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ContributorsShi, Ge (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-25
ContributorsChang, Ruihong (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-29
ContributorsMatthews, Eyona (Performer) / Yoo, Katie Jihye (Performer) / Roubison, Ryan (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-25
ContributorsGambhir, Ruchy (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-29
ContributorsMann, Parker (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-27
ContributorsShatuho, Kristina (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-27
ContributorsHoeckley, Stephanie (Performer) / Lee, Juhyun (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-24
ContributorsGambhir, Rittika (Performer) / Olarte, Aida (Performer) / Gambhir, Ruchika (Performer) / Chen, Neilson (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-24
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Description
Analysis of social networks has the potential to provide insights into wide range of applications. As datasets continue to grow, a key challenge is the lack of a widely applicable algorithmic framework for detection of statistically anomalous networks and network properties. Unlike traditional signal processing, where models of truth or

Analysis of social networks has the potential to provide insights into wide range of applications. As datasets continue to grow, a key challenge is the lack of a widely applicable algorithmic framework for detection of statistically anomalous networks and network properties. Unlike traditional signal processing, where models of truth or empirical verification and background data exist and are often well defined, these features are commonly lacking in social and other networks. Here, a novel algorithmic framework for statistical signal processing for graphs is presented. The framework is based on the analysis of spectral properties of the residuals matrix. The framework is applied to the detection of innovation patterns in publication networks, leveraging well-studied empirical knowledge from the history of science. Both the framework itself and the application constitute novel contributions, while advancing algorithmic and mathematical techniques for graph-based data and understanding of the patterns of emergence of novel scientific research. Results indicate the efficacy of the approach and highlight a number of fruitful future directions.
ContributorsBliss, Nadya Travinin (Author) / Laubichler, Manfred (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Leo Kanner first described autism in his 1943 article in Nervous Child titled "Autistic Disturbances of Affective Contact". Throughout, he describes the eleven children with autism in exacting detail. In the closing paragraphs, the parents of autistic children are described as emotionally cold. Yet, he concludes that the condition as

Leo Kanner first described autism in his 1943 article in Nervous Child titled "Autistic Disturbances of Affective Contact". Throughout, he describes the eleven children with autism in exacting detail. In the closing paragraphs, the parents of autistic children are described as emotionally cold. Yet, he concludes that the condition as he described it was innate. Since its publication, his observations about parents have been a source of controversy surrounding the original definition of autism.

Thus far, histories about autism have pointed to descriptions of parents of autistic children with the claim that Kanner abstained from assigning them causal significance. Understanding the theoretical context in which Kanner's practice was embedded is essential to sorting out how he could have held such seemingly contrary views simultaneously.

This thesis illustrates that Kanner held an explicitly descriptive frame of reference toward his eleven child patients, their parents, and autism. Adolf Meyer, his mentor at Johns Hopkins, trained him to make detailed life-charts under a clinical framework called psychobiology. By understanding that Kanner was a psychobiologist by training, I revisit the original definition of autism as a category of mental disorder and restate its terms. This history illuminates the theoretical context of autism's discovery and has important implications for the first definition of autism amidst shifting theories of childhood mental disorders and the place of the natural sciences in defining them.
ContributorsCohmer, Sean (Author) / Hurlbut, James B (Thesis advisor) / Maienschein, Jane (Committee member) / Laubichler, Manfred (Committee member) / Arizona State University (Publisher)
Created2014