Identifying people in historical photographs is an important task in many fields, including history, journalism, genealogy, and collecting. A wide variety of different methods, such as manual analysis, facial recognition, and crowdsourcing, have been used to identify the unknown photos. However, because of the large numbers of candidates and the poor quality or lack of source evidence, accurate historical person identification still remains challenging. Researchers especially struggle with the ``last mile problem" of historical person identification, where they must make a selection among a small number of highly similar candidates. Collaboration, including both human-AI collaboration and collaboration within human teams, has shown the advantages of improving data accuracy, but there is lack of research about how we can design a collaborative workspace to support the historical person identification. In this work, we present SleuthTalk, a web-based collaboration tool integrated into the public website Civil War Photo Sleuth which addresses the last-mile problem in historical person identification by providing support for shortlisting potential candidates from face recognition results, private collaborative workspaces, and structured feedback interfaces. We evaluated this feature in a mixed-method study involving 6 participants, who spent one week each using SleuthTalk and a comparable social media platform to identify an unknown photo. The results of this study show how our design helps with identifying historical photos in a collaborative way and suggests directions for improvement in future work. / Master of Science / Identifying people in historical photographs is an important task in many fields, including history, journalism, genealogy, and collecting. A wide variety of different methods, such as manual analysis, facial recognition, and crowdsourcing, have been used to identify the unknown photos. However, because of the large numbers of candidates and the poor quality or lack of source evidence, accurate historical person identification still remains challenging. Researchers especially struggle with the ``last mile problem" of historical person identification, where they must make a selection among a small number of highly similar candidates. Collaboration, including both human-AI collaboration and collaboration within human teams, has shown the advantages of improving data accuracy, but there is lack of research about how we can design a collaborative workspace to support the historical person identification. In this work, we present SleuthTalk, a web-based collaboration tool integrated into the public website Civil War Photo Sleuth which addresses the last-mile problem in historical person identification by providing support for shortlisting potential candidates from face recognition results, private collaborative workspaces, and structured feedback interfaces. We evaluated this feature in a mixed-method study involving 6 participants, who spent one week each using SleuthTalk and a comparable social media platform to identify an unknown photo. The results of this study show how our design helps with identifying historical photos in a collaborative way and suggests directions for improvement in future work.

As we begin to analyze and construct extremely complex systems, a theory for understanding and designing the underlying architecture becomes very important. To move in the direction of a precise theory of architecture, this thesis will provide some concrete tools to analyze and design complex systems with a given network structure. The first main result of this thesis analyzes the vulnerability of a system and shows that a system's vulnerability depends on its network structure. We will consider destabilization attacks acting on a single link in a system's logical interconnection structure. The concept of a vulnerable link is characterized and necessary and sufficient conditions for identifying these links are provided. The vulnerability of various system architectures are then characterized by the vulnerability of their weakest link, and it is shown that every transfer function has a completely secure architecture with no vulnerable links. The second part of this thesis focuses on synthesizing controllers with a specified network structure. It presents a new approach to distributed controller design that exploits the dynamical structure function representation of linear time invariant systems to characterize the structure of a system. The design technique sequentially constructs each link in an arbitrary controller signal structure, and the main theorem proves that either the resulting controller is stabilizing or that no controller with the desired structure can stabilize the system.