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ABTRACT For decades the United States has tried to increase the number of students pursuing science, technology, engineering, and mathematics (STEM) education and careers. Educators and policy makers continue to seek strategies to increase the number of students in the STEM education pipeline. Public institutions of higher education are involved

ABTRACT For decades the United States has tried to increase the number of students pursuing science, technology, engineering, and mathematics (STEM) education and careers. Educators and policy makers continue to seek strategies to increase the number of students in the STEM education pipeline. Public institutions of higher education are involved in this effort through education and public outreach (EPO) initiatives. Arizona State University opened its largest research facility, the new Interdisciplinary Science and Technology Building IV (ISTB4) in September, 2012. As the new home of the School of Earth & Space Exploration (SESE), ISTB4 was designed to serve the school's dedication to K-12 education and public outreach. This dissertation presents a menu of ideas for revamping the EPO program for SESE. Utilizing the Delphi method, I was able to clarify which ideas would be most supported, and those that would not, by a variety of important SESE stakeholders. The study revealed that consensus exists in areas related to staffing and expansion of free programming, whereas less consensus exist in the areas of fee-based programs. The following most promising ideas for improving the SESE's EPO effort were identified and will be presented to SESE's incoming director in July, 2013: (a) hire a full-time director, theater manager, and program coordinator; (b) establish a service-learning requirement obligating undergraduate SESE majors to serve as docent support for outreach programs; (c) obligate all EPO operations to advise, assist, and contribute to the development of curricula, activities, and exhibits; (d) perform a market and cost analysis of other informational education venues offering similar programming; (3) establish a schedule of fee-based planetarium and film offerings; and (f) create an ISTB4 centric, fee-based package of programs specifically correlated to K12 education standards that can be delivered as a fieldtrip experience.
ContributorsFisher, Richard D. (Author) / Clark, Christopher M. (Thesis advisor) / Kelley, Michael (Committee member) / Glasper, Rufus (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Fully distributed wireless sensor networks (WSNs) without fusion center have advantages such as scalability in network size and energy efficiency in communications. Each sensor shares its data only with neighbors and then achieves global consensus quantities by in-network processing. This dissertation considers robust distributed parameter estimation methods, seeking global consensus

Fully distributed wireless sensor networks (WSNs) without fusion center have advantages such as scalability in network size and energy efficiency in communications. Each sensor shares its data only with neighbors and then achieves global consensus quantities by in-network processing. This dissertation considers robust distributed parameter estimation methods, seeking global consensus on parameters of adaptive learning algorithms and statistical quantities.

Diffusion adaptation strategy with nonlinear transmission is proposed. The nonlinearity was motivated by the necessity for bounded transmit power, as sensors need to iteratively communicate each other energy-efficiently. Despite the nonlinearity, it is shown that the algorithm performs close to the linear case with the added advantage of power savings. This dissertation also discusses convergence properties of the algorithm in the mean and the mean-square sense.

Often, average is used to measure central tendency of sensed data over a network. When there are outliers in the data, however, average can be highly biased. Alternative choices of robust metrics against outliers are median, mode, and trimmed mean. Quantiles generalize the median, and they also can be used for trimmed mean. Consensus-based distributed quantile estimation algorithm is proposed and applied for finding trimmed-mean, median, maximum or minimum values, and identification of outliers through simulation. It is shown that the estimated quantities are asymptotically unbiased and converges toward the sample quantile in the mean-square sense. Step-size sequences with proper decay rates are also discussed for convergence analysis.

Another measure of central tendency is a mode which represents the most probable value and also be robust to outliers and other contaminations in data. The proposed distributed mode estimation algorithm achieves a global mode by recursively shifting conditional mean of the measurement data until it converges to stationary points of estimated density function. It is also possible to estimate the mode by utilizing grid vector as well as kernel density estimator. The densities are estimated at each grid point, while the points are updated until they converge to a global mode.
ContributorsLee, Jongmin (Electrical engineer) (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Konstantinos (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2017
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Description
I investigate two models interacting agent systems: the first is motivated by the flocking and swarming behaviors in biological systems, while the second models opinion formation in social networks. In each setting, I define natural notions of convergence (to a ``flock" and to a ``consensus'', respectively), and study the convergence

I investigate two models interacting agent systems: the first is motivated by the flocking and swarming behaviors in biological systems, while the second models opinion formation in social networks. In each setting, I define natural notions of convergence (to a ``flock" and to a ``consensus'', respectively), and study the convergence properties of each in the limit as $t \rightarrow \infty$. Specifically, I provide sufficient conditions for the convergence of both of the models, and conduct numerical experiments to study the resulting solutions.
ContributorsTheisen, Ryan (Author) / Motsch, Sebastien (Thesis advisor) / Lanchier, Nicholas (Committee member) / Kostelich, Eric (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Distributed wireless sensor networks (WSNs) have attracted researchers recently due to their advantages such as low power consumption, scalability and robustness to link failures. In sensor networks with no fusion center, consensus is a process where

all the sensors in the network achieve global agreement using only local transmissions. In this

Distributed wireless sensor networks (WSNs) have attracted researchers recently due to their advantages such as low power consumption, scalability and robustness to link failures. In sensor networks with no fusion center, consensus is a process where

all the sensors in the network achieve global agreement using only local transmissions. In this dissertation, several consensus and consensus-based algorithms in WSNs are studied.

