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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.


Resource Type
  • Doctoral Dissertation
  • 1 Text
Subject
Date Range
2011 2019


Online social networks are the hubs of social activity in cyberspace, and using them to exchange knowledge, experiences, and opinions is common. In this work, an advanced topic modeling framework is designed to analyse complex longitudinal health information from social media with minimal human annotation, and Adverse Drug Events and Reaction (ADR) information is extracted and automatically processed by using a biased topic modeling method. This framework improves and extends existing topic modelling algorithms that incorporate background knowledge. Using this approach, background knowledge such as ADR terms and other biomedical knowledge can be incorporated during the text mining process, with …

Contributors
Yang, Jian, Gonzalez, Graciela, Davulcu, Hasan, et al.
Created Date
2017

The adoption of the Service Oriented Architecture (SOA) as the foundation for developing a new generation of software systems - known as Service Based Software Systems (SBS), poses new challenges in system design. While simulation as a methodology serves a principal role in design, there is a growing recognition that simulation of SBS requires modeling capabilities beyond those that are developed for the traditional distributed software systems. In particular, while different component-based modeling approaches may lend themselves to simulating the logical process flows in Service Oriented Computing (SOC) systems, they are inadequate in terms of supporting SOA-compliant modeling. Furthermore, composite …

Contributors
Muqsith, Mohammed Abdul, Sarjoughian, Hessam S, Yau, Sik-Sang, et al.
Created Date
2011

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

Accurate quantitative information of tumor/lesion volume plays a critical role in diagnosis and treatment assessment. The current clinical practice emphasizes on efficiency, but sacrifices accuracy (bias and precision). In the other hand, many computational algorithms focus on improving the accuracy, but are often time consuming and cumbersome to use. Not to mention that most of them lack validation studies on real clinical data. All of these hinder the translation of these advanced methods from benchside to bedside. In this dissertation, I present a user interactive image application to rapidly extract accurate quantitative information of abnormalities (tumor/lesion) from multi-spectral medical images, …

Contributors
Xue, Wenzhe, Kaufman, David, Mitchell, J. Ross, et al.
Created Date
2016

A Pairwise Comparison Matrix (PCM) is used to compute for relative priorities of criteria or alternatives and are integral components of widely applied decision making tools: the Analytic Hierarchy Process (AHP) and its generalized form, the Analytic Network Process (ANP). However, a PCM suffers from several issues limiting its application to large-scale decision problems, specifically: (1) to the curse of dimensionality, that is, a large number of pairwise comparisons need to be elicited from a decision maker (DM), (2) inconsistent and (3) imprecise preferences maybe obtained due to the limited cognitive power of DMs. This dissertation proposes a PCM Framework …

Contributors
Jalao, Eugene Rex Lazaro, Shunk, Dan L, Wu, Teresa, et al.
Created Date
2013

This dissertation introduces FARCOM (Fortran Adaptive Refiner for Cartesian Orthogonal Meshes), a new general library for adaptive mesh refinement (AMR) based on an unstructured hexahedral mesh framework. As a result of the underlying unstructured formulation, the refinement and coarsening operators of the library operate on a single-cell basis and perform in-situ replacement of old mesh elements. This approach allows for h-refinement without the memory and computational expense of calculating masked coarse grid cells, as is done in traditional patch-based AMR approaches, and enables unstructured flow solvers to have access to the automated domain generation capabilities usually only found in tree …

Contributors
Ballesteros, Carlos Alberto, Herrmann, Marcus, Adrian, Ronald, et al.
Created Date
2019

In motor learning, real-time multi-modal feedback is a critical element in guided training. Serious games have been introduced as a platform for at-home motor training due to their highly interactive and multi-modal nature. This dissertation explores the design of a multimodal environment for at-home training in which an autonomous system observes and guides the user in the place of a live trainer, providing real-time assessment, feedback and difficulty adaptation as the subject masters a motor skill. After an in-depth review of the latest solutions in this field, this dissertation proposes a person-centric approach to the design of this environment, in …

Contributors
Tadayon, Ramin, Panchanathan, Sethuraman, McDaniel, Troy, et al.
Created Date
2017

Dynamic software update (DSU) enables a program to update while it is running. DSU aims to minimize the loss due to program downtime for updates. Usually DSU is done in three steps: suspending the execution of an old program, mapping the execution state from the old program to a new one, and resuming execution of the new program with the mapped state. The semantic correctness of DSU depends largely on the state mapping which is mostly composed by developers manually nowadays. However, the manual construction of a state mapping does not necessarily ensure sound and dependable state mapping. This dissertation …

