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Kankakee County in Deindustrialization: An Oral History Approach
Get PDFThe City of Kankakee was an industrialized city which prospered economically for decades. Throughout the late 1970s and 1980s, economic trends shifted for Kankakee and the surrounding communities. The major factories, such as Roper Corporation and A.O. Smith, migrated their source of production from Kankakee to other regions of the United States and abroad. As a result, the declining industrial economic activity led to changing community perceptions. Kankakee is an example of the “Rust Belt” region, a region in the Midwestern and Northeastern States of the United States where declining industrial activity occurred throughout the 1970s and 1980s. The paper uses an Oral History Approach to investigate the changing economic landscape and community and individual perceptions of Kankakee during the Deindustrialization period
Impact of Mindfulness on Test Anxiety in College Students
Get PDFBackground
Mindfulness is defined as the state of giving full attention to a stimulus, internal or external, without inducing judgment or becoming reactional about the feelings experienced, positive or negative (Davis & Hayes, 2012). Previous studies have investigated the relationship between mindfulness techniques and the reduction of anxiety (Chambers et al., 2008; Macdonald & Olsen, 2020); a smaller number of studies have considered test anxiety (Cho et al., 2016; Sparks, 2017). Prior research has used multiple mindfulness techniques to measure the impact on test anxiety, but few have isolated mindfulness trainings to compare the relative impact of each type on test anxiety. The present study utilized two different types of mindfulness trainings to analyze their impact on test anxiety in comparison with each other and a control group; it was hypothesized that mindfulness would increase, and test anxiety would decrease for students in the experimental conditions. The Fog Rolling In training group was hypothesized to experience greater decreases in test anxiety compared to the Counting Breaths and control group.
Methods
Forty-two individuals from three sections of a gen-ed class participated. Students were asked to participate in the study through the completion of the Mindful Attention Awareness Scale (MAAS) and a shortened form of the Test Anxiety Inventory (TAI—5). Both forms were given to each class before trainings began and again at the end of data collection. In the weeks between measures, a class-specific mindfulness training was presented three times.
Results
Data were analyzed using 2x3 mixed factorial ANOVA. There was a nonsignificant interaction (p = .466), non-significant main effects for mindfulness (p = .501) and test anxiety (p = .611), and non-significant main effect for time (p = .484). Mindfulness and test anxiety variables also failed to reach significance when using a paired-samples ttest to exclude the control group (p = .064; p = .960).
Conclusions
Neither mindfulness nor test anxiety changed after participants were exposed to a mindfulness training. In addition, no significant differences were found between two different forms of mindfulness training and a control group on mindfulness and test anxiety
In-Line Profile/Easy Open Inspection
Get PDFDesign, build, and test a device that has the capability of visually inspecting our zipper profiles on our production lines for start-ups or a device that can detect easy-open/weak zippers during regular production
Preprocessing of Astronomical Images From the NEOWISE Survey for Near-Earth Asteroid Detection
Get PDFAsteroid detection is a common field in astronomy for planetary defense which requires observations from survey telescopes to detect and classify different objects. The amount of data collected each night is increasing as better designed telescopes are created each year. This amount is quickly becoming unmanageable and many researchers are looking for ways to better process this data. The dominant solution is to implement computer algorithms to automatically detect these sources and to use Machine Learning in order to create a more efficient and accurate classifier. In the past there has been a focus on larger asteroids that create streaks in the telescope images, but this leads to less accuracy on classifying smaller and slower moving asteroids, which do not appear as often as streaks. We use image and source data from the NEOWISE survey telescope to create a preprocessing pipeline that allows for better training and testing data for a classifying Machine Learning algorithm. We were able to create a pipeline that finds sources on an image within .02 degrees as well as a collection of data on the known sources that can be used to set better parameters for finding specific sources in new images. These steps should aid in creating an algorithm focused on detecting smaller and slower moving asteroids, but our research also indicates that these may be more often mistaken for comets
