Surviving Monolingualism: Embracing Translingual Perspectives and Trans-semiotizing

This thesis is an attempt to contribute to the deconstruction of the monolingual myth that has dominated language attitudes and the language classroom in the U.S. for centuries. Its main proposition is that by promoting and advocating for translanguaging and trans-semiotizing in the classroom and in daily life, we can affirm the linguistic and cultural identities of students, individuals, and groups that are marginalized or oppressed by hegemonic monolingual ideologies and improve our language teaching practices. Through literature review and personal narrative, the author has endeavored to demonstrate how translanguaging offers potential solutions to some current linguistic conflicts and how monolingualism undervalues all language users, no matter the number of languages spoken. The author contends that all speakers practice translanguaging and trans-semiotizing when making meaning dialogically. Suggestions are then offered for what educators and individuals can do in the classroom and in their personal lives to incorporate and more fully embrace translingual practices and thus begin to change the linguistic narrative

Determining the efficacy of additive manufacturing for the aerospace spare parts supply chain

This thesis investigates how additive manufacturing (AM) based on-demand part production can supplement or replace the traditional production and inventory in typical aerospace’s spare parts supply chain systems. This study focuses on the operational characteristics of AM and its impacts on the overall logistics of plant-level operations. To capture the microscopic operational aspects of the AM production, a discrete-event simulation based approach was adopted, with key AM operation resources (e.g. AM system, operator) and attributes (e.g. AM manufacturing speed, individual part characteristics and demands) accounted for in the modeling process. In addition, a benchmark warehouse inventory model was also established separately based on classic theories, which was subsequently utilized to create a cost/benefit analysis for the AM based part supply strategies versus the traditional strategies. The results from virtual experiments with these models were analyzed in order to gain an understanding of the operational characteristics (e.g., production cost, system utilization, lead time) as a function of various production policies such as machine/operator configurations and part prioritization. Data analysis shows cost savings for AM as an alternative to warehousing under high penalty scenarios. Results also indicate higher cost savings with the addition of extra machines over extra operators to meet capacity. Finally, analysis shows that reprioritizing orders waiting in a queue has higher savings when assessing due date and penalty outcomes

Collective Classification for Social Media Credibility Estimation

We introduce a novel extension of the iterative classification algorithm to heterogeneous graphs and apply it to estimate credibility in social media. Given a heterogeneous graph of events, users, and websites derived from social media posts, and given prior knowledge of the credibility of a subset of graph nodes, the approach iteratively converges to a set of classifiers that estimate credibility of the remaining nodes. To measure the performance of this approach, we train on a set of manually labeled events extracted from a corpus of Twitter data and calculate the resulting receiver operating characteristic (ROC) curves. We show that collective classification outperforms independent classification approaches, implying that graph dependencies are crucial to estimating credibility in social media

Wave Energy in Clatsop County, OR: An Economic Impact Analysis

This study analyzes the economic impacts of building a wave energy commercial generation project in Clatsop County, Oregon. The modeled project is relatively small, and was produced by reviewing relevant wave energy literature and working with two local wave energy developers to estimate the expenditures and related costs of the project. We find that the construction and ongoing operation of a commercial wave energy project would create gains in employment, income, and output in the area as well as preparing Astoria for further wave energy development

XLab: Early Indications & Warnings from Open Source Data with Application to Biological Threat

XLab is an early warning system that addresses a broad range of national security threats using a flexible, rapidly reconfigurable architecture. XLab enables intelligence analysts to visualize, explore, and query a knowledge base constructed from multiple data sources, guided by subject matter expertise codified in threat model graphs. This paper describes a novel system prototype that addresses threats arising from biological weapons of mass destruction. The prototype applies knowledge extraction analytics-”including link estimation, entity disambiguation, and event detection-”to build a knowledge base of 40 million entities and 140 million relationships from open sources. Exact and inexact subgraph matching analytics enable analysts to search the knowledge base for instances of modeled threats. The paper introduces new methods for inexact matching that accommodate threat models with temporal and geospatial patterns. System performance is demonstrated using several simplified threat models and an embedded scenario

Nexus of Despair: A Network Analysis of Suicidal Ideation among Veterans

The objective of this study was to estimate a network model of risk and resilience factors of suicidal ideation among veterans. Two network models of suicidal ideation among Operation Iraqi Freedom/ Operation Enduring Freedom/Operation New Dawn veterans (N = 276) incorporated key disorders, traumatic stress, and resilience constructs to contextualize suicidal ideation. Childhood trauma was positively connected with suicidal ideation and harassment and inversely connected with social support and distress tolerance. This exemplifies long-lasting associations between childhood trauma and revictimization, emotion regulation, and ability to form supportive social relationships. A subsequent model including lower-order facets indicated that combat trauma was predominantly associated with posttraumatic stress disorder–intrusion symptoms. This study highlights the importance of addressing both risk and resilience to reduce suicide risk among veterans and increases understanding of factors that contribute to suicidal ideation