ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Sen, Arunabha
- Creators: Shen, Wei
- Creators: Kaloush, Kamil
Description
In recent years, an increase of environmental temperature in urban areas has raised many concerns. These areas are subjected to higher temperature compared to the rural surrounding areas. Modification of land surface and the use of materials such as concrete and/or asphalt are the main factors influencing the surface energy balance and therefore the environmental temperature in the urban areas. Engineered materials have relatively higher solar energy absorption and tend to trap a relatively higher incoming solar radiation. They also possess a higher heat storage capacity that allows them to retain heat during the day and then slowly release it back into the atmosphere as the sun goes down. This phenomenon is known as the Urban Heat Island (UHI) effect and causes an increase in the urban air temperature. Many researchers believe that albedo is the key pavement affecting the urban heat island. However, this research has shown that the problem is more complex and that solar reflectivity may not be the only important factor to evaluate the ability of a pavement to mitigate UHI. The main objective of this study was to analyze and research the influence of pavement materials on the near surface air temperature. In order to accomplish this effort, test sections consisting of Hot Mix Asphalt (HMA), Porous Hot Mix asphalt (PHMA), Portland Cement Concrete (PCC), Pervious Portland Cement Concrete (PPCC), artificial turf, and landscape gravels were constructed in the Phoenix, Arizona area. Air temperature, albedo, wind speed, solar radiation, and wind direction were recorded, analyzed and compared above each pavement material type. The results showed that there was no significant difference in the air temperature at 3-feet and above, regardless of the type of the pavement. Near surface pavement temperatures were also measured and modeled. The results indicated that for the UHI analysis, it is important to consider the interaction between pavement structure, material properties, and environmental factors. Overall, this study demonstrated the complexity of evaluating pavement structures for UHI mitigation; it provided great insight on the effects of material types and properties on surface temperatures and near surface air temperature.
ContributorsPourshams-Manzouri, Tina (Author) / Kaloush, Kamil (Thesis advisor) / Wang, Zhihua (Thesis advisor) / Zapata, Claudia E. (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Vehicle type choice is a significant determinant of fuel consumption and energy sustainability; larger, heavier vehicles consume more fuel, and expel twice as many pollutants, than their smaller, lighter counterparts. Over the course of the past few decades, vehicle type choice has seen a vast shift, due to many households making more trips in larger vehicles with lower fuel economy. During the 1990s, SUVs were the fastest growing segment of the automotive industry, comprising 7% of the total light vehicle market in 1990, and 25% in 2005. More recently, due to rising oil prices, greater awareness to environmental sensitivity, the desire to reduce dependence on foreign oil, and the availability of new vehicle technologies, many households are considering the use of newer vehicles with better fuel economy, such as hybrids and electric vehicles, over the use of the SUV or low fuel economy vehicles they may already own. The goal of this research is to examine how vehicle miles traveled, fuel consumption and emissions may be reduced through shifts in vehicle type choice behavior. Using the 2009 National Household Travel Survey data it is possible to develop a model to estimate household travel demand and total fuel consumption. If given a vehicle choice shift scenario, using the model it would be possible to calculate the potential fuel consumption savings that would result from such a shift. In this way, it is possible to estimate fuel consumption reductions that would take place under a wide variety of scenarios.
ContributorsChristian, Keith (Author) / Pendyala, Ram M. (Thesis advisor) / Chester, Mikhail (Committee member) / Kaloush, Kamil (Committee member) / Ahn, Soyoung (Committee member) / Arizona State University (Publisher)
Created2013
Description
With the advent of social media (like Twitter, Facebook etc.,) people are easily sharing their opinions, sentiments and enforcing their ideologies on others like never before. Even people who are otherwise socially inactive would like to share their thoughts on current affairs by tweeting and sharing news feeds with their friends and acquaintances. In this thesis study, we chose Twitter as our main data platform to analyze shifts and movements of 27 political organizations in Indonesia. So far, we have collected over 30 million tweets and 150,000 news articles from RSS feeds of the corresponding organizations for our analysis. For Twitter data extraction, we developed a multi-threaded application which seamlessly extracts, cleans and stores millions of tweets matching our keywords from Twitter Streaming API. For keyword extraction, we used topics and perspectives which were extracted using n-grams techniques and later approved by our social scientists. After the data is extracted, we aggregate the tweet contents that belong to every user on a weekly basis. Finally, we applied linear and logistic regression using SLEP, an open source sparse learning package to compute weekly score for users and mapping them to one of the 27 organizations on a radical or counter radical scale. Since, we are mapping users to organizations on a weekly basis, we are able to track user's behavior and important new events that triggered shifts among users between organizations. This thesis study can further be extended to identify topics and organization specific influential users and new users from various social media platforms like Facebook, YouTube etc. can easily be mapped to existing organizations on a radical or counter-radical scale.
