thesis is to create a second screen application that will enhance the experience while watching a first screen. In order to create that type of application research within the subject and reviews of existing application is conducted. The reviews resulted in functionality and content that a second screen application should have. One of the big challenges for working with a second screen balance the focus between the screens and to make sure that the application creates value, rather than taking time and being frustrating. A concept of an application based on findings and iterations that will en- hance the experience were created. The concept were realised in wireframes and design mockups. The main functionality for the application is implemented with the native language objective-c as a working prototype on iPad. The biggest finding during this thesis is to remember to focus on solving one specific problem for the user.

No / This research seeks to measure citizen satisfaction with the electronic Prescription Prepayment Certificate (PPC) offered by National Health Service (NHS) in the United Kingdom (UK). The paper reports on the findings of a survey of over 500 users of the NHS PPC service. Satisfaction is measured using the four dimensions from the COBRA framework (Osman et al. (2011) [1]) which comprise the cost, opportunity, benefits and risk assessment constructs. This is the first study to measure citizen satisfaction with the electronic PPC in the UK across these constructs. The results show that most citizens using the PPC electronic service are satisfied with this service and that the service meets their essential needs. The paper also presents the results of qualitative feedback obtained from the participants that can be used to determine the areas that need further improvement in the current electronic PPC service and potential influence on user satisfaction.

Yes / This paper introduces the concept of user validity and provides a new perspective on the validity of interpretations from tests. Test interpretation is based on outputs such as test scores, profiles, reports, spread-sheets of multiple candidates’ scores, etc. The user validity perspective focuses on the interpretations a test user makes given the purpose of the test and the information provided in the test output. This innovative perspective focuses on how user validity can be extended to content, criterion and to some extent construct-related validity. It provides a basis for researching the validity of interpretations and an improved understanding of the appropriateness of different approaches to score interpretation, as well as how to design test outputs and assessments which are pragmatic and optimal.

There are very few software packages for model-building and visualization in electromagnetic geophysics, particularly when compared to other geophysical disciplines, such as seismology. The purpose of this thesis is to design, develop, and test a geophysical model-building interface that allows users to parameterize the 2D magnetotellurics problem. Through the evaluation of this interface, feedback was collected from a usability specialist and a group of geophysics graduate students to study the steps users take to work through the 2D forward-modeling problem, and to analyze usability errors encountered while working with the interface to gain a better understanding of how to build a more effective interface. Similar work has been conducted on interface design in other fields, such as medicine and consumer websites. Usability Engineering is the application of a systematic set of methods to the design and development of software with the goal of making the software more learnable, easy to use, and accessible. Two different Usability Engineering techniques — Heuristic Evaluation and Thinking Aloud Protocol — were involved in the evaluation of the interface designed in this study (FEM2DGUI). Heuristic Evaluation is a usability inspection method that employs a usability specialist to detect errors based on a known set of guidelines and personal experience. Thinking Aloud Protocol is a usability evaluation method where potential end-users are observed as they verbalize their every step as they work through specific scenarios with an interface. These Usability Engineering methods were combined in a effort to understand how the first prototype of FEM2DGUI could be refined to make it more usable and to understand how end-users work through the forward-modeling problem. The Usability Engineering methods employed in this project uncovered multiple usability errors that were corrected through a refinement of the interface. Discovery of these errors helped with refining the system to become more robust and usable, which is believed to aid users in more efficient model-building. Because geophysical model-building is inherently a difficult task, it is possible that other model-building graphical user interfaces could benefit from the application of Usability Engineering methods, such as those presented in this research.â / Master of Science

Thematic tourist maps provide users with a tangible geographic route to their travel destinations and also may contain a wide variety of additional information to enhance traveler experiences. Unlike other types of maps that focus on accurate topographic representation of an area or on depiction of spatial data, tourist maps should be specifically constructed to appeal directly to the end-user. Toward that end, this research developed and implemented a model to incorporate user opinion on content, levels of detail, and labeling conventions during the process of designing and creating a wine tourism map for southwest Virginia. Over 700 (total) wine tourists completed brief questionnaires during five distinct phases of data collection and map modeling. At each point, we incorporated user input into map design for the preceding phase, and a final assessment surveyed tourist attitude of the finished product. Interestingly, surveys indicated a propensity for users to highly rank the idea of more and more detailed content data, as well as high levels of spatial detail, but when presented with the corresponding maps, they tended to favor a cleaner more simplified display. This finding underscores our conclusion that while user input is critical for developing successful tourist maps, cartographic training and skill is still required to achieve a quality product. Overall, the final map incorporating user input received overwhelmingly positive user reviews when compared to existing regional maps indicating that our iterative method of seeking user input at various stages of map development was successful, and facilitated creation of an improved product. / Master of Science

