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Plants are essential to human life. They release oxygen into the atmosphere for us to breathe. They also provide shelter, medicine, clothing, tools, and food. For many people, the food that is on their tables and in their supermarkets isn't given much thought. Where did it come from? What part

Plants are essential to human life. They release oxygen into the atmosphere for us to breathe. They also provide shelter, medicine, clothing, tools, and food. For many people, the food that is on their tables and in their supermarkets isn't given much thought. Where did it come from? What part of the plant is it? How does it relate to others in the plant kingdom? How do other cultures use this plant? The most many of us know about them is that they are at the supermarket when we need them for dinner (Nabhan, 2009) (Vileisis, 2008).
ContributorsBarron, Kara (Author) / Landrum, Leslie (Thesis director) / Swanson, Tod (Committee member) / Pigg, Kathleen (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor)
Created2012-12
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Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develo

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Contributorsde Guzman, Lorenzo (Co-author) / Chmelnik, Nathan (Co-author) / Martz, Emma (Co-author) / Johnson, Katelyn (Co-author) / Ju, Feng (Thesis director) / Courter, Brandon (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / School of Politics and Global Studies (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develo

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

ContributorsJohnson, Katelyn Rose (Co-author) / Martz, Emma (Co-author) / Chmelnik, Nathan (Co-author) / de Guzman, Lorenzo (Co-author) / Ju, Feng (Thesis director) / Courter, Brandon (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develo

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

ContributorsChmelnik, Nathan (Co-author) / de Guzman, Lorenzo (Co-author) / Johnson, Katelyn (Co-author) / Martz, Emma (Co-author) / Ju, Feng (Thesis director) / Courter, Brandon (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

RESEARCH QUESTION: Does Online "Working Out Work" as a Treatment and Prevention for Depression in Older Adults? An Analysis of a Prescribed and Monitored Exercise Program Administered via the Internet for Senior Adults with Depression.
OBJECTIVE: The purpose of this study is to investigate and access the effectiveness of an online

RESEARCH QUESTION: Does Online "Working Out Work" as a Treatment and Prevention for Depression in Older Adults? An Analysis of a Prescribed and Monitored Exercise Program Administered via the Internet for Senior Adults with Depression.
OBJECTIVE: The purpose of this study is to investigate and access the effectiveness of an online prescribed and monitored exercise program for the treatment of depression in Older Adults. The Dependent Variable for the study is Depression. The Independent Variable for the study is the Effects of Exercise administered via the Internet and the population is geriatric adults defined as senior adults aged 50 and older. Depression is defined by Princeton University Scholars (Wordnet, 2006) as a mental state characterized by a pessimistic sense of inadequacy and a despondent lack of activity.
METHODS: The presence and severity of depression will be assessed by using The Merck Manual of Geriatrics (GDS-15) Geriatric Depression Scale. Assessments will be performed at baseline, before and after the treatment is concluded. The subjects will complete the Physical Activity Readiness Questionnaire (PAR-Q) prior to participating in an exercise program three times per week.
LIMITATIONS OF RESEARCH: The limitations of this study are: 1) There is a small sample size limited to Senior Adults aged 50 - 80, and 2) there is no control group with structured activity or placebo, therefore researcher is unable to evaluate if the marked improvement was due to a non-specific therapeutic effect associated with taking part in a social activity (group online exercise program). Further research could compare and analyze the positive effects of a muscular strength training exercise program verses a cardiovascular training exercise program.

ContributorsCaballero-Garcia, Robelyn (Author) / Waldron, Kathleen (Thesis advisor) / College of Liberal Arts and Sciences (Contributor)
Created2011-05-02