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- Genre: Masters Thesis
- Creators: Johnston, Carol
- Creators: Turaga, Pavan
- Member of: ASU Electronic Theses and Dissertations
- Resource Type: Text
Description
One of the main challenges in planetary robotics is to traverse the shortest path through a set of waypoints. The shortest distance between any two waypoints is a direct linear traversal. Often times, there are physical restrictions that prevent a rover form traversing straight to a waypoint. Thus, knowledge of the terrain is needed prior to traversal. The Digital Terrain Model (DTM) provides information about the terrain along with waypoints for the rover to traverse. However, traversing a set of waypoints linearly is burdensome, as the rovers would constantly need to modify their orientation as they successively approach waypoints. Although there are various solutions to this problem, this research paper proposes the smooth traversability of the rover using splines as a quick and easy implementation to traverse a set of waypoints. In addition, a rover was used to compare the smoothness of the linear traversal along with the spline interpolations. The data collected illustrated that spline traversals had a less rate of change in the velocity over time, indicating that the rover performed smoother than with linear paths.
ContributorsKamasamudram, Anurag (Author) / Saripalli, Srikanth (Thesis advisor) / Fainekos, Georgios (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
The body is capable of regulating hunger in several ways. Some of these hunger regulation methods are innate, such as genetics, and some, such as the responses to stress and to the smell of food, are innate but can be affected by body conditions such as BMI and physical activity. Further, some hunger regulation methods stem from learned behaviors originating from cultural pressures or parenting styles. These latter regulation methods for hunger can be grouped into the categories: emotion, environment, and physical. The factors that regulate hunger can also influence the incidence of disordered eating, such as eating in the absence of hunger (EAH). Eating in the absence of hunger can occur in one of two scenarios, continuous EAH or beginning EAH. College students are at a particularly high risk for EAH and weight gain due to stress, social pressures, and the constant availability of energy dense and nutrient poor food options. The purpose of this study is to validate a modified EAH-C survey in college students and to discover which of the three latent factors (emotion, environment, physical) best predicts continual and beginning EAH. To do so, a modified EAH-C survey, with additional demographic components, was administered to students at a major southwest university. This survey contained two questions, one each for continuing and beginning EAH, regarding 14 factors related to emotional, physical, or environmental reasons that may trigger EAH. The results from this study revealed that the continual and beginning EAH surveys displayed good internal consistency reliability. We found that for beginning and continuing EAH, although emotion is the strongest predictor of EAH, all three latent factors are significant predictors of EAH. In addition, we found that environmental factors had the greatest influence on an individual's likelihood to continue to eat in the absence of hunger. Due to statistical abnormalities and differing numbers of factors in each category, we were unable to determine which of the three factors exerted the greatest influence on an individual's likelihood to begin eating in the absence of hunger. These results can be utilized to develop educational tools aimed at reducing EAH in college students, and ultimately reducing the likelihood for unhealthy weight gain and health complications related to obesity.
ContributorsGoett, Taylor (Author) / Johnston, Carol (Thesis advisor) / Lee, Chong (Committee member) / Lespron, Christy (Committee member) / Arizona State University (Publisher)
Created2013
Description
Our research focuses on finding answers through decentralized search, for complex, imprecise queries (such as "Which is the best hair salon nearby?") in situations where there is a spatiotemporal constraint (say answer needs to be found within 15 minutes) associated with the query. In general, human networks are good in answering imprecise queries. We try to use the social network of a person to answer his query. Our research aims at designing a framework that exploits the user's social network in order to maximize the answers for a given query. Exploiting an user's social network has several challenges. The major challenge is that the user's immediate social circle may not possess the answer for the given query, and hence the framework designed needs to carry out the query diffusion process across the network. The next challenge involves in finding the right set of seeds to pass the query to in the user's social circle. One other challenge is to incentivize people in the social network to respond to the query and thereby maximize the quality and quantity of replies. Our proposed framework is a mobile application where an individual can either respond to the query or forward it to his friends. We simulated the query diffusion process in three types of graphs: Small World, Random and Preferential Attachment. Given a type of network and a particular query, we carried out the query diffusion by selecting seeds based on attributes of the seed. The main attributes are Topic relevance, Replying or Forwarding probability and Time to Respond. We found that there is a considerable increase in the number of replies attained, even without saturating the user's network, if we adopt an optimal seed selection process. We found the output of the optimal algorithm to be satisfactory as the number of replies received at the interrogator's end was close to three times the number of neighbors an interrogator has. We addressed the challenge of incentivizing people to respond by associating a particular amount of points for each query asked, and awarding the same to people involved in answering the query. Thus, we aim to design a mobile application based on our proposed framework so that it helps in maximizing the replies for the interrogator's query by diffusing the query across his/her social network.
