Matching Items (44)
Description
In recent years, overall consumption of meat products has been decreasing, and at the same time vegetarianism is on the rise. A variety of factors are likely driving changes in consumers' attitudes towards, and consumption of, meat products. Although concern regarding animal welfare may contribute to these trends, growing consumer interest in the roles that production and processing of meat play in terms of environmental degradation could also impact individuals' decisions about the inclusion of meat in their diets. Because these factors could be related to moral attitudes as well, the purpose of this study was to explore the relations among meat consumption, general environmental attitudes, and moral `foundations' of decision-making, including concern about minimizing `harm' and maximizing `care,' as well as issues of `purity' and `sanctity.' A survey was conducted among current college students using the New Ecological Paradigm scale and the Moral Foundations Questionnaire to assess environmental and moral attitudes. A food frequency questionnaire was used to assess meat consumption. Multiple linear regression analyses explored the relations of environmental and moral attitudes with meat consumption, controlling for potential confounding variables. The results showed no significant correlations among meat consumption, environmental attitudes or moral foundations of harm/care and purity/sanctity.
ContributorsSpringer, LeeAnn (Author) / Wharton, Christopher (Christopher Mack), 1977- (Thesis advisor) / Hekler, Eric (Thesis advisor) / Ohri-Vachaspati, Punam (Committee member) / Hall, Rick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Majority of the Sensor networks consist of low-cost autonomously powered devices, and are used to collect data in physical world. Today's sensor network deployments are mostly application specific & owned by a particular entity. Because of this application specific nature & the ownership boundaries, this modus operandi hinders large scale sensing & overall network operational capacity. The main goal of this research work is to create a mechanism to dynamically form personal area networks based on mote class devices spanning ownership boundaries. When coupled with an overlay based control system, this architecture can be conveniently used by a remote client to dynamically create sensor networks (personal area network based) even when the client does not own a network. The nodes here are "borrowed" from existing host networks & the application related to the newly formed network will co-exist with the native applications thanks to concurrency. The result allows users to embed a single collection tree onto spatially distant networks as if they were within communication range. This implementation consists of core operating system & various other external components that support injection maintenance & dissolution sensor network applications at client's request. A large object data dissemination protocol was designed for reliable application injection. The ability of this system to remotely reconfigure a network is useful given the high failure rate of real-world sensor network deployments. Collaborative sensing, various physical phenomenon monitoring also be considered as applications of this architecture.
ContributorsFernando, M. S. R (Author) / Dasgupta, Partha (Thesis advisor) / Bhattacharya, Amiya (Thesis advisor) / Gupta, Sandeep (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study was designed to influence consumer habits, specifically those relating to purchases of fruits, vegetables, and junk food. Previous studies have clearly shown the ineffectiveness of simply describing the health benefits of eating more fruits and vegetables (F/V). In contrast, this study aimed to change the result by changing the message: providing participants with insight into the hidden agendas of food companies and grocery stores, provide useful tips on how to include children when selecting F/V, and emphasizing the importance of parental modeling in regard to food purchases. Participants of this study were separated into two groups, the tour group and the education group. The tour group was guided through a grocery store where they learned about sales tactics and manipulations used by grocery stores and food companies to influence purchases. Education group participants were provided with an education session focusing on USDA and FDA handouts displaying current educational suggestions for increasing F/V consumption. Grocery store receipts were collected and analyzed to track the progress of both groups. The goal of the study was to identify a method of informing consumers that will produce a significant change in behavior. Increasing F/V consumption, even in relatively small amounts, would be an important step forward in improving the diet and overall health of Americans. This study was the first of its kind to measure purchasing patterns objectively (through analysis of purchase receipts, rather than personal opinion/evaluation surveys) and in a wide-scope retail environment that includes all grocery store purchases by participants. Significant increases or decreases in the amount of money spent on F/V, or the amount (pounds) of F/V purchased were not seen, however a small correlation (r = 0.133) exists when comparing the weight of F/V purchased pre/post intervention. Data from Food Frequency Questionnaires shows participants consuming significantly higher amounts of F/V post intervention (p=0.043). The tour group and education group experienced an average increase of 0.7 servings per day. Future interventions might benefit by extending their scope to include cooking demonstrations, in-home interventions, and education on healthy eating outside of the home.