The unprecedented rise of IoT has revolutionized every business vertical enthralling people to embrace IoT applications in their day-to-day lives to accrue multifaceted benefits. It is absolutely fair to say that a day without connected IoT systems, such as smart devices, smart enterprises, smart homes or offices, etc., would hamper our conveniences, drastically. Many IoT applications for these connected systems are safety-critical, and any unauthorized access could have severe consequences to their consumers and society. In the overall IoT security spectrum, human-to-machine authentication for IoT applications is a critical and foremost challenge owing to highly prescriptive characteristics of conventional user authentication schemes, i.e., knowledge-based or token-based authentication schemes, currently used in them. Furthermore, studies have reported numerous users’ concerns, from both the security and usability perspectives, that users are facing in using available authentication schemes for IoT applications. Therefore, an impetus is required to upgrade user authentication schemes for new IoT age applications to address any unforeseen incidents or unintended consequences. This dissertation aims at designing next-generation user authentication schemes for IoT applications to secure connected systems, namely, smart devices, smart enterprises, smart homes, or offices. To accomplish my research objectives, I perform a thorough study of ways and types of user authentication mechanisms emphasizing their security and usability ramifications. Subsequently, based on the substantive findings of my studies, I design, prototype, and validate our proposed user authentication schemes. I exploit both physiological and behavioral biometrics to design novel schemes that provide implicit (frictionless), continuous (active) or risk-based (non-static) authentication for multi-user scenarios. Afterward, I present a comparative analysis of the proposed schemes in terms of accuracy against the available state-of-the-art user authentication solutions. Also, I conduct SUS surveys to evaluate the usability of user authentication schemes.

Yes / Background: Head and Neck Cancer (HNC) is the eighth most prevalent global cancer. Timely recognition of symptoms is crucial for reducing mortality rates. The EVolution of a patiEnt-REported symptom-based risk stratification sySTem to redesign the suspected Head and Neck cancer referral pathway (EVEREST-HN) study aims to develop and evaluate a risk stratification tool using patient reported symptoms, which will be populated remotely in the community before the patient is seen by the clinician to hasten HNC diagnosis. EVEREST-HN will design a patient SYmptom iNput Clinical (SYNC) system to gather patient symptom data and calculate a risk score to aid clinicians in identifying high-risk cases. This identification potentially allows for high-risk patients to be seen sooner, thereby improving patient outcomes. Methods: Three workshop sessions were conducted involving a total of 17 unique participants, with several contributing to multiple sessions: nine in the co-design session, six in the validation session, and nine in the evaluation session. The co-design session employed online collaboration with patients’ representatives. Thematic analysis was used to identify requirements and concerns informing the development of a low-fidelity prototype. The validation session assessed whether the prototype aligned with patient expectations. In the evaluation session, participants interacted with an online prototype and provided further feedback. Results: During the co-design workshop, participants emphasized the need for a concise and clear SYNC system questionnaire for reporting suspected HNC symptoms. Concerns were raised about questionnaire length, language clarity, and the inclusion of probing questions. Participants suggested concise questions using lay language, incorporating visual aids for topics like alcohol and tobacco use, and making the sexual activity question optional. Recommendations included diverse language options, hard copies for non-English speakers, and phone call options for those uncomfortable with screen-based technology. The validation workshop confirmed that the prototype reflected participants’ ideas. Feedback highlighted the need for call-back features to help those not confident with technology and the need to present symptom questions first before social background questions. Feedback from the evaluation demonstrated a commitment to efficiency, and continuous improvement. Conclusion: This study aims to develop the SYNC system to enhance efficiency of suspected HNC referrals. The workshops highlighted the importance of end-user inclusiveness in the system development life cycle, with collaboration with stakeholders and repeated feedback, providing crucial insights for ensuring the SYNC system effectively addresses the needs and concerns of patients in the context of HNC diagnosis. / This study is funded by the NIHR Programme Grants for Applied Research (NIHR202862).

Master of Science / Department of Computing and Information Sciences / Alley Stoughton / This thesis covers the process leading up to the release of eXene 2.0, a User Interface Management System (UIMS) toolkit. Since its inception, eXene has provided a unique way to create meaningful graphical user interfaces (GUIs) for Standard ML applications. Additionally, it has gone through several quality revisions which have both enhanced the toolkit and corrected many deficiencies that were present. Even with these improvements, however, the full potential of eXene has become increasingly difficult for developers to utilize. That is, in spite of the natural innovation that eXene brings to GUI construction, its current lack of extensibility, usability, and functionality has caused Standard ML developers to choose simpler, more familiar UIMS toolkits, despite their limitations, for the creation of their applications. In light of this fact, eXene needs an internal and cosmetic overhaul to extend its usage and appeal. First, to improve its extensibility, formerly weakened by organic growth, eXene requires some restructuring of its architecture. Second, to improve its overall usability, previously stifled by sparse documentation, eXene requires the implementation of an interactive electronic document for its API. Finally, to improve its functionality, several new multi-purpose widgets need to be introduced. It is the author's hypothesis that the revised structure, improved documentation, and additional multi-purpose widgets detailed in this thesis sufficiently elevate eXene's extensibility, usability, and functionality such that eXene can be considered a fully featured UIMS toolkit. With these changes and the release of eXene 2.0, eXene is more likely to be adopted as the primary UIMS toolkit for Standard ML developers.