ContributorsSwaminathan, Neelakantan (Author) / Sundaram, Hari (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
We solve the problem of activity verification in the context of sustainability. Activity verification is the process of proving the user assertions pertaining to a certain activity performed by the user. Our motivation lies in incentivizing the user for engaging in sustainable activities like taking public transport or recycling. Such incentivization schemes require the system to verify the claim made by the user. The system verifies these claims by analyzing the supporting evidence captured by the user while performing the activity. The proliferation of portable smart-phones in the past few years has provided us with a ubiquitous and relatively cheap platform, having multiple sensors like accelerometer, gyroscope, microphone etc. to capture this evidence data in-situ. In this research, we investigate the supervised and semi-supervised learning techniques for activity verification. Both these techniques make use the data set constructed using the evidence submitted by the user. Supervised learning makes use of annotated evidence data to build a function to predict the class labels of the unlabeled data points. The evidence data captured can be either unimodal or multimodal in nature. We use the accelerometer data as evidence for transportation mode verification and image data as evidence for recycling verification. After training the system, we achieve maximum accuracy of 94% when classifying the transport mode and 81% when detecting recycle activity. In the case of recycle verification, we could improve the classification accuracy by asking the user for more evidence. We present some techniques to ask the user for the next best piece of evidence that maximizes the probability of classification. Using these techniques for detecting recycle activity, the accuracy increases to 93%. The major disadvantage of using supervised models is that it requires extensive annotated training data, which expensive to collect. Due to the limited training data, we look at the graph based inductive semi-supervised learning methods to propagate the labels among the unlabeled samples. In the semi-supervised approach, we represent each instance in the data set as a node in the graph. Since it is a complete graph, edges interconnect these nodes, with each edge having some weight representing the similarity between the points. We propagate the labels in this graph, based on the proximity of the data points to the labeled nodes. We estimate the performance of these algorithms by measuring how close the probability distribution of the data after label propagation is to the probability distribution of the ground truth data. Since labeling has a cost associated with it, in this thesis we propose two algorithms that help us in selecting minimum number of labeled points to propagate the labels accurately. Our proposed algorithm achieves a maximum of 73% increase in performance when compared to the baseline algorithm.
ContributorsDesai, Vaishnav (Author) / Sundaram, Hari (Thesis advisor) / Li, Baoxin (Thesis advisor) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this thesis, quantitative evaluation of quality of movement during stroke rehabilitation will be discussed. Previous research on stroke rehabilitation in hospital has been shown to be effective. In this thesis, we study various issues that arise when creating a home-based system that can be deployed in a patient's home. Limitation of motion capture due to reduced number of sensors leads to problems with design of kinematic features for quantitative evaluation. Also, the hierarchical three-level tasks of rehabilitation requires new design of kinematic features. In this thesis, the design of kinematic features for a home based stroke rehabilitation system will be presented. Results of the most challenging classifier are shown and proves the effectiveness of the design. Comparison between modern classification techniques and low computational cost threshold based classification with same features will also be shown.
