Human vital signs are crucial parameters which reflect essential body functions and are often accessed by medical professionals at the first place during clinical diagnostics to provide immediate assistance in health status measurements. However, due to the recent COVID-19 pandemic, measurements made with direct body contact have become increasingly challenging and costly because of the spreading nature of this virus. Therefore, contactless vital sign measurements are highly desirable, and it motivates us to research and develop a new solution which is capable of performing real time heart rate (HR) detection, respiratory (RR) detection, and body temperature (BT) measurement together from a distant human subject under an ambient light environment. The thesis describes a new system framework, which utilizes the power of computer vision to collect remote video image data, processes them using signal processing and machine learning (ML) technologies simultaneously, and produces rapid updates on display. Furthermore, our validation analysis on the system has showed varied results based on different methodologies used, which enables us to apply the most suitable approach on each component for an optimized final integration. At the time of completing this thesis, we have achieved a complete system integrated with remote HR, RR estimations and BT detection, which are all fully functional in both real-time and offline. To further refine the performance on HR estimation, we selected the extreme gradient boost model through a number of ML models we tested, as it not only gives the lowest root mean square error of 8.2 but also produces stable and robust output.

The language-based analogical reasoning abilities of Deaf children are a controversial topic. Researchers lack agreement about whether Deaf children possess the ability to reason using language-based analogies, or whether this ability is limited by a lack of access to vocabulary, both written and signed. This dissertation examines factors that scaffold the development of language-based analogical reasoning through signed language. First it examines how background factors, such as age, race/ethnicity, or additional disabilities can affect the development of language-based analogical reasoning. Second, it looks at how different kinds of American Sign Language (ASL) vocabulary support the development of language-based analogical reasoning. Five-hundred and fifty-six Deaf children were given five tasks from the ASL Assessment Instrument; one analogies task and four vocabulary tasks: an antonyms task, a synonyms task, a definitions task, and a contextual-based vocabulary task. The data showed that background traits can and do affect how well Deaf children reason using language-based analogies. The most important predictor of performance on the analogies task was ASL vocabulary knowledge, although other factors such as age, race/ethnicity, and additional disabilities can impact task performance. The data also showed that ASL vocabulary knowledge that promotes metalinguistic thinking is the best predictor of language-based analogical reasoning abilities. Potential applications to the classroom and to teacher training are also discussed.

Deaf students have unique linguistic and cultural needs that are cultivated in social settings; however, these needs have received minimal consideration from school administrators and policy makers when designing and implementing educational programs. Inquiry regarding how Deaf people learn in social situations and whether these processes are present in formal educational settings is necessary to understand how to better serve this population in school. Observations were used to provide insight on how deaf people teach and learn from one another in social/informal settings. Individual interviews with 11 Deaf people ages 18 to 40 provided insight regarding personal experiences in formal and informal educational settings. Constructivism, sociocultural theory, and multiple intelligences theory were the conceptual frameworks for this study. Trustworthiness was established using member checking and detailed accounts of participants' experiences in their educational placements. The findings revealed that deaf people value facets of Deaf culture in all aspects of their lives, including education. Participants expressed the need for school staff and administrators to understand cultural nuances that are important for deaf students, the need for barrier-free communication, the importance of self-identity, and the need for Deaf mentors and or role models in school. In social settings, deaf people use visual communication and require clear sightlines for communication, use expansion techniques unique to ASL, use scaffolding to support and mentor one another, and use repetition for clarity, understanding, and emphasis. The knowledge gained from this study can help actualize educational curricula that improve literacy and increase job and educational opportunities for deaf people.

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Trust negotiation, a new authentication paradigm, enables strangers on the Internet to establish trust through the gradual disclosure of digital credentials and access control policies. Previous research in trust negotiation does not address issues in preserving trust across multiple sessions. This thesis discusses issues in preserving trust between parties who were previously considered strangers. It also describes the design and implementation of trust preservation in TrustBuilder, a prototype trust negotiation system. Preserving trust information can reduce the frequency and cost of renegotiation. A scenario is presented that demonstrates that a server supporting trust preservation can recoup the cost of the trust preservation facility when approximately 25% of its requests are from repeat customers. The throughput and response time improve up to approximately 33% as the percentage of repeat customers grows to 100%.

A graph in which every edge is labeled positive or negative is called a signed graph. We determine the number of ways to sign the edges of the McGee graph with exactly two negative edges up to switching isomorphism. We characterize signed graphs that are both sign-symmetric and have a frustration index of 1. We prove some results about which signed graphs on complete multipartite graphs have frustration indices 2 and 3. In the final part, we derive the relationship between the frustration index and the number of parts in a sign-symmetric signed graph on complete multipartite graphs.

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