ContributorsKinsfather, Diana (Author) / Johnston, Carol (Thesis advisor) / Hekler, Eric (Committee member) / Tetreault, Colin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Wireless technologies for health monitoring systems have seen considerable interest in recent years owing to it's potential to achieve vision of pervasive healthcare, that is healthcare to anyone, anywhere and anytime. Development of wearable wireless medical devices which have the capability to sense, compute, and send physiological information to a mobile gateway, forming a Body Sensor Network (BSN) is considered as a step towards achieving the vision of pervasive health monitoring systems (PHMS). PHMS consisting of wearable body sensors encourages unsupervised long-term monitoring, reducing frequent visit to hospital and nursing cost. Therefore, it is of utmost importance that operation of PHMS must be reliable, safe and have longer lifetime. A model-based automatic code generation provides a state-of-art code generation of sensor and smart phone code from high-level specification of a PHMS. Code generator intakes meta-model of PHMS specification, uses codebase containing code templates and algorithms, and generates platform specific code. Health-Dev, a framework for model-based development of PHMS, uses code generation to implement PHMS in sensor and smart phone. As a part of this thesis, model-based automatic code generation was evaluated and experimentally validated. The generated code was found to be safe in terms of ensuring no race condition, array, or pointer related errors in the generated code and more optimized as compared to hand-written BSN benchmark code in terms of lesser unreachable code.
ContributorsVerma, Sunit (Author) / Gupta, Sandeep (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2013
Description
Increasing computational demands in data centers require facilities to operate at higher ambient temperatures and at higher power densities. Conventionally, data centers are cooled with electrically-driven vapor-compressor equipment. This paper proposes an alternative data center cooling architecture that is heat-driven. The source is heat produced by the computer equipment. This dissertation details experiments investigating the quantity and quality of heat that can be captured from a liquid-cooled microprocessor on a computer server blade from a data center. The experiments involve four liquid-cooling setups and associated heat-extraction, including a radical approach using mineral oil. The trials examine the feasibility of using the thermal energy from a CPU to drive a cooling process. Uniquely, the investigation establishes an interesting and useful relationship simultaneously among CPU temperatures, power, and utilization levels. In response to the system data, this project explores the heat, temperature and power effects of adding insulation, varying water flow, CPU loading, and varying the cold plate-to-CPU clamping pressure. The idea is to provide an optimal and steady range of temperatures necessary for a chiller to operate. Results indicate an increasing relationship among CPU temperature, power and utilization. Since the dissipated heat can be captured and removed from the system for reuse elsewhere, the need for electricity-consuming computer fans is eliminated. Thermocouple readings of CPU temperatures as high as 93°C and a calculated CPU thermal energy up to 67Wth show a sufficiently high temperature and thermal energy to serve as the input temperature and heat medium input to an absorption chiller. This dissertation performs a detailed analysis of the exergy of a processor and determines the maximum amount of energy utilizable for work. Exergy as a source of realizable work is separated into its two contributing constituents: thermal exergy and informational exergy. The informational exergy is that usable form of work contained within the most fundamental unit of information output by a switching device within a CPU. Exergetic thermal, informational and efficiency values are calculated and plotted for our particular CPU, showing how the datasheet standards compare with experimental values. The dissertation concludes with a discussion of the work's significance.
