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- Genre: Masters Thesis
Description
The increasing popularity of Twitter renders improved trustworthiness and relevance assessment of tweets much more important for search. However, given the limitations on the size of tweets, it is hard to extract measures for ranking from the tweet's content alone. I propose a method of ranking tweets by generating a reputation score for each tweet that is based not just on content, but also additional information from the Twitter ecosystem that consists of users, tweets, and the web pages that tweets link to. This information is obtained by modeling the Twitter ecosystem as a three-layer graph. The reputation score is used to power two novel methods of ranking tweets by propagating the reputation over an agreement graph based on tweets' content similarity. Additionally, I show how the agreement graph helps counter tweet spam. An evaluation of my method on 16~million tweets from the TREC 2011 Microblog Dataset shows that it doubles the precision over baseline Twitter Search and achieves higher precision than current state of the art method. I present a detailed internal empirical evaluation of RAProp in comparison to several alternative approaches proposed by me, as well as external evaluation in comparison to the current state of the art method.
ContributorsRavikumar, Srijith (Author) / Kambhampati, Subbarao (Thesis advisor) / Davulcu, Hasan (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2013
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
Continuous Delivery, as one of the youngest and most popular member of agile model family, has become a popular concept and method in software development industry recently. Instead of the traditional software development method, which requirements and solutions must be fixed before starting software developing, it promotes adaptive planning, evolutionary development and delivery, and encourages rapid and flexible response to change. However, several problems prevent Continuous Delivery to be introduced into education world. Taking into the consideration of the barriers, we propose a new Cloud based Continuous Delivery Software Developing System. This system is designed to fully utilize the whole life circle of software developing according to Continuous Delivery concepts in a virtualized environment in Vlab platform.
ContributorsDeng, Yuli (Author) / Huang, Dijiang (Thesis advisor) / Davulcu, Hasan (Committee member) / Chen, Yinong (Committee member) / Arizona State University (Publisher)
Created2013
Description
Topological insulators with conducting surface states yet insulating bulk states have generated a lot of interest amongst the physics community due to their varied characteristics and possible applications. Doped topological insulators have presented newer physical states of matter where topological order co&ndashexists; with other physical properties (like magnetic order). The electronic states of these materials are very intriguing and pose problems and the possible solutions to understanding their unique behaviors. In this work, we use Electron Energy Loss Spectroscopy (EELS) – an analytical TEM tool to study both core&ndashlevel; and valence&ndashlevel; excitations in Bi2Se3 and Cu(doped)Bi2Se3 topological insulators. We use this technique to retrieve information on the valence, bonding nature, co-ordination and lattice site occupancy of the undoped and the doped systems. Using the reference materials Cu(I)Se and Cu(II)Se we try to compare and understand the nature of doping that copper assumes in the lattice. And lastly we utilize the state of the art monochromated Nion UltraSTEM 100 to study electronic/vibrational excitations at a record energy resolution from sub-nm regions in the sample.
ContributorsSubramanian, Ganesh (Author) / Spence, John (Thesis advisor) / Jiang, Nan (Committee member) / Chen, Tingyong (Committee member) / Chan, Candace (Committee member) / Arizona State University (Publisher)
Created2013
Description
As the complexity of robotic systems and applications grows rapidly, development of high-performance, easy to use, and fully integrated development environments for those systems is inevitable. Model-Based Design (MBD) of dynamic systems using engineering software such as Simulink® from MathWorks®, SciCos from Metalau team and SystemModeler® from Wolfram® is quite popular nowadays. They provide tools for modeling, simulation, verification and in some cases automatic code generation for desktop applications, embedded systems and robots. For real-world implementation of models on the actual hardware, those models should be converted into compilable machine code either manually or automatically. Due to the complexity of robotic systems, manual code translation from model to code is not a feasible optimal solution so we need to move towards automated code generation for such systems. MathWorks® offers code generation facilities called Coder® products for this purpose. However in order to fully exploit the power of model-based design and code generation tools for robotic applications, we need to enhance those software systems by adding and modifying toolboxes, files and other artifacts as well as developing guidelines and procedures. In this thesis, an effort has been made to propose a guideline as well as a Simulink® library, StateFlow® interface API and a C/C++ interface API to complete this toolchain for NAO humanoid robots. Thus the model of the hierarchical control architecture can be easily and properly converted to code and built for implementation.
