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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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2011 2019


Complex systems are pervasive in science and engineering. Some examples include complex engineered networks such as the internet, the power grid, and transportation networks. The complexity of such systems arises not just from their size, but also from their structure, operation (including control and management), evolution over time, and that people are involved in their design and operation. Our understanding of such systems is limited because their behaviour cannot be characterized using traditional techniques of modelling and analysis. As a step in model development, statistically designed screening experiments may be used to identify the main effects and interactions most significant …

Contributors
Aldaco-Gastelum, Abraham Netzahualcoyotl, Syrotiuk, Violet R., Colbourn, Charles J., et al.
Created Date
2015

For systems having computers as a significant component, it becomes a critical task to identify the potential threats that the users of the system can present, while being both inside and outside the system. One of the most important factors that differentiate an insider from an outsider is the fact that the insider being a part of the system, owns privileges that enable him/her access to the resources and processes of the system through valid capabilities. An insider with malicious intent can potentially be more damaging compared to outsiders. The above differences help to understand the notion and scope of …

Contributors
Nolastname, Sharad, Bazzi, Rida, Sen, Arunabha, et al.
Created Date
2019

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 …

Contributors
Bhyravajosyula, Sai Vishnu Kiran, Syrotiuk, Violet R., Sen, Arunabha, et al.
Created Date
2013

Text classification, in the artificial intelligence domain, is an activity in which text documents are automatically classified into predefined categories using machine learning techniques. An example of this is classifying uncategorized news articles into different predefined categories such as "Business", "Politics", "Education", "Technology" , etc. In this thesis, supervised machine learning approach is followed, in which a module is first trained with pre-classified training data and then class of test data is predicted. Good feature extraction is an important step in the machine learning approach and hence the main component of this text classifier is semantic triplet based features in …

Contributors
Karad, Ravi Chandravadan, Davulcu, Hasan, Corman, Steven, et al.
Created Date
2013

The overall contribution of the Minerva Initiative at ASU is to map social organizations in a multidimensional space that provides a measure of their radical or counter radical influence over the demographics of a nation. This tool serves as a simple content management system to store and track project resources like documents, images, videos and web links. It provides centralized and secure access to email conversations among project team members. Conversations are categorized into one of the seven pre-defined categories. Each category is associated with a certain set of keywords and we follow a frequency based approach for matching email …

Contributors
Nair, Apurva, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2012

Muslim radicalism is recognized as one of the greatest security threats for the United States and the rest of the world. Use of force to eliminate specific radical entities is ineffective in containing radicalism as a whole. There is a need to understand the origin, ideologies and behavior of Radical and Counter-Radical organizations and how they shape up over a period of time. Recognizing and supporting counter-radical organizations is one of the most important steps towards impeding radical organizations. A lot of research has already been done to categorize and recognize organizations, to understand their behavior, their interactions with other …

Contributors
Nair, Shreejay, Davulcu, Hasan, Dasgpta, Partha, et al.
Created Date
2012

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

Predicting when an individual will adopt a new behavior is an important problem in application domains such as marketing and public health. This thesis examines the performance of a wide variety of social network based measurements proposed in the literature - which have not been previously compared directly. This research studies the probability of an individual becoming influenced based on measurements derived from neighborhood (i.e. number of influencers, personal network exposure), structural diversity, locality, temporal measures, cascade measures, and metadata. It also examines the ability to predict influence based on choice of the classifier and how the ratio of positive …

Contributors
Nanda Kumar, Nikhil, Shakarian, Paulo, Sen, Arunabha, et al.
Created Date
2016

Distributed systems are prone to attacks, called Sybil attacks, wherein an adversary may generate an unbounded number of bogus identities to gain control over the system. In this thesis, an algorithm, DownhillFlow, for mitigating such attacks is presented and tested experimentally. The trust rankings produced by the algorithm are significantly better than those of the distributed SybilGuard protocol and only slightly worse than those of the best-known Sybil defense algorithm, ACL. The results obtained for ACL are consistent with those obtained in previous studies. The running times of the algorithms are also tested and two results are obtained: first, DownhillFlow’s …

Contributors
Bradley, Michael, Bazzi, Rida, Richa, Andrea, et al.
Created Date
2018

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

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 trading, volume is a measure of how much stock has been exchanged in a given period of time. Since every stock is distinctive and has an alternate measure of shares, volume can be contrasted with historical volume inside a stock to spot changes. It is likewise used to affirm value patterns, breakouts, and spot potential reversals. In my thesis, I hypothesize that the concept of trading volume can be extrapolated to social media (Twitter). The ubiquity of social media, especially Twitter, in financial market has been overly resonant in the past couple of years. With the growth of its …

Contributors
Awasthi, Piyush, Davulcu, Hasan, Tong, Hanghang, et al.
Created Date
2015