ContributorsPoornachandran, Sathishkumar (Author) / Davulcu, Hasan (Thesis advisor) / Sen, Arunabha (Committee member) / Woodward, Mark (Committee member) / Arizona State University (Publisher)
Created2013
Description
Heating of asphalt during production and construction causes the volatilization and oxidation of binders used in mixes. Volatilization and oxidation causes degradation of asphalt pavements by increasing the stiffness of the binders, increasing susceptibility to cracking and negatively affecting the functional and structural performance of the pavements. Degradation of asphalt binders by volatilization and oxidation due to high production temperature occur during early stages of pavement life and are known as Short Term Aging (STA). Elevated temperatures and increased exposure time to elevated temperatures causes increased STA of asphalt. The objective of this research was to investigate how elevated mixing temperatures and exposure time to elevated temperatures affect aging and stiffening of binders, thus influencing properties of the asphalt mixtures. The study was conducted in two stages. The first stage evaluated STA effect of asphalt binders. It involved aging two Performance Graded (PG) virgin asphalt binders, PG 76-16 and PG 64-22 at two different temperatures and durations, then measuring their viscosities. The second stage involved evaluating the effects of elevated STA temperature and time on properties of the asphalt mixtures. It involved STA of asphalt mixtures produced in the laboratory with the PG 64-22 binder at mixing temperatures elevated 25OF above standard practice; STA times at 2 and 4 hours longer than standard practices, and then compacted in a gyratory compactor. Dynamic modulus (E*) and Indirect Tensile Strength (IDT) were measured for the aged mixtures for each temperature and duration to determine the effect of different aging times and temperatures on the stiffness and fatigue properties of the aged asphalt mixtures. The binder test results showed that in all cases, there was increased viscosity. The results showed the highest increase in viscosity resulted from increased aging time. The results also indicated that PG 64-22 was more susceptible to elevated STA temperature and extended time than the PG 76-16 binders. The asphalt mixture test results confirmed the expected outcome that increasing the STA and mixing temperature by 25oF alters the stiffness of mixtures. Significant change in the dynamic modulus mostly occurred at four hour increase in STA time regardless of temperature.
ContributorsLolly, Rubben (Author) / Kaloush, Kamil (Thesis advisor) / Bearup, Wylie (Committee member) / Zapata, Claudia (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Laboratory assessment of crack resistance and propagation in asphalt concrete is a difficult task that challenges researchers and engineers. Several fracture mechanics based laboratory tests currently exist; however, these tests and subsequent analysis methods rely on elastic behavior assumptions and do not consider the time-dependent nature of asphalt concrete. The C* Line Integral test has shown promise to capture crack resistance and propagation within asphalt concrete. In addition, the fracture mechanics based C* parameter considers the time-dependent creep behavior of the materials. However, previous research was limited and lacked standardized test procedure and detailed data analysis methods were not fully presented. This dissertation describes the development and refinement of the C* Fracture Test (CFT) based on concepts of the C* line integral test. The CFT is a promising test to assess crack propagation and fracture resistance especially in modified mixtures. A detailed CFT test protocol was developed based on a laboratory study of different specimen sizes and test conditions. CFT numerical simulations agreed with laboratory results and indicated that the maximum horizontal tensile stress (Mode I) occurs at the crack tip but diminishes at longer crack lengths when shear stress (Mode II) becomes present. Using CFT test results and the principles of time-temperature superposition, a crack growth rate master curve was successfully developed to describe crack growth over a range of test temperatures. This master curve can be applied to pavement design and analysis to describe crack propagation as a function of traffic conditions and pavement temperatures. Several plant mixtures were subjected to the CFT and results showed differences in resistance to crack propagation, especially when comparing an asphalt rubber mixture to a conventional one. Results indicated that crack propagation is ideally captured within a given range of dynamic modulus values. Crack growth rates and C* prediction models were successfully developed for all unmodified mixtures in the CFT database. These models can be used to predict creep crack propagation and the C* parameter when laboratory testing is not feasible. Finally, a conceptual approach to incorporate crack growth rate and the C* parameter into pavement design and analysis was presented.