ContributorsHaywood, Anna (Author) / Phelan, Patrick E (Thesis advisor) / Herrmann, Marcus (Committee member) / Gupta, Sandeep (Committee member) / Trimble, Steve (Committee member) / Myhajlenko, Stefan (Committee member) / Arizona State University (Publisher)
Created2014
Description
The energy consumption of data centers is increasing steadily along with the associ- ated power-density. Approximately half of such energy consumption is attributed to the cooling energy, as a result of which reducing cooling energy along with reducing servers energy consumption in data centers is becoming imperative so as to achieve greening of the data centers. This thesis deals with cooling energy management in data centers running data-processing frameworks. In particular, we propose ther- mal aware scheduling for MapReduce framework and its Hadoop implementation to reduce cooling energy in data centers. Data-processing frameworks run many low- priority batch processing jobs, such as background log analysis, that do not have strict completion time requirements; they can be delayed by a bounded amount of time. Cooling energy savings are possible by being able to temporally spread the workload, and assign it to the computing equipments which reduce the heat recirculation in data center room and therefore the load on the cooling systems. We implement our scheme in Hadoop and performs some experiments using both CPU-intensive and I/O-intensive workload benchmarks in order to evaluate the efficiency of our scheme. The evaluation results highlight that our thermal aware scheduling reduces hot-spots and makes uniform temperature distribution within the data center possible. Sum- marizing the contribution, we incorporated thermal awareness in Hadoop MapReduce framework by enhancing the native scheduler to make it thermally aware, compare the Thermal Aware Scheduler(TAS) with the Hadoop scheduler (FCFS) by running PageRank and TeraSort benchmarks in the BlueTool data center of Impact lab and show that there is reduction in peak temperature and decrease in cooling power using TAS over FCFS scheduler.
ContributorsKole, Sayan (Author) / Gupta, Sandeep (Thesis advisor) / Huang, Dijiang (Committee member) / Varsamopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2013
Description
Children are five times more likely to be overweight at the age of 12 years if they are overweight during the preschool period, and 60% of overweight preschoolers are overweight at the age of 12 years (Matusik & Malecka-Tendera, 2011). Primary care interventions are urgently needed to improve healthy lifestyle behaviors in families. Parental influence plays an important factor in the development of healthy behaviors in children. Cognitive behavioral interventions have demonstrated preliminary success in promoting healthy lifestyle behaviors in both adults and children. Mobile technology used to supplement interventions aimed at behavior change offers an outlet to bridge gaps in health disparities and generate innovative evidence. Therefore, the purpose of this research was to establish the feasibility, acceptability, and preliminary effects of a cognitive-behavioral intervention (TEXT2COPE) synergized with mobile technology on the healthy lifestyle behaviors of parents of overweight and obese preschoolers. Primary aims of the proposed pilot study were to (a) examine the feasibility and acceptability of the TEXT2COPE program among parents of overweight or obese preschoolers with mobile phones; (b) evaluate the preliminary effects of the TEXT2COPE program on healthy lifestyle behaviors in families with overweight or obese preschoolers; and (c) evaluate the relationship among the study variables (i.e., cognitive beliefs, perceived difficulty, and healthy lifestyle behaviors). Findings indicate that this program is feasible and acceptable in this population. The intervention improved healthy lifestyle beliefs and behaviors in parents. Further supported are the interconnected relationships between parental beliefs, thoughts, and behaviors.
ContributorsMilitello, Lisa K (Author) / Melnyk, Bernadette M (Thesis advisor) / Small, Leigh (Committee member) / Hekler, Eric (Committee member) / Jacobson, Diana (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the ever-increasing demand for high-end services, technological companies have been forced to operate on high performance servers. In addition to the customer services, the company's internal need to store and manage huge amounts of data has also increased their need to invest in High Density Data Centers. As a result, the performance to size of the data center has increased tremendously. Most of the consumed power by the servers is emitted as heat. In a High Density Data Center, the power per floor space area is higher compared to the regular data center. Hence the thermal management of this type of data center is relatively complicated.
Because of the very high power emission in a smaller containment, improper maintenance can result in failure of the data center operation in a shorter period. Hence the response time of the cooler to the temperature rise of the servers is very critical. Any delay in response will constantly lead to increased temperature and hence the server's failure.