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 …

Contributors
Buell, Kevin, Collofello, James, Davulcu, Hasan, et al.
Created Date
2012

Networks naturally appear in many high-impact applications. The simplest model of networks is single-layered networks, where the nodes are from the same domain and the links are of the same type. However, as the world is highly coupled, nodes from different application domains tend to be interdependent on each other, forming a more complex network model called multi-layered networks. Among the various aspects of network studies, network connectivity plays an important role in a myriad of applications. The diversified application areas have spurred numerous connectivity measures, each designed for some specific tasks. Although effective in their own fields, none of …

Contributors
Chen, Chen, Tong, Hanghang, Davulcu, Hasan, et al.
Created Date
2019

There has been extensive study of the target tracking problems in the recent years. Very little work has been done in the problem of continuous monitoring of all the mobile targets using the fewest number of mobile trackers, when the trajectories of all the targets are known in advance. Almost all the existing research discretized time (and/or space), or assume infinite tracker velocity. In this thesis, I consider the problem of covering (tracking) target nodes using a network of Unmanned Airborne Vehicles (UAV's) for the entire period of observation by adding the constraint of fixed velocity on the trackers and …

Contributors
Vachhani, Harsh, Sen, Arunabha, Saripalli, Srikanth, et al.
Created Date
2014

US Senate is the venue of political debates where the federal bills are formed and voted. Senators show their support/opposition along the bills with their votes. This information makes it possible to extract the polarity of the senators. Similarly, blogosphere plays an increasingly important role as a forum for public debate. Authors display sentiment toward issues, organizations or people using a natural language. In this research, given a mixed set of senators/blogs debating on a set of political issues from opposing camps, I use signed bipartite graphs for modeling debates, and I propose an algorithm for partitioning both the opinion …

Contributors
Gokalp, Sedat, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2015

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

In the realm of network science, many topics can be abstracted as graph problems, such as routing, connectivity enhancement, resource/frequency allocation and so on. Though most of them are NP-hard to solve, heuristics as well as approximation algorithms are proposed to achieve reasonably good results. Accordingly, this dissertation studies graph related problems encountered in real applications. Two problems studied in this dissertation are derived from wireless network, two more problems studied are under scenarios of FIWI and optical network, one more problem is in Radio- Frequency Identification (RFID) domain and the last problem is inspired by satellite deployment. The objective …

Contributors
Zhou, Chenyang, Richa, Andrea, Sen, Arunabha, et al.
Created Date
2019

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 …

Contributors
Banerjee, Sujogya, Sen, Arunabha, Xue, Guoliang, et al.
Created Date
2013

Resource allocation is one of the most challenging issues policy decision makers must address. The objective of this thesis is to explore the resource allocation from an economical perspective, i.e., how to purchase resources in order to satisfy customers' requests. In this thesis, we attend to answer the question: when and how to buy resources to fulfill customers' demands with minimum costs? The first topic studied in this thesis is resource allocation in cloud networks. Cloud computing heralded an era where resources (such as computation and storage) can be scaled up and down elastically and on demand. This flexibility is …

Contributors
Hu, Xinhui, Richa, Andrea, Schmid, Stefan, et al.
Created Date
2015

The use of energy-harvesting in a wireless sensor network (WSN) is essential for situations where it is either difficult or not cost effective to access the network's nodes to replace the batteries. In this paper, the problems involved in controlling an active sensor network that is powered both by batteries and solar energy are investigated. The objective is to develop control strategies to maximize the quality of coverage (QoC), which is defined as the minimum number of targets that must be covered and reported over a 24 hour period. Assuming a time varying solar profile, the problem is to optimally …

Contributors
Gaudette, Benjamin David, Vrudhula, Sarma, Shrivastava, Aviral, et al.
Created Date
2012

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

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

The field of Data Mining is widely recognized and accepted for its applications in many business problems to guide decision-making processes based on data. However, in recent times, the scope of these problems has swollen and the methods are under scrutiny for applicability and relevance to real-world circumstances. At the crossroads of innovation and standards, it is important to examine and understand whether the current theoretical methods for industrial applications (which include KDD, SEMMA and CRISP-DM) encompass all possible scenarios that could arise in practical situations. Do the methods require changes or enhancements? As part of the thesis I study …

Contributors
Anand, Aneeth, Liu, Huan, Kempf, Karl G, et al.
Created Date
2012

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 statement appearing in social media provides a very significant challenge for determining the provenance of the statement. Provenance describes the origin, custody, and ownership of something. Most statements appearing in social media are not published with corresponding provenance data. However, the same characteristics that make the social media environment challenging, including the massive amounts of data available, large numbers of users, and a highly dynamic environment, provide unique and untapped opportunities for solving the provenance problem for social media. Current approaches for tracking provenance data do not scale for online social media and consequently there is a gap in …