Contributors
Shen, Jun, Bazzi, Rida A, Fainekos, Georgios, et al.
Created Date
2015

Nearly 25 years ago, parallel computing techniques were first applied to vector spatial analysis methods. This initial research was driven by the desire to reduce computing times in order to support scaling to larger problem sets. Since this initial work, rapid technological advancement has driven the availability of High Performance Computing (HPC) resources, in the form of multi-core desktop computers, distributed geographic information processing systems, e.g. computational grids, and single site HPC clusters. In step with increases in computational resources, significant advancement in the capabilities to capture and store large quantities of spatially enabled data have been realized. A key …

Contributors
Laura, Jason R., Rey, Sergio J., Anselin, Luc, et al.
Created Date
2015

Automating aspects of biocuration through biomedical information extraction could significantly impact biomedical research by enabling greater biocuration throughput and improving the feasibility of a wider scope. An important step in biomedical information extraction systems is named entity recognition (NER), where mentions of entities such as proteins and diseases are located within natural-language text and their semantic type is determined. This step is critical for later tasks in an information extraction pipeline, including normalization and relationship extraction. BANNER is a benchmark biomedical NER system using linear-chain conditional random fields and the rich feature set approach. A case study with BANNER locating …

Contributors
Leaman, James Robert, Gonzalez, Graciela, Baral, Chitta, et al.
Created Date
2013

An old proverb claims that “two heads are better than one”. Crowdsourcing research and practice have taken this to heart, attempting to show that thousands of heads can be even better. This is not limited to leveraging a crowd’s knowledge, but also their creativity—the ability to generate something not only useful, but also novel. In practice, there are initiatives such as Free and Open Source Software communities developing innovative software. In research, the field of crowdsourced creativity, which attempts to design scalable support mechanisms, is blooming. However, both contexts still present many opportunities for advancement. In this dissertation, I seek …

Contributors
da Silva Girotto, Victor Augusto, Walker, Erin A, Burleson, Winslow, et al.
Created Date
2019

Affect signals what humans care about and is involved in rational decision-making and action selection. Many technologies may be improved by the capability to recognize human affect and to respond adaptively by appropriately modifying their operation. This capability, named affect-driven self-adaptation, benefits systems as diverse as learning environments, healthcare applications, and video games, and indeed has the potential to improve systems that interact intimately with users across all sectors of society. The main challenge is that existing approaches to advancing affect-driven self-adaptive systems typically limit their applicability by supporting the creation of one-of-a-kind systems with hard-wired affect recognition and self-adaptation …

Contributors
Gonzalez Sanchez, Javier, Burleson, Winslow, Collofello, James, 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

In the last 15 years, there has been a significant increase in the number of motor neural prostheses used for restoring limb function lost due to neurological disorders or accidents. The aim of this technology is to enable patients to control a motor prosthesis using their residual neural pathways (central or peripheral). Recent studies in non-human primates and humans have shown the possibility of controlling a prosthesis for accomplishing varied tasks such as self-feeding, typing, reaching, grasping, and performing fine dexterous movements. A neural decoding system comprises mainly of three components: (i) sensors to record neural signals, (ii) an algorithm …

Contributors
Padmanaban, Subash, Greger, Bradley, Santello, Marco, et al.
Created Date
2017

Cyber systems, including IoT (Internet of Things), are increasingly being used ubiquitously to vastly improve the efficiency and reduce the cost of critical application areas, such as finance, transportation, defense, and healthcare. Over the past two decades, computing efficiency and hardware cost have dramatically been improved. These improvements have made cyber systems omnipotent, and control many aspects of human lives. Emerging trends in successful cyber system breaches have shown increasing sophistication in attacks and that attackers are no longer limited by resources, including human and computing power. Most existing cyber defense systems for IoT systems have two major issues: (1) …

Contributors
Buduru, Arun Balaji, Yau, Sik-Sang, Ahn, Gail-Joon, et al.
Created Date
2016

Internet of Things (IoT) is emerging as part of the infrastructures for advancing a large variety of applications involving connections of many intelligent devices, leading to smart communities. Due to the severe limitation of the computing resources of IoT devices, it is common to offload tasks of various applications requiring substantial computing resources to computing systems with sufficient computing resources, such as servers, cloud systems, and/or data centers for processing. However, this offloading method suffers from both high latency and network congestion in the IoT infrastructures. Recently edge computing has emerged to reduce the negative impacts of tasks offloading to …

