Matching Items (476)
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Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find

Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
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The stigma surrounding math- that it is difficult, pointless, and requires your brain to be wired a certain way- has for a long time impacted the success of students throughout their schooling. Students sometimes perceive math as boring and begin to lose focus when the math concepts become more abstract

The stigma surrounding math- that it is difficult, pointless, and requires your brain to be wired a certain way- has for a long time impacted the success of students throughout their schooling. Students sometimes perceive math as boring and begin to lose focus when the math concepts become more abstract as they reach middle school and high school. Sixth grade is when the brain shifts to more abstract thinking as kids transition from the concrete operational stage to the formal operational stage of cognitive development. This shift is reflected in the math curriculum and contributes to the struggle students face in learning math. To increase student engagement, gamification is a way to incorporate elements of gaming into education. Gamification can be used to motivate and encourage students to participate in their learning. In this project, a unit for 6th graders was designed to help combat students' math perception and failure that centers around a mystery game. Students learn about variables and expressions while engaging with the interactive mystery.

ContributorsCarson, Emma Charlotte (Author) / Barnett, Juliet (Thesis director) / Zucker, Stanley (Committee member) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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As climate change continues to escalate natural hazards around the globe, certain communities feel the impacts of these disasters more so than others. After Hurricane Maria devastated communities in 2017, Puerto Rico struggled to respond to the needs of its citizens, particularly those in rural areas. Many of the regions

As climate change continues to escalate natural hazards around the globe, certain communities feel the impacts of these disasters more so than others. After Hurricane Maria devastated communities in 2017, Puerto Rico struggled to respond to the needs of its citizens, particularly those in rural areas. Many of the regions affected did not have resilient community structures in place to be able to withstand the systemic ripple effects of the hurricane. However, various community endeavors have developed post-Hurricane Maria to foster community collaboration and resiliency, including the development of agricultural tourism, otherwise known as agritourism. <br/>Although agritourism has begun to develop in rural regions of Puerto Rico, including the municipalities of Utuado, Ciales, Florida, and Jayuya, a systems-understanding is lacking of the current agritourism situation in the region and its related capacities, limitations, and opportunities of agritourism. To address this gap, a spatially explicit understanding and map of the underlying tourism infrastructure is needed to support the development of sustainable agritourism in Utuado, Jayuya, Ciales, and Florida municipalities in Puerto Rico. <br/>This report spatially represents the current state of tourism opportunities in the region as a result of asking “What are the spatial networks of gastronomy, accommodations, farms, and attractions that support the development of agritourism in Utuado, Jayuya, Ciales and Florida municipalities in Puerto Rico?” Three steps lead to the spatial representation starting with developing a comprehensive inventory. Second, we visualize the spatial map through Google Maps. Lastly, we explore the larger context of the report through an ArcGIS Storymap. The inventory will help with better understanding the number and variety of tourism resources available. The spatial visualization will help with understanding the distribution of resources and explore potential connections between resources and what relationships could be fostered in the future. Lastly, the ArcGIS Storymap will serve as a framework for outlining the future development of the SARE project. Overall, this report outlines the spatial maps of tourism resources and provides a tool to be used by community partners, tourists, and project partners.

ContributorsCretors, Kasey Ann (Author) / Brundiers, Katja (Thesis director) / Holladay, Patrick (Committee member) / Lazaro, Pablo Mendez (Committee member) / School of International Letters and Cultures (Contributor) / School of Sustainability (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

I have created a workshop for educators. The workshop describes the significance of adverse childhood experiences in a student's life. It also displays how an educator might use Social Emotional Learning strategies to support students who have experienced trauma.