Contributors
Barbier, Geoffrey, Liu, Huan, Bell, Herbert, et al.
Created Date
2011

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 …

Contributors
Bhattacharya, Indrani, Sen, Arunabha, Kempf, Karl G, et al.
Created Date
2013

The critical infrastructures of the nation are a large and complex network of human, physical and cyber-physical systems. In recent times, it has become increasingly apparent that individual critical infrastructures, such as the power and communication networks, do not operate in isolation, but instead are part of a complex interdependent ecosystem where a failure involving a small set of network entities can trigger a cascading event resulting in the failure of a much larger set of entities through the failure propagation process. Recognizing the need for a deeper understanding of the interdependent relationships between such critical infrastructures, several models have …

Contributors
Das, Arun, Sen, Arunabha, Xue, Guoliang, et al.
Created Date
2016

There are many applications where the truth is unknown. The truth values are guessed by different sources. The values of different properties can be obtained from various sources. These will lead to the disagreement in sources. An important task is to obtain the truth from these sometimes contradictory sources. In the extension of computing the truth, the reliability of sources needs to be computed. There are models which compute the precision values. In those earlier models Banerjee et al. (2005) Dong and Naumann (2009) Kasneci et al. (2011) Li et al. (2012) Marian and Wu (2011) Zhao and Han (2012) …

Contributors
Jain, Karan, Xue, Guoliang, Sen, Arunabha, et al.
Created Date
2019

The popularity of social media has generated abundant large-scale social networks, which advances research on network analytics. Good representations of nodes in a network can facilitate many network mining tasks. The goal of network representation learning (network embedding) is to learn low-dimensional vector representations of social network nodes that capture certain properties of the networks. With the learned node representations, machine learning and data mining algorithms can be applied for network mining tasks such as link prediction and node classification. Because of its ability to learn good node representations, network representation learning is attracting increasing attention and various network embedding …

Contributors
Wang, Suhang, Liu, Huan, Aggarwal, Charu, et al.
Created Date
2018

We live in a networked world with a multitude of networks, such as communication networks, electric power grid, transportation networks and water distribution networks, all around us. In addition to such physical (infrastructure) networks, recent years have seen tremendous proliferation of social networks, such as Facebook, Twitter, LinkedIn, Instagram, Google+ and others. These powerful social networks are not only used for harnessing revenue from the infrastructure networks, but are also increasingly being used as “non-conventional sensors” for monitoring the infrastructure networks. Accordingly, nowadays, analyses of social and infrastructure networks go hand-in-hand. This dissertation studies resource allocation problems encountered in this …

Contributors
Mazumder, Anisha, Sen, Arunabha, Richa, Andrea, et al.
Created Date
2016

Error correcting systems have put increasing demands on system designers, both due to increasing error correcting requirements and higher throughput targets. These requirements have led to greater silicon area, power consumption and have forced system designers to make trade-offs in Error Correcting Code (ECC) functionality. Solutions to increase the efficiency of ECC systems are very important to system designers and have become a heavily researched area. Many such systems incorporate the Bose-Chaudhuri-Hocquenghem (BCH) method of error correcting in a multi-channel configuration. BCH is a commonly used code because of its configurability, low storage overhead, and low decoding requirements when compared …

Contributors
Dill, Russell, Shrivastava, Aviral, Oh, Hyunok, et al.
Created Date
2015

This research start utilizing an efficient sparse inverse covariance matrix (precision matrix) estimation technique to identify a set of highly correlated discriminative perspectives between radical and counter-radical groups. A ranking system has been developed that utilizes ranked perspectives to map Islamic organizations on a set of socio-cultural, political and behavioral scales based on their web site corpus. Simultaneously, a gold standard ranking of these organizations was created through domain experts and compute expert-to-expert agreements and present experimental results comparing the performance of the QUIC based scaling system to another baseline method for organizations. The QUIC based algorithm not only outperforms …

Contributors
Kim, Nyunsu, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2018

The presence of a rich set of embedded sensors on mobile devices has been fuelling various sensing applications regarding the activities of individuals and their surrounding environment, and these ubiquitous sensing-capable mobile devices are pushing the new paradigm of Mobile Crowd Sensing (MCS) from concept to reality. MCS aims to outsource sensing data collection to mobile users and it could revolutionize the traditional ways of sensing data collection and processing. In the meantime, cloud computing provides cloud-backed infrastructures for mobile devices to provision their capabilities with network access. With enormous computational and storage resources along with sufficient bandwidth, it functions …