Contributors
Song, Yaozhong, Yau, Sik-Sang, Huang, Dijiang, et al.
Created Date
2018

Currently, educational games are designed with the educational content as the primary factor driving the design of the game. While this may seem to be the optimal approach, this design paradigm causes multiple issues. For one, the games themselves are often not engaging as game design principles were put aside in favor of increasing the educational value of the game. The other issue is that the code base of the game is mostly or completely unusable for any other games as the game mechanics are too strongly connected to the educational content being taught. This means that the mechanics are …

Contributors
Baron, Tyler John, Amresh, Ashish, Nelson, Brian C, et al.
Created Date
2017

The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to …

Contributors
Manikonda, Lydia, Kambhampati, Subbarao, Liu, Huan, et al.
Created Date
2019

Wireless communication technologies have been playing an important role in modern society. Due to its inherent mobility property, wireless networks are more vulnerable to passive attacks than traditional wired networks. Anonymity, as an important issue in mobile network environment, serves as the first topic that leads to all the research work presented in this manuscript. Specifically, anonymity issue in Mobile Ad hoc Networks (MANETs) is discussed with details as the first section of research. To thoroughly study on this topic, the presented work approaches it from an attacker's perspective. Under a perfect scenario, all the traffic in a targeted MANET …

Contributors
Li, Bing, Huang, Dijiang, Xue, Guoliang, et al.
Created Date
2016

Answer Set Programming (ASP) is one of the most prominent and successful knowledge representation paradigms. The success of ASP is due to its expressive non-monotonic modeling language and its efficient computational methods originating from building propositional satisfiability solvers. The wide adoption of ASP has motivated several extensions to its modeling language in order to enhance expressivity, such as incorporating aggregates and interfaces with ontologies. Also, in order to overcome the grounding bottleneck of computation in ASP, there are increasing interests in integrating ASP with other computing paradigms, such as Constraint Programming (CP) and Satisfiability Modulo Theories (SMT). Due to the …

Contributors
Meng, Yunsong, Lee, Joohyung, Ahn, Gail-Joon, et al.
Created Date
2013

Question Answering has been under active research for decades, but it has recently taken the spotlight following IBM Watson's success in Jeopardy! and digital assistants such as Apple's Siri, Google Now, and Microsoft Cortana through every smart-phone and browser. However, most of the research in Question Answering aims at factual questions rather than deep ones such as ``How'' and ``Why'' questions. In this dissertation, I suggest a different approach in tackling this problem. We believe that the answers of deep questions need to be formally defined before found. Because these answers must be defined based on something, it is better …

Contributors
Vo, Nguyen Ha, Baral, Chitta, Lee, Joohyung, et al.
Created Date
2015

This dissertation presents the Temporal Event Query Language (TEQL), a new language for querying event streams. Event Stream Processing enables online querying of streams of events to extract relevant data in a timely manner. TEQL enables querying of interval-based event streams using temporal database operators. Temporal databases and temporal query languages have been a subject of research for more than 30 years and are a natural fit for expressing queries that involve a temporal dimension. However, operators developed in this context cannot be directly applied to event streams. The research extends a preexisting relational framework for event stream processing to …

Contributors
Shiva, Foruhar Ali, Urban, Susan D, Chen, Yi, et al.
Created Date
2012

One of the main goals of computer architecture design is to improve performance without much increase in the power consumption. It cannot be achieved by adding increasingly complex intelligent schemes in the hardware, since they will become increasingly less power-efficient. Therefore, parallelism comes up as the solution. In fact, the irrevocable trend of computer design in near future is still to keep increasing the number of cores while reducing the operating frequency. However, it is not easy to scale number of cores. One important challenge is that existing cores consume too much power. Another challenge is that cache-based memory hierarchy …

Contributors
Lu, Jing, Shrivastava, Aviral, Sarjoughian, Hessam, et al.
Created Date
2019

Introductory programming courses, also known as CS1, have a specific set of expected outcomes related to the learning of the most basic and essential computational concepts in computer science (CS). However, two of the most often heard complaints in such courses are that (1) they are divorced from the reality of application and (2) they make the learning of the basic concepts tedious. The concepts introduced in CS1 courses are highly abstract and not easily comprehensible. In general, the difficulty is intrinsic to the field of computing, often described as "too mathematical or too abstract." This dissertation presents a small-scale …