ContributorsCheng, Long (Author) / Turaga, Pavan (Thesis advisor) / Arizona State University (Publisher)
Created2012
Description
Motion capture using cost-effective sensing technology is challenging and the huge success of Microsoft Kinect has been attracting researchers to uncover the potential of using this technology into computer vision applications. In this thesis, an upper-body motion analysis in a home-based system for stroke rehabilitation using novel RGB-D camera - Kinect is presented. We address this problem by first conducting a systematic analysis of the usability of Kinect for motion analysis in stroke rehabilitation. Then a hybrid upper body tracking approach is proposed which combines off-the-shelf skeleton tracking with a novel depth-fused mean shift tracking method. We proposed several kinematic features reliably extracted from the proposed inexpensive and portable motion capture system and classifiers that correlate torso movement to clinical measures of unimpaired and impaired. Experiment results show that the proposed sensing and analysis works reliably on measuring torso movement quality and is promising for end-point tracking. The system is currently being deployed for large-scale evaluations.
ContributorsDu, Tingfang (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Rikakis, Thanassis (Committee member) / Arizona State University (Publisher)
Created2012
Description
Dietary protein is known to increase postprandial thermogenesis more so than carbohydrates or fats, probably related to the fact that amino acids have no immediate form of storage in the body and can become toxic if not readily incorporated into body tissues or excreted. It is also well documented that subjects report greater satiety on high- versus low-protein diets and that subject compliance tends to be greater on high-protein diets, thus contributing to their popularity. What is not as well known is how a high-protein diet affects resting metabolic rate over time, and what is even less well known is if resting metabolic rate changes significantly when a person consuming an omnivorous diet suddenly adopts a vegetarian one. This pilot study sought to determine whether subjects adopting a vegetarian diet would report decreased satiety or demonstrate a decreased metabolic rate due to a change in protein intake and possible increase in carbohydrates. Further, this study sought to validate a new device called the SenseWear Armband (SWA) to determine if it might be sensitive enough to detect subtle changes in metabolic rate related to diet. Subjects were tested twice on all variables, at baseline and post-test. Independent and related samples tests revealed no significant differences between or within groups for any variable at any time point in the study. The SWA had a strong positive correlation to the Oxycon Mobile metabolic cart but due to a lack of change in metabolic rate, its sensitivity was undetermined. These data do not support the theory that adopting a vegetarian diet results in a long-term change in metabolic rate.
ContributorsMoore, Amy (Author) / Johnston, Carol (Thesis advisor) / Appel, Christy (Thesis advisor) / Gaesser, Glenn (Committee member) / Arizona State University (Publisher)
Created2012
Description
Objective: Vinegar consumption studies have demonstrated possible therapeutic effects in reducing HbA1c and postprandial glycemia. The purpose of the study was to closely examine the effects of a commercial vinegar drink on daily fluctuations in fasting glucose concentrations and postprandial glycemia, and on HbA1c, in individuals at risk for Type 2 Diabetes Mellitus (T2D). Design: Thirteen women and one man (21-62 y; mean, 46.0±3.9 y) participated in this 12-week parallel-arm trial. Participants were recruited from a campus community and were healthy and not diabetic by self-report. Participants were not prescribed oral hypoglycemic medications or insulin; other medications were allowed if use was stable for > 3 months. Subjects were randomized to one of two groups: VIN (8 ounces vinegar drink providing 1.5 g acetic acid) or CON (1 vinegar pill providing 0.04 g acetic acid). Treatments were taken twice daily immediately prior to the lunch and dinner meals. Venous blood samples were drawn at trial weeks 0 and 12 to measure insulin, fasting glucose, and HbA1c. Subjects recorded fasting glucose and 2-h postprandial glycemia concentrations daily using a glucometer. Results: The VIN group showed significant reductions in fasting capillary blood glucose concentrations (p=0.05) that were immediate and sustained throughout the duration of the study. The VIN group had reductions in 2-h postprandial glucose (mean change of −7.6±6.8 mg/dL over the 12-week trial), but this value was not significantly different than that for the CON group (mean change of 3.3±5.3 mg/dL over the 12-week trial, p=0.232). HbA1c did not significantly change (p=0.702), but the reduction in HbA1c in the VIN group, −0.14±0.1%, may have physiological relevance. Conclusions: Significant reductions in HbA1c were not observed after daily consumption of a vinegar drink containing 1.5 g acetic acid in non-diabetic individuals. However, the vinegar drink did significantly reduce fasting capillary blood glucose concentrations in these individuals as compared to a vinegar pill containing 0.04 g acetic acid. These results support a therapeutic effect for vinegar in T2D prevention and progression, specifically in high-risk populations.