In this paper, the significance of this delay time is understood by performing CFD simulation on different variants of High Density Modules using ANSYS Fluent. It was found out that the delay was becoming longer as the size of the data center increases. But the overload temperature, ie. the temperature rise beyond the set-point became lower with the increase in data center size. The results were common for both the single-row and the double-row model. The causes of the increased delay are accounted and explained in detail manner in this paper.
Because of the very high power emission in a smaller containment, improper maintenance can result in failure of the data center operation in a shorter period. Hence the response time of the cooler to the temperature rise of the servers is very critical. Any delay in response will constantly lead to increased temperature and hence the server's failure.
In this paper, the significance of this delay time is understood by performing CFD simulation on different variants of High Density Modules using ANSYS Fluent. It was found out that the delay was becoming longer as the size of the data center increases. But the overload temperature, ie. the temperature rise beyond the set-point became lower with the increase in data center size. The results were common for both the single-row and the double-row model. The causes of the increased delay are accounted and explained in detail manner in this paper.
ContributorsRamaraj, Dinesh Balaji (Author) / Gupta, Sandeep (Thesis advisor) / Hermann, Marcus (Committee member) / Huang, Huei-Ping (Committee member) / Arizona State University (Publisher)
Created2015
Description
There are multivariate factors that not only play a role in an individual's ability to lose weight, but may create barriers to his or her success. One such factor is internalized weight bias (IWB), which is inversely associated with weight loss outcomes and body satisfaction, and directly associated with psychosocial maladjustments such as depression and binge eating. This study examined the relationship between internalized weight bias and weight loss outcomes using a coding scheme developed for an online weight loss forum to see whether results would be consistent with self-administered surveys that measure IWB. The coding scheme was developed using an exploratory factor analysis of a survey composed of existing measures of IWB. Participants' posts within an online weight loss forum were coded and participants given a weekly IWB score that was compared to weekly weight loss using mixed model analysis. No significance was found between IWB and weight loss outcomes in this study, however, the coding scheme developed is a novel approach to measuring IWB, and the categories identified from latent constructs of IWB may be used in the future to determine the dimensions that exist within it. Ultimately, a better understanding of IWB could lead to the development of targeted weight loss interventions that address the beliefs and attitudes held by individuals who experience it.
ContributorsEscajeda, Janessa (Author) / Hekler, Eric (Thesis advisor) / Barroso, Cristina (Thesis advisor) / Dixon, Kathleen (Committee member) / Arizona State University (Publisher)
Created2015
Description
S-Taliro is a fully functional Matlab toolbox that searches for trajectories of minimal robustness in hybrid systems that are implemented as either m-functions or Simulink/State flow models. Trajectories with minimal robustness are found using automatic testing of hybrid systems against user specifications. In this work we use Metric Temporal Logic (MTL) to describe the user specifications for the hybrid systems. We then try to falsify the MTL specification using global minimization of robustness metric. Global minimization is carried out using stochastic optimization algorithms like Monte-Carlo (MC) and Extended Ant Colony Optimization (EACO) algorithms. Irrespective of the type of the model we provide as an input to S-Taliro, the user needs to specify the MTL specification, the initial conditions and the bounds on the inputs. S-Taliro then uses this information to generate test inputs which are used to simulate the system. The simulation trace is then provided as an input to Taliro which computes the robustness estimate of the MTL formula. Global minimization of this robustness metric is performed to generate new test inputs which again generate simulation traces which are closer to falsifying the MTL formula. Traces with negative robustness values indicate that the simulation trace falsified the MTL formula. Traces with positive robustness values are also of great importance because they indicate how robust the system is against the given specification. S-Taliro has been seamlessly integrated into the Matlab environment, which is extensively used for model-based development of control software. Moreover the toolbox has been developed in a modular fashion and therefore adding new optimization algorithms is easy and straightforward. In this work I present the architecture of S-Taliro and its working on a few benchmark problems.
ContributorsAnnapureddy, Yashwanth Singh Rahul (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Gupta, Sandeep (Committee member) / Arizona State University (Publisher)
Created2011