ContributorsRaji Kermani, Ramtin (Author) / Fainekos, Georgios (Thesis advisor) / Lee, Yann-Hang (Committee member) / Sarjoughian, Hessam S. (Committee member) / Arizona State University (Publisher)
Created2013
Description
The alkali activation of aluminosilicate materials as binder systems derived from industrial byproducts have been extensively studied due to the advantages they offer in terms enhanced material properties, while increasing sustainability by the reuse of industrial waste and byproducts and reducing the adverse impacts of OPC production. Fly ash and ground granulated blast furnace slag are commonly used for their content of soluble silica and aluminate species that can undergo dissolution, polymerization with the alkali, condensation on particle surfaces and solidification. The following topics are the focus of this thesis: (i) the use of microwave assisted thermal processing, in addition to heat-curing as a means of alkali activation and (ii) the relative effects of alkali cations (K or Na) in the activator (powder activators) on the mechanical properties and chemical structure of these systems. Unsuitable curing conditions instigate carbonation, which in turn lowers the pH of the system causing significant reductions in the rate of fly ash activation and mechanical strength development. This study explores the effects of sealing the samples during the curing process, which effectively traps the free water in the system, and allows for increased aluminosilicate activation. The use of microwave-curing in lieu of thermal-curing is also studied in order to reduce energy consumption and for its ability to provide fast volumetric heating. Potassium-based powder activators dry blended into the slag binder system is shown to be effective in obtaining very high compressive strengths under moist curing conditions (greater than 70 MPa), whereas sodium-based powder activation is much weaker (around 25 MPa). Compressive strength decreases when fly ash is introduced into the system. Isothermal calorimetry is used to evaluate the early hydration process, and to understand the reaction kinetics of the alkali powder activated systems. A qualitative evidence of the alkali-hydroxide concentration of the paste pore solution through the use of electrical conductivity measurements is also presented, with the results indicating the ion concentration of alkali is more prevalent in the pore solution of potassium-based systems. The use of advanced spectroscopic and thermal analysis techniques to distinguish the influence of studied parameters is also discussed.
ContributorsChowdhury, Ussala (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramanium D. (Committee member) / Mobasher, Barzin (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
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
Rapid processing and reduced end-of-range diffusion effects demonstrate that susceptor-assisted microwave annealing is an efficient processing alternative for electrically activating dopants and removing ion-implantation damage in ion-implanted semiconductors. Sheet resistance and Hall measurements provide evidence of electrical activation. Raman spectroscopy and ion channeling analysis monitor the extent of ion implantation damage and recrystallization. The presence of damage and defects in ion implanted silicon, and the reduction of the defects as a result of annealing, is observed by Rutherford backscattering spectrometry, moreover, the boron implanted silicon is further investigated by cross-section transmission electron microscopy. When annealing B+ implanted silicon, the dissolution of small extended defects and growth of large extended defects result in reduced crystalline quality that hinders the electrical activation process. Compared to B+ implanted silicon, phosphorus implanted samples experience more effective activation and achieve better crystalline quality. Comparison of end-of-range dopants diffusion resulting from microwave annealing and rapid thermal annealing (RTA) is done using secondary ion mass spectroscopy. Results from microwave annealed P+ implanted samples show that almost no diffusion occurs during time periods required for complete dopant activation and silicon recrystallization. The relative contributions to heating of the sample, by a SiC susceptor, and by Si self-heating in the microwave anneal, were also investigated. At first 20s, the main contributor to the sample's temperature rise is Si self-heating by microwave absorption.
ContributorsZhao, Zhao (Author) / Alford, Terry Lynn (Thesis advisor) / Theodore, David (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microwave (MW), thermal, and ultraviolet (UV) annealing were used to explore the response of Ag structures on a Ge-Se chalcogenide glass (ChG) thin film as flexible radiation sensors, and Te-Ti chalcogenide thin films as a material for diffusion barriers in microelectronics devices and processing of metallized Cu. Flexible resistive radiation sensors consisting of Ag electrodes on a Ge20Se80 ChG thin film and polyethylene naphthalate substrate were exposed to UV radiation. The sensors were mounted on PVC tubes of varying radii to induce bending strains and annealed under ambient conditions up to 150 oC. Initial sensor resistance was measured to be ~1012 Ω; after exposure to UV radiation, the resistance was ~104 Ω. Bending strain and low temperature annealing had no significant effect on the resistance of the sensors. Samples of Cu on Te-Ti thin films were annealed in vacuum for up to 30 minutes and were stable up to 500 oC as revealed using Rutherford backscattering spectrometry (RBS) and four-point-probe analysis. X-ray diffractometry (XRD) indicates Cu grain growth up to 500 oC and phase instability of the Te-Ti barrier at 600 oC. MW processing was performed in a 2.45-GHz microwave cavity on Cu/Te-Ti films for up to 30 seconds to induce oxide growth. Using a calibrated pyrometer above the sample, the temperature of the MW process was measured to be below a maximum of 186 oC. Four-point-probe analysis shows an increase in resistance with an increase in MW time. XRD indicates growth of CuO on the sample surface. RBS suggests oxidation throughout the Te-Ti film. Additional samples were exposed to 907 J/cm2 UV radiation in order to ensure other possible electromagnetically induced mechanisms were not active. There were no changes observed using XRD, RBS or four point probing.
ContributorsRoos, Benjamin, 1990- (Author) / Alford, Terry L. (Thesis advisor) / Theodore, David (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2013