ASU Electronic Theses and Dissertations

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Date Range
2010 2017

Social media has become popular in the past decade. Facebook for example has 1.59 billion active users monthly. With such massive social networks generating lot of data, everyone is constantly looking for ways of leveraging the knowledge from social networks to make their systems more personalized to their end users. And with rapid increase in the usage of mobile phones and wearables, social media data is being tied to spatial networks. This research document proposes an efficient technique that answers socially k-Nearest Neighbors with Spatial Range Filter. The proposed approach performs a joint search on both the social and spatial ...

Contributors
Pasumarthy, Nitin, Sarwat, Mohamed, Papotti, Paolo, et al.
Created Date
2016

In supervised learning, machine learning techniques can be applied to learn a model on a small set of labeled documents which can be used to classify a larger set of unknown documents. Machine learning techniques can be used to analyze a political scenario in a given society. A lot of research has been going on in this field to understand the interactions of various people in the society in response to actions taken by their organizations. This paper talks about understanding the Russian influence on people in Latvia. This is done by building an eeffective model learnt on initial set ...

Contributors
Bollapragada, Lakshmi Gayatri Niharika, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2016

A community in a social network can be viewed as a structure formed by individuals who share similar interests. Not all communities are explicit; some may be hidden in a large network. Therefore, discovering these hidden communities becomes an interesting problem. Researchers from a number of fields have developed algorithms to tackle this problem. Besides the common feature above, communities within a social network have two unique characteristics: communities are mostly small and overlapping. Unfortunately, many traditional algorithms have difficulty recognizing these small communities (often called the resolution limit problem) as well as overlapping communities. In this work, two enhanced ...

Contributors
Wang, Ran, Liu, Huan, Sen, Arunabha, et al.
Created Date
2015

Cloud computing is regarded as one of the most revolutionary technologies in the past decades. It provides scalable, flexible and secure resource provisioning services, which is also the reason why users prefer to migrate their locally processing workloads onto remote clouds. Besides commercial cloud system (i.e., Amazon EC2), ProtoGENI and PlanetLab have further improved the current Internet-based resource provisioning system by allowing end users to construct a virtual networking environment. By archiving the similar goal but with more flexible and efficient performance, I present the design and implementation of MobiCloud that is a geo-distributed mobile cloud computing platform, and G-PLaNE ...

Contributors
Xing, Tianyi, Huang, Dijiang, Xue, Guoliang, et al.
Created Date
2014

While network problems have been addressed using a central administrative domain with a single objective, the devices in most networks are actually not owned by a single entity but by many individual entities. These entities make their decisions independently and selfishly, and maybe cooperate with a small group of other entities only when this form of coalition yields a better return. The interaction among multiple independent decision-makers necessitates the use of game theory, including economic notions related to markets and incentives. In this dissertation, we are interested in modeling, analyzing, addressing network problems caused by the selfish behavior of network ...

Contributors
Yang, Dejun, Xue, Guoliang, Richa, Andrea, et al.
Created Date
2013

With the advent of Internet, the data being added online is increasing at enormous rate. Though search engines are using IR techniques to facilitate the search requests from users, the results are not effective towards the search query of the user. The search engine user has to go through certain webpages before getting at the webpage he/she wanted. This problem of Information Overload can be solved using Automatic Text Summarization. Summarization is a process of obtaining at abridged version of documents so that user can have a quick view to understand what exactly the document is about. Email threads from ...

Contributors
Nadella, Sravan, Davulcu, Hasan, Li, Baoxin, et al.
Created Date
2015

In this thesis multiple approaches are explored to enhance sentiment analysis of tweets. A standard sentiment analysis model with customized features is first trained and tested to establish a baseline. This is compared to an existing topic based mixture model and a new proposed topic based vector model both of which use Latent Dirichlet Allocation (LDA) for topic modeling. The proposed topic based vector model has higher accuracies in terms of averaged F scores than the other two models. Dissertation/Thesis

Contributors
Baskaran, Swetha, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2016

Imagine that we have a piece of matter that can change its physical properties like its shape, density, conductivity, or color in a programmable fashion based on either user input or autonomous sensing. This is the vision behind what is commonly known as programmable matter. Envisioning systems of nano-sensors devices, programmable matter consists of systems of simple computational elements, called particles, that can establish and release bonds, compute, and can actively move in a self-organized way. In this dissertation the feasibility of solving fundamental problems relevant for programmable matter is investigated. As a model for such self-organizing particle systems (SOPS), ...

Contributors
Derakhshandeh, Zahra, Richa, Andrea, Sen, Arunabha, et al.
Created Date
2017

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 ...

Contributors
Poornachandran, Sathishkumar, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2013

Network-on-Chip (NoC) architectures have emerged as the solution to the on-chip communication challenges of multi-core embedded processor architectures. Design space exploration and performance evaluation of a NoC design requires fast simulation infrastructure. Simulation of register transfer level model of NoC is too slow for any meaningful design space exploration. One of the solutions to reduce the speed of simulation is to increase the level of abstraction. SystemC TLM2.0 provides the capability to model hardware design at higher levels of abstraction with trade-off of simulation speed and accuracy. In this thesis, SystemC TLM2.0 models of NoC routers are developed at three ...

Contributors
Arlagadda Narasimharaju, Jyothi Swaroop, Chatha, Karamvir S, Sen, Arunabha, et al.
Created Date
2012

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.