Firstly, a distributed consensus algorithm for estimating the maximum and minimum value of the initial measurements in a sensor network in the presence of communication noise is proposed. In the proposed algorithm, a soft-max approximation together with a non-linear average consensus algorithm is used. A design parameter controls the trade-off between the soft-max error and convergence speed. An analysis of this trade-off gives guidelines towards how to choose the design parameter for the max estimate. It is also shown that if some prior knowledge of the initial measurements is available, the consensus process can be accelerated.

Secondly, a distributed system size estimation algorithm is proposed. The proposed algorithm is based on distributed average consensus and L2 norm estimation. Different sources of error are explicitly discussed, and the distribution of the final estimate is derived. The CRBs for system size estimator with average and max consensus strategies are also considered, and different consensus based system size estimation approaches are compared.

Then, a consensus-based network center and radius estimation algorithm is described. The center localization problem is formulated as a convex optimization problem with a summation form by using soft-max approximation with exponential functions. Distributed optimization methods such as stochastic gradient descent and diffusion adaptation are used to estimate the center. Then, max consensus is used to compute the radius of the network area.

Finally, two average consensus based distributed estimation algorithms are introduced: distributed degree distribution estimation algorithm and algorithm for tracking the dynamics of the desired parameter. Simulation results for all proposed algorithms are provided.
ContributorsZhang, Sai (Electrical engineer) (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Spanias, Andreas (Thesis advisor) / Tsakalis, Kostas (Committee member) / Bliss, Daniel (Committee member) / Arizona State University (Publisher)
Created2017
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Description

The operation of Glen Canyon Dam on the Colorado River affects several downstream resources and water uses including water supply for consumptive uses in Arizona, California, and Nevada, hydroelectric power production, endangered species of native fish, recreational angling for non-native fish, and recreational boating in the Grand Canyon. Decisions about

The operation of Glen Canyon Dam on the Colorado River affects several downstream resources and water uses including water supply for consumptive uses in Arizona, California, and Nevada, hydroelectric power production, endangered species of native fish, recreational angling for non-native fish, and recreational boating in the Grand Canyon. Decisions about the magnitude and timing of water releases through the dam involve trade-offs between these resources and uses. The numerous laws affecting dam operations create a hierarchy of legal priorities that should govern these decisions. At the top of the hierarchy are mandatory requirements for water storage and delivery and for conservation of endangered species. Other resources and water uses have lower legal priorities. The Glen Canyon Dam Adaptive Management Program ("AMP") has substituted collaborative decision making among stakeholders for the hierarchy of priorities created by law. The AMP has thereby facilitated non-compliance with the Endangered Species Act by the Bureau of Reclamation, which operates the dam, and has effectively given hydroelectric power production and non-native fisheries higher priorities than they are legally entitled to. Adaptive management is consistent with the laws governing operation of Glen Canyon Dam, but collaborative decision making is not. Nor is collaborative decision making an essential, or even logical, component of adaptive management. As implemented in the case of Glen Canyon Dam, collaborative decision making has actually stifled adaptive management by making agreement among stakeholders a prerequisite to changes in the operation of the dam. This Article proposes a program for adaptive, but not collaborative, management of Glen Canyon Dam that would better conform to the law and would be more amenable to adaptation and experimentation than would the current, stakeholder-centered program.

ContributorsFeller, Joseph M. (Author)
Created2008-07-18
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This brief article, written for a symposium on "Collaboration and the Colorado River," evaluates the U.S. Department of the Interior's Glen Canyon Dam Adaptive Management Program ("AMP"). The AMP has been advanced as a pioneering collaborative and adaptive approach for both decreasing scientific uncertainty in support of regulatory decision-making and

This brief article, written for a symposium on "Collaboration and the Colorado River," evaluates the U.S. Department of the Interior's Glen Canyon Dam Adaptive Management Program ("AMP"). The AMP has been advanced as a pioneering collaborative and adaptive approach for both decreasing scientific uncertainty in support of regulatory decision-making and helping manage contentious resource disputes -- in this case, the increasingly thorny conflict over the Colorado River's finite natural resources. Though encouraging in some respects, the AMP serves as a valuable illustration of the flaws of existing regulatory processes purporting to incorporate collaboration and regulatory adaptation into the decision-making process. Born in the shadow of the law and improvised with too little thought as to its structure, the AMP demonstrates the need to attend to the design of the regulatory process and integrate mechanisms that compel systematic program evaluation and adaptation. As such, the AMP provides vital information on how future collaborative experiments might be modified to enhance their prospects of success.

