766 research outputs found

    Creating Identity Through Dialect In Fantasy Media: The Absence, Presence And Use Of Stereotypes In Characters

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    As everyone speaks in a dialect, and its meaning is limited to biographical details. However, dialects have stereotypes associated with them that impart information that may or may not be true for a person. This is not true in media. A character\u27s dialect has broader meaning couched in those stereotypes, especially when it is a non-standard dialect. This thesis explores how a dialect and its stereotypes are used in media as a tool for characterization. As a part that is the examination of the convergence and divergence of a dialect\u27s stereotypes and characterization. The media examined is limited to fantasy media produced in the United States. In the thesis, multiple characters from two films, one videogame, and two podcasts are examined

    Extension Programming for Food Entrepreneurs: An Indiana Needs Assessment

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    The objective of the research reported here was to identify the needs of food entrepreneurs in the state of Indiana. To attain this objective, Purdue Extension educators from 86 counties in Indiana were surveyed. Topics of interest from the survey results included marketing, new business start-up, food regulations, and food safety. This assessment tool has directed Purdue Extension in developing a Food Entrepreneur Engagement Program. The survey results were used to develop a statewide workshop for food entrepreneurs. Resources provided by this program ultimately helped several food entrepreneurs create value-added food businesses in Indiana

    A new capacitance medium for presumptive detection of Listeria spp. from cheese samples

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    The paper presents a new medium and a method for the rapid presumptive detection of Listeria spp. in cheese samples by electrical capacitance changes. The Bactometer based capacitance broth (LED medium) required a 30% change in signal within 30 h to identify presumptive positive results. Of 32 cheese samples tested, 10 were found to contain Listeria spp. using a Fraser broth screening method and 12 using the LED medium and method. The LED method also gave 16 fewer (total = 1) false presumptive positive results. Results show the LED method to be superior to Fraser broth in regard to both the number of false presumptive positive and confirmed false negative results detected. The method appears to be suitable as a reliable rapid screen for the presence of Listeria spp. in cheese

    Catalog of Chromium, Cobalt, and Nickel Abundances in Globular Clusters and Dwarf Galaxies

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    We present measurements of the abundances of chromium, cobalt, and nickel in 4113 red giants, including 2277 stars in globular clusters (GCs), 1820 stars in the Milky Way's dwarf satellite galaxies, and 16 field stars. We measured the abundances from mostly archival Keck/DEIMOS medium-resolution spectroscopy with a resolving power of R ~ 6500 and a wavelength range of approximately 6500–9000 Å. The abundances were determined by fitting spectral regions that contain absorption lines of the elements under consideration. We used estimates of temperature, surface gravity, and metallicity that we previously determined from the same spectra. We estimated systematic error by examining the dispersion of abundances within mono-metallic GCs. The median uncertainties for [Cr/Fe], [Co/Fe], and [Ni/Fe] are 0.20, 0.20, and 0.13, respectively. Finally, we validated our estimations of uncertainty through duplicate measurements, and we evaluated the accuracy and precision of our measurements through comparison to high-resolution spectroscopic measurements of the same stars

    Creating an Explainable Intrusion Detection System Using Self Organizing Maps

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    Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex black boxes. This means that a security analyst will have little to no explanation or clarification on why an IDS model made a particular prediction. A potential solution to this problem is to research and develop Explainable Intrusion Detection Systems (X-IDS) based on current capabilities in Explainable Artificial Intelligence (XAI). In this paper, we create a Self Organizing Maps (SOMs) based X-IDS system that is capable of producing explanatory visualizations. We leverage SOM's explainability to create both global and local explanations. An analyst can use global explanations to get a general idea of how a particular IDS model computes predictions. Local explanations are generated for individual datapoints to explain why a certain prediction value was computed. Furthermore, our SOM based X-IDS was evaluated on both explanation generation and traditional accuracy tests using the NSL-KDD and the CIC-IDS-2017 datasets
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