Contributors
Wang, Zhijie, Wang, Zhijie, Xue, Guoliang, et al.
Created Date
2016

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 …

Contributors
Shirazipourazad, Shahrzad, Sen, Arunabha, Sen, Arunabha, et al.
Created Date
2014

Interference constitutes a major challenge for communication networks operating over a shared medium where availability is imperative. This dissertation studies the problem of designing and analyzing efficient medium access protocols which are robust against strong adversarial jamming. More specifically, four medium access (MAC) protocols (i.e., JADE, ANTIJAM, COMAC, and SINRMAC) which aim to achieve high throughput despite jamming activities under a variety of network and adversary models are presented. We also propose a self-stabilizing leader election protocol, SELECT, that can effectively elect a leader in the network with the existence of a strong adversary. Our protocols can not only deal …

Contributors
Zhang, Jin, Richa, Andrea W, Scheideler, Christian, et al.
Created Date
2012

Analysis of political texts, which contains a huge amount of personal political opinions, sentiments, and emotions towards powerful individuals, leaders, organizations, and a large number of people, is an interesting task, which can lead to discover interesting interactions between the political parties and people. Recently, political blogosphere plays an increasingly important role in politics, as a forum for debating political issues. Most of the political weblogs are biased towards their political parties, and they generally express their sentiments towards their issues (i.e. leaders, topics etc.,) and also towards issues of the opposing parties. In this thesis, I have modeled the …

Contributors
Thirumalai, Dananjayan, Davulcu, Hasan, Sarjoughian, Hessam, et al.
Created Date
2012

Emerging from years of research and development, the Internet-of-Things (IoT) has finally paved its way into our daily lives. From smart home to Industry 4.0, IoT has been fundamentally transforming numerous domains with its unique superpower of interconnecting world-wide devices. However, the capability of IoT is largely constrained by the limited resources it can employ in various application scenarios, including computing power, network resource, dedicated hardware, etc. The situation is further exacerbated by the stringent quality-of-service (QoS) requirements of many IoT applications, such as delay, bandwidth, security, reliability, and more. This mismatch in resources and demands has greatly hindered the …

Contributors
Yu, Ruozhou, Xue, Guoliang, Huang, Dijiang, et al.
Created Date
2019

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

Mobile ad hoc networks (MANETs) have attracted attention for mission critical applications. This dissertation investigates techniques of statistical monitoring and control for overhead reduction in a proactive MANET routing protocol. Proactive protocols transmit overhead periodically. Instead, we propose that the local conditions of a node should determine this transmission decision. While the goal is to minimize overhead, a balance in the amount of overhead transmitted and the performance achieved is required. Statistical monitoring consists of techniques to determine if a characteristic has shifted away from an in-control state. A basic tool for monitoring is a control chart, a time-oriented representation …

Contributors
Shaukat, Kahkashan, Syrotiuk, Violet R, Colbourn, Charles J, et al.
Created Date
2012

Time series forecasting is the prediction of future data after analyzing the past data for temporal trends. This work investigates two fields of time series forecasting in the form of Stock Data Prediction and the Opioid Incident Prediction. In this thesis, the Stock Data Prediction Problem investigates methods which could predict the trends in the NYSE and NASDAQ stock markets for ten different companies, nine of which are part of the Dow Jones Industrial Average (DJIA). A novel deep learning model which uses a Generative Adversarial Network (GAN) is used to predict future data and the results are compared with …

Contributors
Thomas, Kevin, Sen, Arunabha, Davulcu, Hasan, et al.
Created Date
2019

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

The power and communication networks are highly interdependent and form a part of the critical infrastructure of a country. Similarly, dependencies exist within the networks itself. Owing to cascading failures, interdependent and intradependent networks are extremely susceptible to widespread vulnerabilities. In recent times the research community has shown significant interest in modeling to capture these dependencies. However, many of them are simplistic in nature which limits their applicability to real world systems. This dissertation presents a Boolean logic based model termed as Implicative Interdependency Model (IIM) to capture the complex dependencies and cascading failures resulting from an initial failure of …

Contributors
Banerjee, Joydeep, Sen, Arunabha, Dasgupta, Partha, et al.
Created Date
2017

Internet and social media devices created a new public space for debate on political and social topics (Papacharissi 2002; Himelboim 2010). Hotly debated issues span all spheres of human activity; from liberal vs. conservative politics, to radical vs. counter-radical religious debate, to climate change debate in scientific community, to globalization debate in economics, and to nuclear disarmament debate in security. Many prominent ’camps’ have emerged within Internet debate rhetoric and practice (Dahlberg, n.d.). In this research I utilized feature extraction and model fitting techniques to process the rhetoric found in the web sites of 23 Indonesian Islamic religious organizations, later …

Contributors
Tikves, Sukru, Davulcu, Hasan, Sen, Arunabha, et al.
Created Date
2016