ContributorsCamacho, Alejandro E. (Author)
Created2008-09-19
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With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of

With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort. Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.

ContributorsMelis, Theodore S. (Author) / Walters, Carl (Author) / Korman, Josh (Author)
Created2015
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The Glen Canyon Dam Adaptive Management Program (AMP) has been identified as a model for natural resource management. We challenge that assertion, citing the lack of progress toward a long-term management plan for the dam, sustained extra-programmatic conflict, and a downriver ecology that is still in jeopardy, despite over ten

The Glen Canyon Dam Adaptive Management Program (AMP) has been identified as a model for natural resource management. We challenge that assertion, citing the lack of progress toward a long-term management plan for the dam, sustained extra-programmatic conflict, and a downriver ecology that is still in jeopardy, despite over ten years of meetings and an expensive research program. We have examined the primary and secondary sources available on the AMP’s design and operation in light of best practices identified in the literature on adaptive management and collaborative decision-making. We have identified six shortcomings: (1) an inadequate approach to identifying stakeholders; (2) a failure to provide clear goals and involve stakeholders in establishing the operating procedures that guide the collaborative process; (3) inappropriate use of professional neutrals and a failure to cultivate consensus; (4) a failure to establish and follow clear joint fact-finding procedures; (5) a failure to produce functional written agreements; and (6) a failure to manage the AMP adaptively and cultivate long-term problem-solving capacity.

Adaptive management can be an effective approach for addressing complex ecosystem-related processes like the operation of the Glen Canyon Dam, particularly in the face of substantial complexity, uncertainty, and political contentiousness. However, the Glen Canyon Dam AMP shows that a stated commitment to collaboration and adaptive management is insufficient. Effective management of natural resources can only be realized through careful attention to the collaborative design and implementation of appropriate problem-solving and adaptive-management procedures. It also requires the development of an appropriate organizational infrastructure that promotes stakeholder dialogue and agency learning. Though the experimental Glen Canyon Dam AMP is far from a success of collaborative adaptive management, the lessons from its shortcomings can foster more effective collaborative adaptive management in the future by Congress, federal agencies, and local and state authorities.

ContributorsSusskind, Lawrence (Author) / Camacho, Alejandro E. (Author) / Schenk, Todd (Author)
Created2010-03-23
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DescriptionUnderstanding the evolution of opinions is a delicate task as the dynamics of how one changes their opinion based on their interactions with others are unclear.
ContributorsWeber, Dylan (Author) / Motsch, Sebastien (Thesis advisor) / Lanchier, Nicolas (Committee member) / Platte, Rodrigo (Committee member) / Armbruster, Dieter (Committee member) / Fricks, John (Committee member) / Arizona State University (Publisher)
Created2021
Description

Due to what is known as the “biologically desert fallacy” and the pervasive westernized ideal of wilderness that has influenced widespread American Conservation culture for millennia, urban areas have long been deemed as areas devoid of biodiversity. However, cities can contribute significantly to regional biodiversity and provide vital niches for

Due to what is known as the “biologically desert fallacy” and the pervasive westernized ideal of wilderness that has influenced widespread American Conservation culture for millennia, urban areas have long been deemed as areas devoid of biodiversity. However, cities can contribute significantly to regional biodiversity and provide vital niches for wildlife, illuminating the growing awareness that cities are crucial to the future of conservation and combating the global biodiversity crisis. In terms of the biodiversity crisis, bats are a relevant species of concern. In many studies, different bat species have been broadly classified according to their ability to adapt to urban environments. There is evidence that urban areas can filter bat species based on traits and behavior, with many bats possessing traits that do not allow them to live in cities. The three broad categories are urban avoiders, urban adapters, or urban exploiters based upon where their abundance is highest along a gradient of urban intensity. A common example of an urban exploiter bat is a Mexican Free-tailed bat, which can thrive and rely on urban environments and it is found in the Phoenix Metropolitan area. Bats are important as even in urban environments they play vital ecological roles such as cactus pollination, insect management, and seed dispersal. Bat Crazy is a thesis project focused on urban enhancement and the field of urban biodiversity. The goals of this thesis are to observe how bio-conscious urban cities that work to promote species conservation can serve as a positive tool to promote biodiversity and foster community education and engagement for their urban environment.

ContributorsKaiser, Nicole (Author) / Senko, Jesse (Thesis director) / Angilletta, Michael (Committee member) / Lynch, John (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Life Sciences (Contributor)
Created2023-05