Matching Items (72)
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- All Subjects: conservation
- All Subjects: Machine Learning
- Creators: School of Life Sciences
- Creators: School of Mathematical and Statistical Sciences
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Description
Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.
ContributorsFisher, Rachel (Author) / Blain Christen, Jennifer (Thesis director) / Anderson, Karen (Committee member) / School of Life Sciences (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Zoos are doing amazing projects to help wildlife globally and locally. A lot of people aren't aware of what goes on with these conservation projects because much of it happens behind the scenes. So I decided to make a film to explain how zoos facilitate our world's wildlife. My film can be viewed at this link: https://www.youtube.com/watch?v=_JmLGf138zY
ContributorsRossman, Chloe June (Author) / Sandler, Kevin (Thesis director) / Wells, Stuart (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Film, Dance and Theatre (Contributor)
Created2014-05
Description
The OMFIT (One Modeling Framework for Integrated Tasks) modeling environment and the BRAINFUSE module have been deployed on the PPPL (Princeton Plasma Physics Laboratory) computing cluster with modifications that have rendered the application of artificial neural networks (NNs) to the TRANSP databases for the JET (Joint European Torus), TFTR (Tokamak Fusion Test Reactor), and NSTX (National Spherical Torus Experiment) devices possible through their use. This development has facilitated the investigation of NNs for predicting heat transport profiles in JET, TFTR, and NSTX, and has promoted additional investigations to discover how else NNs may be of use to scientists at PPPL. In applying NNs to the aforementioned devices for predicting heat transport, the primary goal of this endeavor is to reproduce the success shown in Meneghini et al. in using NNs for heat transport prediction in DIII-D. Being able to reproduce the results from is important because this in turn would provide scientists at PPPL with a quick and efficient toolset for reliably predicting heat transport profiles much faster than any existing computational methods allow; the progress towards this goal is outlined in this report, and potential additional applications of the NN framework are presented.
ContributorsLuna, Christopher Joseph (Author) / Tang, Wenbo (Thesis director) / Treacy, Michael (Committee member) / Orso, Meneghini (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Physics (Contributor)
Created2015-05
Description
Twitter, the microblogging platform, has grown in prominence to the point that the topics that trend on the network are often the subject of the news and other traditional media. By predicting trends on Twitter, it could be possible to predict the next major topic of interest to the public. With this motivation, this paper develops a model for trends leveraging previous work with k-nearest-neighbors and dynamic time warping. The development of this model provides insight into the length and features of trends, and successfully generalizes to identify 74.3% of trends in the time period of interest. The model developed in this work provides understanding into why par- ticular words trend on Twitter.
ContributorsMarshall, Grant A (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
A literature review summarizing the current status of conservation efforts of the Mojave Desert tortoise (Gopherus agassizii) including a brief overview of the Endangered Species Act (ESA) and its applicability to this species' conservation. A genetic and physiological comparison of the morphologically similar Mojave species with the Sonoran (Gopherus morafkai) species proceeded by an analysis of if and how the ESA should apply to the Sonoran population. Analysis of current plans and interagency cooperations followed by a multi-step proposal on how best to conserve the Sonoran population of Desert tortoise.
ContributorsKulik, Elise Chikako (Author) / Kusumi, Kenro (Thesis director) / Tollis, Marc (Committee member) / Wilson Sayres, Melissa (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Bots tamper with social media networks by artificially inflating the popularity of certain topics. In this paper, we define what a bot is, we detail different motivations for bots, we describe previous work in bot detection and observation, and then we perform bot detection of our own. For our bot detection, we are interested in bots on Twitter that tweet Arabic extremist-like phrases. A testing dataset is collected using the honeypot method, and five different heuristics are measured for their effectiveness in detecting bots. The model underperformed, but we have laid the ground-work for a vastly untapped focus on bot detection: extremist ideal diffusion through bots.
ContributorsKarlsrud, Mark C. (Author) / Liu, Huan (Thesis director) / Morstatter, Fred (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Globally, many species of shark are facing rapid population decline. This is due to increasing fishing pressures, primarily from the booming demand in China for shark fins for soup. In recent years there has also been an increase in international shark conservation efforts, but there is still a long way to go in gathering support for those efforts. Public perception of sharks in America has been greatly influenced by negative media representations of them, Jaws being one of the most influential. Many of these representations are based on inaccurate information that has been disproven by science, but still lingers in popular culture. Symbolic Interactionism Theory proved to be a useful framework for unpacking the connections between public perception, mainstream culture and media, and conservation regarding sharks. A social psychological theory, Symbolic Interactionism describes the ways that people construct meaning about a topic through direct and indirect interactions, and how this meaning can change on individual, social, and cultural levels. By changing the way sharks are perceived and represented to the public, these important and incredible animals may gather the support they need to continue living in the world's oceans.
ContributorsCressler, Christina Nancy (Author) / Minteer, Ben (Thesis director) / Gerber, Leah (Committee member) / Ellison, Karin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
The purpose of my thesis is to illustrate the story of the black-footed ferret's conservation, and to provide my own suggestions for how to eventually get the species removed from the Endangered Species List, marking a successful rebound in population numbers. I highlight my personal experience working at the Phoenix Zoo's black-footed ferret breeding center. In the first chapter, I present the species by describing its morphology, diet, reproduction, behaviors, range, and habitat. In the second chapter, I recount the chronological history of the conservation of the species, starting with its rediscovery following its putative "extinction", and ending with its present status. In the third chapter, I discuss the threats that have led to the species' overall decline and continue to affect its persistence today. In the fourth and final chapter, I conclude by making recommendations regarding what needs to occur in order to eventually get the species delisted.
ContributorsGeer, Emily Maren (Author) / Smith, Andrew T. (Thesis director) / Minteer, Ben (Committee member) / Wells, Stuart (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
Consumption of seafood poses a substantial threat to global biodiversity. Chemical contamination found in both wild-caught and farmed seafood also presents significant health risks to consumers. Flame retardants, used in upholstery, plastics, clothing, and other products to reduce fire danger, are of particular concern as they are commonly found in the marine environment and permeate the tissues of fish that are sold for consumption via multiple pathways. By summarizing various metrics of sustainability and the mercury content in consumed species of fish and shellfish, researchers have found that high levels of chemical contamination was linked with lesser fishery sustainability. I conducted a literature review of flame retardant content in seafood to further compare contamination and sustainability in addition to the initial analysis with mercury. My review suggests that the widespread issue of fishery collapse could be alleviated by demonstrating to stakeholders that many unsustainable fish stocks are mutually disadvantageous for both human consumers and the environment. Future research should address the need for the collection of data that better represent actual global contaminant concentrations in seafood.
ContributorsNoziglia, Andrea Joyce (Author) / Gerber, Leah (Thesis director) / Smith, Andrew (Committee member) / Pratt, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
Conservation is a complicated entity consisting of a multitude of professional fields including social issues, cultural issues, and physical science. This thesis evaluates the positive and negative aspects of two broad types of conservation: top down fortress conservation and bottom up community-based conservation. Fortress conservation has many negative aspects, such as displacing human communities and preventing utilization of resources. However, it also has positive aspects, such as preventing the destruction of delicate ecosystems and slowing down extinctions. Community-based conservation is more inclusive and focuses on including the indigenous populations located within the proposed conservation site in the decision-making process. Its negatives include having an anthropocentric goal instead of valuing nature's intrinsic values. Understanding the differences inherent in these two methods is necessary in order to implement a conservation network with the highest chance for success.
ContributorsFink, Laurel Berylline (Author) / Smith, Andrew (Thesis director) / Collins, James (Committee member) / Minteer, Ben (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05