THE FANNED FLAMES OF DISCONTENT: A SOLIDARITY-INSPIRED HISTORY OF THE IDENTITY/IDEOLOGY, CULTURAL HISTORY, AND RHETORICAL STRATEGIES OF THE WOBBLIES DURING THE 1916 MINNESOTA IRON ORE STRIKE

Rooted in critical scholarship this dissertation is an interdisciplinary study, which contends that having a history is a basic human right. Advocating a newly conceived and termed, Solidarity-inspired History framework/practice perspective, the dissertation argues for and then delivers a restorative voice to working-class historical actors during the 1916 Minnesota Iron Ore Strike. Utilizing an interdisciplinary methodological framework the dissertation combines research methods from the Humanities and the Social Sciences to form a working-class history that is a corrective to standardized studies of labor in the late 19th and early 20th centuries. Oftentimes class interests and power relationships determine the dominant perspectives or voices established in history and disregard people and organizations that run counter to, or in the face of, customary or traditional American themes of patriotism, the Protestant work ethic, adherence to capitalist dogma, or United States exceptionalism. This dissertation counteracts these traditional narratives with a unique, perhaps even revolutionary, examination of the 1916 Minnesota Iron Ore Strike. The intention of this dissertation's critical perspective is to poke, prod, and prompt academics, historians, and the general public to rethink, and then think again, about the place of those who have been dislocated from or altogether forgotten, misplaced, or underrepresented in the historical record. Thus, the purpose of the dissertation is to give voice to historical actors in the dismembered past. Historical actors who have run counter to traditional American narratives often have their body of "evidence" disjointed or completely dislocated from the story of our nation. This type of disremembering creates an artificial recollection of our collective past, which de-articulates past struggles from contemporary groups seeking solidarity and social justice in the present. Class-conscious actors, immigrants, women, the GLBTQ community, and people of color have the right to be remembered on their own terms using primary sources and resources they produced. Therefore, similar to the Wobblies industrial union and its rank-and-file, this dissertation seeks to fan the flames of discontented historical memory by offering a working-class perspective of the 1916 Strike that seeks to interpret the actions, events, people, and places of the strike anew, thus restoring the voices of these marginalized historical actors.

VISUAL-INERTIAL INTEGRATION FOR HUMAN MOTION TRACKING AND NAVIGATION IN FREE-LIVING ENVIRONMENTS

The aging population has become a burning issue for all modern societies around the world recently. There are two important issues existing now to be solved. One is how to continuously monitor the movements of those people having suffered a stroke in natural living environment for providing more valuable feedback to guide clinical interventions. The other one is how to guide those old people effectively when they are at home or inside other buildings and to make their life easier and convenient. Therefore, human motion tracking and navigation have been active research fields with the increasing number of elderly people. However, motion capture has been extremely challenging to go beyond laboratory environments and obtain accurate measurements of human physical activity especially in free-living environments, and navigation in free-living environments also poses some problems such as the denied GPS signal and the moving objects commonly presented in free-living environments. This thesis seeks to develop new technologies to enable accurate motion tracking and positioning in free-living environments. This thesis comprises three specific goals using our developed IMU board and the camera from the imaging source company: (1) to develop a robust and real-time orientation algorithm using only the measurements from IMU; (2) to develop a robust distance estimation in static free-living environments to estimate people’s position and navigate people in static free-living environments and simultaneously the scale ambiguity problem, usually appearing in the monocular camera tracking, is solved by integrating the data from the visual and inertial sensors; (3) in case of moving objects viewed by the camera existing in free-living environments, to firstly design a robust scene segmentation algorithm and then respectively estimate the motion of the vIMU system and moving objects. To achieve real-time orientation tracking, an Adaptive-Gain Orientation Filter (AGOF) is proposed in this thesis based on the basic theory of deterministic approach and frequency-based approach using only measurements from the newly developed MARG (Magnet, Angular Rate, and Gravity) sensors. To further obtain robust positioning, an adaptive frame-rate vision-aided IMU system is proposed to develop and implement fast vIMU ego-motion estimation algorithms, where the orientation is estimated in real time from MARG sensors in the first step and then used to estimate the position based on the data from visual and inertial sensors. In case of the moving objects viewed by the camera existing in free-living environments, a robust scene segmentation algorithm is firstly proposed to obtain position estimation and simultaneously the 3D motion of moving objects. Finally, corresponding simulations and experiments have been carried out.

INNOVATIVE HUMAN-COMPUTER INTERACTIONS TO SUPPORT COGNITIVE COLLABORATIVE GEOSPATIAL ENVIRONMENTS

In the current world geospatial information is being demanded in almost real time, which requires the speed at which this data is processed and made available to the user to be at an all-time high. In order to keep up with this ever increasing speed, analysts must find ways to increase their productivity. At the same time the demand for new analysts is high, and current methods of training are long and can be costly. Through the use of human computer interactions and basic networking systems, this paper explores new ways to increase efficiency in data processing and analyst training.

A NATURALISTIC COMPUTATIONAL MODEL OF HUMAN BEHAVIOR IN NAVIGATION AND SEARCH TASKS

Planning, navigation, and search are fundamental human cognitive abilities central to spatial problem solving in search and rescue, law enforcement, and military operations. Despite a wealth of literature concerning naturalistic spatial problem solving in animals, literature on naturalistic spatial problem solving in humans is comparatively lacking and generally conducted by separate camps among which there is little crosstalk. Addressing this deficiency will allow us to predict spatial decision making in operational environments, and understand the factors leading to those decisions. The present dissertation is comprised of two related efforts, (1) a set of empirical research studies intended to identify characteristics of planning, execution, and memory in naturalistic spatial problem solving tasks, and (2) a computational modeling effort to develop a model of naturalistic spatial problem solving. The results of the behavioral studies indicate that problem space hierarchical representations are linear in shape, and that human solutions are produced according to multiple optimization criteria. The Mixed Criteria Model presented in this dissertation accounts for global and local human performance in a traditional and naturalistic Traveling Salesman Problem. The results of the empirical and modeling efforts hold implications for basic and applied science in domains such as problem solving, operations research, human-computer interaction, and artificial intelligence.