ContributorsStempihar, Jeffrey (Author) / Kaloush, Kamil (Thesis advisor) / Witczak, Matthew (Committee member) / Mamlouk, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
The pay-as-you-go economic model of cloud computing increases the visibility, traceability, and verifiability of software costs. Application developers must understand how their software uses resources when running in the cloud in order to stay within budgeted costs and/or produce expected profits. Cloud computing's unique economic model also leads naturally to an earn-as-you-go profit model for many cloud based applications. These applications can benefit from low level analyses for cost optimization and verification. Testing cloud applications to ensure they meet monetary cost objectives has not been well explored in the current literature. When considering revenues and costs for cloud applications, the resource economic model can be scaled down to the transaction level in order to associate source code with costs incurred while running in the cloud. Both static and dynamic analysis techniques can be developed and applied to understand how and where cloud applications incur costs. Such analyses can help optimize (i.e. minimize) costs and verify that they stay within expected tolerances. An adaptation of Worst Case Execution Time (WCET) analysis is presented here to statically determine worst case monetary costs of cloud applications. This analysis is used to produce an algorithm for determining control flow paths within an application that can exceed a given cost threshold. The corresponding results are used to identify path sections that contribute most to cost excess. A hybrid approach for determining cost excesses is also presented that is comprised mostly of dynamic measurements but that also incorporates calculations that are based on the static analysis approach. This approach uses operational profiles to increase the precision and usefulness of the calculations.
ContributorsBuell, Kevin, Ph.D (Author) / Collofello, James (Thesis advisor) / Davulcu, Hasan (Committee member) / Lindquist, Timothy (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012
Description
Communication networks, both wired and wireless, are expected to have a certain level of fault-tolerance capability.These networks are also expected to ensure a graceful degradation in performance when some of the network components fail. Traditional studies on fault tolerance in communication networks, for the most part, make no assumptions regarding the location of node/link faults, i.e., the faulty nodes and links may be close to each other or far from each other. However, in many real life scenarios, there exists a strong spatial correlation among the faulty nodes and links. Such failures are often encountered in disaster situations, e.g., natural calamities or enemy attacks. In presence of such region-based faults, many of traditional network analysis and fault-tolerant metrics, that are valid under non-spatially correlated faults, are no longer applicable. To this effect, the main thrust of this research is design and analysis of robust networks in presence of such region-based faults. One important finding of this research is that if some prior knowledge is available on the maximum size of the region that might be affected due to a region-based fault, this piece of knowledge can be effectively utilized for resource efficient design of networks. It has been shown in this dissertation that in some scenarios, effective utilization of this knowledge may result in substantial saving is transmission power in wireless networks. In this dissertation, the impact of region-based faults on the connectivity of wireless networks has been studied and a new metric, region-based connectivity, is proposed to measure the fault-tolerance capability of a network. In addition, novel metrics, such as the region-based component decomposition number(RBCDN) and region-based largest component size(RBLCS) have been proposed to capture the network state, when a region-based fault disconnects the network. Finally, this dissertation presents efficient resource allocation techniques that ensure tolerance against region-based faults, in distributed file storage networks and data center networks.