ContributorsPierce, Alyssa Cruz (Author) / Oliver, Jill (Thesis director) / Roderick, Valerie (Committee member) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde

The COVID-19 Pandemic has provided a challenge for educators to create virtual learning materials that are engaging and impactful during times of high stress and isolation. In this creative project, I explore the variety of virtual tools and web applications from Esri by creating a Story Map on the Verde River Watershed. This Story Map is intended for an audience of students in late middle school and early high school but can be a resource to teachers for a wider age range. The integration of interactive technology and virtual tools in educational practices is likely to continue past the immediate circumstances of the COVID-19 pandemic. The purpose of this Story Map is to showcase one of the many uses for geospatial web applications beyond the immediate realm of GIS.

ContributorsTueller, Margaret (Author) / Frazier, Amy (Thesis director) / Dorn, Ron (Committee member) / School of Geographical Sciences and Urban Planning (Contributor, Contributor, Contributor) / Division of Teacher Preparation (Contributor) / The Design School (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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The purpose of our study was to examine the effectiveness of a cycling intervention on body composition in adolescents with Down syndrome (DS). Participants completed one of three interventions over eight consecutive weeks. The interventions were: 1) Voluntary Cycling (VC), in which participants cycled at their self-selected pedaling rate 2)

The purpose of our study was to examine the effectiveness of a cycling intervention on body composition in adolescents with Down syndrome (DS). Participants completed one of three interventions over eight consecutive weeks. The interventions were: 1) Voluntary Cycling (VC), in which participants cycled at their self-selected pedaling rate 2) Assisted Cycling (AC), in which the participants' voluntary pedaling rates were assisted with a motor to ensure the maintenance of 80 rpms. 3) No cycling (NC), in which the participants acted as controls. Participants in the AC intervention did not decrease body fat or increase lean body mass however they did maintain these measures during the intervention as compared to the VC and NO participants who increased body fat and decreased lean body mass. These statistics were not exactly as expected nor were they statistically significant. Future research will try to replicate this data with statistically significant values for more cycling adolescents with DS using more randomized intervention groups.
ContributorsBennett, Kristen Leigh (Author) / Ringenbach, Shannon (Thesis director) / Brown, Steven (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
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This research study examined the effects of assisted cycling using a stationary recumbent bicycle that had an internal motor to help participants pedal at a desired cadence. The participants were either placed in an Assisted Cycling (AC), Voluntary Cycling (VC), or No Cycling (NC) intervention group. Those placed in the

This research study examined the effects of assisted cycling using a stationary recumbent bicycle that had an internal motor to help participants pedal at a desired cadence. The participants were either placed in an Assisted Cycling (AC), Voluntary Cycling (VC), or No Cycling (NC) intervention group. Those placed in the AC of VC groups then came to a laboratory setting 3 days a week for 8 weeks to cycle for 30 minutes. This research specifically analyzes the Vineland Adaptive Behavior Scale II to analyze the changes in daily living skills and maladaptive behaviors pre and post the exercise intervention. After analyzing the VABS II scores it was found that those in the VC intervention had statistically significant improvements in maladaptive behaviors. An interpretation of this finding is that the VC intervention had an increased heart rate over the span of the intervention and had a larger power output than those in the AC group. A limitation of this research is that it was a self-reported questionnaire that was given to the caregivers of the participant. The caregivers were not always controlled for, so in some cases two different caregivers were given the questionnaire for a single participant. A suggestion for future research would be to use the participant's mental age versus their chronological age when using the VABS-II and to use the Adaptive Behaviors Assessment System III (ABAS-III).
ContributorsJenkins, Cayla Marie (Author) / Ringenbach, Shannon (Thesis director) / Kulinna, Pamela (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-05
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Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing

Advancements in mobile technologies have significantly enhanced the capabilities of mobile devices to serve as powerful platforms for sensing, processing, and visualization. Surges in the sensing technology and the abundance of data have enabled the use of these portable devices for real-time data analysis and decision-making in digital signal processing (DSP) applications. Most of the current efforts in DSP education focus on building tools to facilitate understanding of the mathematical principles. However, there is a disconnect between real-world data processing problems and the material presented in a DSP course. Sophisticated mobile interfaces and apps can potentially play a crucial role in providing a hands-on-experience with modern DSP applications to students. In this work, a new paradigm of DSP learning is explored by building an interactive easy-to-use health monitoring application for use in DSP courses. This is motivated by the increasing commercial interest in employing mobile phones for real-time health monitoring tasks. The idea is to exploit the computational abilities of the Android platform to build m-Health modules with sensor interfaces. In particular, appropriate sensing modalities have been identified, and a suite of software functionalities have been developed. Within the existing framework of the AJDSP app, a graphical programming environment, interfaces to on-board and external sensor hardware have also been developed to acquire and process physiological data. The set of sensor signals that can be monitored include electrocardiogram (ECG), photoplethysmogram (PPG), accelerometer signal, and galvanic skin response (GSR). The proposed m-Health modules can be used to estimate parameters such as heart rate, oxygen saturation, step count, and heart rate variability. A set of laboratory exercises have been designed to demonstrate the use of these modules in DSP courses. The app was evaluated through several workshops involving graduate and undergraduate students in signal processing majors at Arizona State University. The usefulness of the software modules in enhancing student understanding of signals, sensors and DSP systems were analyzed. Student opinions about the app and the proposed m-health modules evidenced the merits of integrating tools for mobile sensing and processing in a DSP curriculum, and familiarizing students with challenges in modern data-driven applications.
ContributorsRajan, Deepta (Author) / Spanias, Andreas (Thesis advisor) / Frakes, David (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human

With robots being used extensively in various areas, a certain degree of robot autonomy has always been found desirable. In applications like planetary exploration, autonomous path planning and navigation are considered essential. But every now and then, a need to modify the robot's operation arises, a need for a human to provide it some supervisory parameters that modify the degree of autonomy or allocate extra tasks to the robot. In this regard, this thesis presents an approach to include a provision to accept and incorporate such human inputs and modify the navigation functions of the robot accordingly. Concepts such as applying kinematical constraints while planning paths, traversing of unknown areas with an intent of maximizing field of view, performing complex tasks on command etc. have been examined and implemented. The approaches have been tested in Robot Operating System (ROS), using robots such as the iRobot Create, Personal Robotics (PR2) etc. Simulations and experimental demonstrations have proved that this approach is feasible for solving some of the existing problems and that it certainly can pave way to further research for enhancing functionality.
ContributorsVemprala, Sai Hemachandra (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
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In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints.

In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints. Developing a framework to enable cooperative behavior adoption and to sustain it for a long period of time is a major challenge. As a part of developing this framework, I am focusing on methods to understand behavior diffusion over time. Facilitating behavior diffusion with resource constraints in a large population is qualitatively different from promoting cooperation in small groups. Previous work in social sciences has derived conditions for sustainable cooperative behavior in small homogeneous groups. However, how groups of individuals having resource constraint co-operate over extended periods of time is not well understood, and is the focus of my thesis. I develop models to analyze behavior diffusion over time through the lens of epidemic models with the condition that individuals have resource constraint. I introduce an epidemic model SVRS ( Susceptible-Volatile-Recovered-Susceptible) to accommodate multiple behavior adoption. I investigate the longitudinal effects of behavior diffusion by varying different properties of an individual such as resources,threshold and cost of behavior adoption. I also consider how behavior adoption of an individual varies with her knowledge of global adoption. I evaluate my models on several synthetic topologies like complete regular graph, preferential attachment and small-world and make some interesting observations. Periodic injection of early adopters can help in boosting the spread of behaviors and sustain it for a longer period of time. Also, behavior propagation for the classical epidemic model SIRS (Susceptible-Infected-Recovered-Susceptible) does not continue for an infinite period of time as per conventional wisdom. One interesting future direction is to investigate how behavior adoption is affected when number of individuals in a network changes. The affects on behavior adoption when availability of behavior changes with time can also be examined.
ContributorsDey, Anindita (Author) / Sundaram, Hari (Thesis advisor) / Turaga, Pavan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013