ContributorsQuagliano, Samantha (Author) / Johnston, Carol (Thesis advisor) / Appel, Christy (Committee member) / Dixon, Kathleen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Objective: The purpose of this randomized parallel arm trial was to demonstrate the effects of daily fish oil supplementation (600mg per day for eight weeks) on body composition and body mass in young healthy women, aged 18-38, at a large southwestern university. Design: 26 non-obese (mean BMI 23.7±0.6 kg/m2), healthy women (18-38y; mean, 23.5±1.1 y) from a southwestern Arizona university campus community completed the study. Subjects were healthy, non-smokers, consuming less than 3.5 oz of fish per week according to self-report. Participants were randomized to one of two groups: FISH (600 mg omega-3 fatty acids provided in one gel capsule per day), or CON (1000 mg coconut oil placebo provided in one gel capsule per day). Body weight, BMI, and percent body fat were measured using a stadiometer and bioelectrical impedance scale at the screening visit and intervention weeks 1, 4, and 8. 24-hour dietary recalls were also performed at weeks 1 and 8. Results: 8 weeks of omega-3 fatty acid supplementation did not significantly alter body weight (p=0.830), BMI (p=1.00), or body fat percentage (p=0.600) as compared to placebo. Although not statistically significant, 24-hour dietary recalls performed at the beginning and end of the intervention revealed a trend towards increased caloric intake in the FISH group and decreased caloric intake in the CON group throughout the course of the study (p=0.069). If maintained, this difference in caloric intake could have physiological relevance. Conclusions: Omega-3 fatty acids do not significantly alter body weight or body composition in healthy young females. These findings do not refute the current recommendations for Americans to consume at least 8 oz of omega-3-rich seafood per week, supplying 250 mg EPA and DHA per day. More research is needed to investigate the potential for omega-3 fatty acids to modulate daily caloric intake.
ContributorsTeran, Bianca (Author) / Johnston, Carol (Thesis advisor) / Johnson, Melinda (Committee member) / Ohri-Vachaspati, Punam (Committee member) / Arizona State University (Publisher)
Created2013
Description
In 2002, a scientifically derived food guide pyramid for vegetarians, the Modified Food Guide for Lacto-ovo-vegetarians and Vegans was published and well received. Now that 10 years have passed, new scientific literature regarding the bioavailability of the nutrients of key concern in vegetarian diets has been published, and the graphical format of the nation's food guide has evolved from a pyramid shape into a circular plate. The objective of this research was to examine the post-2002 literature regarding the bioavailability of key nutrients in vegetarian diets; to use this information to update the recommendations made in the 2002 Modified Food Guide Pyramid for Lacto-ovo-vegetarians and Vegans; and to adapt this revised food plan to the new USDA MyPlate format. This process involved reviewing the scientific literature to determine if the DRIs for the nutrients of key concern in vegetarian diets are adequate for the vegetarian population and using this information to develop new recommendations for vegetarians if necessary, analyzing the nutrient content of representative foods in different food groups, reconfiguring the food groups so that foods with like nutrient components were grouped together, determining the number of servings of each food group required to meet vegetarians' nutrient requirements at three caloric levels, and developing sample menus. A circular plate graphic, the Vegetarian Plate, was designed to illustrate the recommendations of this updated food guide. This updated, scientifically derived food guide provides a sound base for diet planning for lacto-ovo-vegetarians and vegans. Further research is needed to assess the Vegetarian Plate's adequacy for children, pregnant and lactating women, athletes, and individuals with medical conditions or chronic diseases.
ContributorsFladell, Lauren (Author) / Johnston, Carol (Thesis advisor) / Vaughan, Linda (Committee member) / Shepard, Christina (Committee member) / Arizona State University (Publisher)
Created2013