ContributorsBanerjee, Sujogya (Author) / Sen, Arunabha (Thesis advisor) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Hurlbert, Glenn (Committee member) / Arizona State University (Publisher)
Created2013
Description
Data mining is increasing in importance in solving a variety of industry problems. Our initiative involves the estimation of resource requirements by skill set for future projects by mining and analyzing actual resource consumption data from past projects in the semiconductor industry. To achieve this goal we face difficulties like data with relevant consumption information but stored in different format and insufficient data about project attributes to interpret consumption data. Our first goal is to clean the historical data and organize it into meaningful structures for analysis. Once the preprocessing on data is completed, different data mining techniques like clustering is applied to find projects which involve resources of similar skillsets and which involve similar complexities and size. This results in "resource utilization templates" for groups of related projects from a resource consumption perspective. Then project characteristics are identified which generate this diversity in headcounts and skillsets. These characteristics are not currently contained in the data base and are elicited from the managers of historical projects. This represents an opportunity to improve the usefulness of the data collection system for the future. The ultimate goal is to match the product technical features with the resource requirement for projects in the past as a model to forecast resource requirements by skill set for future projects. The forecasting model is developed using linear regression with cross validation of the training data as the past project execution are relatively few in number. Acceptable levels of forecast accuracy are achieved relative to human experts' results and the tool is applied to forecast some future projects' resource demand.
ContributorsBhattacharya, Indrani (Author) / Sen, Arunabha (Thesis advisor) / Kempf, Karl G. (Thesis advisor) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Contention based IEEE 802.11MAC uses the binary exponential backoff algorithm (BEB) for the contention resolution. The protocol suffers poor performance in the heavily loaded networks and MANETs, high collision rate and packet drops, probabilistic delay guarantees, and unfairness. Many backoff strategies were proposed to improve the performance of IEEE 802.11 but all ignore the network topology and demand. Persistence is defined as the fraction of time a node is allowed to transmit, when this allowance should take into account topology and load, it is topology and load aware persistence (TLA). We develop a relation between contention window size and the TLA-persistence. We implement a new backoff strategy where the TLA-persistence is defined as the lexicographic max-min channel allocation. We use a centralized algorithm to calculate each node's TLApersistence and then convert it into a contention window size. The new backoff strategy is evaluated in simulation, comparing with that of the IEEE 802.11 using BEB. In most of the static scenarios like exposed terminal, flow in the middle, star topology, and heavy loaded multi-hop networks and in MANETs, through the simulation study, we show that the new backoff strategy achieves higher overall average throughput as compared to that of the IEEE 802.11 using BEB.
ContributorsBhyravajosyula, Sai Vishnu Kiran (Author) / Syrotiuk, Violet R. (Thesis advisor) / Sen, Arunabha (Committee member) / Richa, Andrea (Committee member) / Arizona State University (Publisher)
Created2013
Description
As networks are playing an increasingly prominent role in different aspects of our lives, there is a growing awareness that improving their performance is of significant importance. In order to enhance performance of networks, it is essential that scarce networking resources be allocated smartly to match the continuously changing network environment. This dissertation focuses on two different kinds of networks - communication and social, and studies resource allocation problems in these networks. The study on communication networks is further divided into different networking technologies - wired and wireless, optical and mobile, airborne and terrestrial. Since nodes in an airborne network (AN) are heterogeneous and mobile, the design of a reliable and robust AN is highly complex. The dissertation studies connectivity and fault-tolerance issues in ANs and proposes algorithms to compute the critical transmission range in fault free, faulty and delay tolerant scenarios. Just as in the case of ANs, power optimization and fault tolerance are important issues in wireless sensor networks (WSN). In a WSN, a tree structure is often used to deliver sensor data to a sink node. In a tree, failure of a node may disconnect the tree. The dissertation investigates the problem of enhancing the fault tolerance capability of data gathering trees in WSN. The advent of OFDM technology provides an opportunity for efficient resource utilization in optical networks and also introduces a set of novel problems, such as routing and spectrum allocation (RSA) problem. This dissertation proves that RSA problem is NP-complete even when the network topology is a chain, and proposes approximation algorithms. In the domain of social networks, the focus of this dissertation is study of influence propagation in presence of active adversaries. In a social network multiple vendors may attempt to influence the nodes in a competitive fashion. This dissertation investigates the scenario where the first vendor has already chosen a set of nodes and the second vendor, with the knowledge of the choice of the first, attempts to identify a smallest set of nodes so that after the influence propagation, the second vendor's market share is larger than the first.
ContributorsShirazipourazad, Shahrzad (Author) / Sen, Arunabha (Committee member) / Xue, Guoliang (Committee member) / Richa, Andrea (Committee member) / Saripalli, Srikanth (Committee member) / Arizona State University (Publisher)
Created2014