Contributors
Billionniere, Elodie V., Collofello, James, Ganesh, Tirupalavanam, et al.
Created Date
2011

Access control is one of the most fundamental security mechanisms used in the design and management of modern information systems. However, there still exists an open question on how formal access control models can be automatically analyzed and fully realized in secure system development. Furthermore, specifying and managing access control policies are often error-prone due to the lack of effective analysis mechanisms and tools. In this dissertation, I present an Assurance Management Framework (AMF) that is designed to cope with various assurance management requirements from both access control system development and policy-based computing. On one hand, the AMF framework facilitates …

Contributors
Hu, Hongxin, Ahn, Gail-Joon, Yau, Stephen S., et al.
Created Date
2012

Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge …

Contributors
Lee, Preston Victor, Dinu, Valentin, Sottara, Davide, et al.
Created Date
2018

The rapid escalation of technology and the widespread emergence of modern technological equipments have resulted in the generation of humongous amounts of digital data (in the form of images, videos and text). This has expanded the possibility of solving real world problems using computational learning frameworks. However, while gathering a large amount of data is cheap and easy, annotating them with class labels is an expensive process in terms of time, labor and human expertise. This has paved the way for research in the field of active learning. Such algorithms automatically select the salient and exemplar instances from large quantities …

Contributors
Chakraborty, Shayok, Panchanathan, Sethuraman, Balasubramanian, Vineeth N., et al.
Created Date
2013

The problem of multiple object tracking seeks to jointly estimate the time-varying cardinality and trajectory of each object. There are numerous challenges that are encountered in tracking multiple objects including a time-varying number of measurements, under varying constraints, and environmental conditions. In this thesis, the proposed statistical methods integrate the use of physical-based models with Bayesian nonparametric methods to address the main challenges in a tracking problem. In particular, Bayesian nonparametric methods are exploited to efficiently and robustly infer object identity and learn time-dependent cardinality; together with Bayesian inference methods, they are also used to associate measurements to objects and …

Contributors
Moraffah, Bahman, Papandreou-Suppappola, Antonia, Bliss, Daniel W., et al.
Created Date
2019

Identifying chemical compounds that inhibit bacterial infection has recently gained a considerable amount of attention given the increased number of highly resistant bacteria and the serious health threat it poses around the world. With the development of automated microscopy and image analysis systems, the process of identifying novel therapeutic drugs can generate an immense amount of data - easily reaching terabytes worth of information. Despite increasing the vast amount of data that is currently generated, traditional analytical methods have not increased the overall success rate of identifying active chemical compounds that eventually become novel therapeutic drugs. Moreover, multispectral imaging has …

Contributors
Trevino, Robert, Liu, Huan, Lamkin, Thomas J, et al.
Created Date
2016

Science instructors need questions for use in exams, homework assignments, class discussions, reviews, and other instructional activities. Textbooks never have enough questions, so instructors must find them from other sources or generate their own questions. In order to supply instructors with biology questions, a semantic network approach was developed for generating open response biology questions. The generated questions were compared to professional authorized questions. To boost students’ learning experience, adaptive selection was built on the generated questions. Bayesian Knowledge Tracing was used as embedded assessment of the student’s current competence so that a suitable question could be selected based on …

Contributors
Zhang, Lishan, VanLehn, Kurt, Baral, Chitta, et al.
Created Date
2015

Decades of research in cyberpsychology and human-computer interaction has pointed to a strong distinction between the online and offline worlds, suggesting that attitudes and behaviors in one domain do not necessarily generalize to the other. However, as humans spend increasing amounts of time in the digital world, psychological understandings of safety may begin to influence human perceptions of threat while online. This dissertation therefore examines whether perceived threat generalizes between domains across archival, correlational, and experimental research methods. Four studies offer insight into the relationship between objective indicators of physical and online safety on the levels of nation and state; …

Contributors
Bodford, Jessica Erin, Kwan, Virginia S. Y., Adame, Bradley, et al.
Created Date
2017

Different logic-based knowledge representation formalisms have different limitations either with respect to expressivity or with respect to computational efficiency. First-order logic, which is the basis of Description Logics (DLs), is not suitable for defeasible reasoning due to its monotonic nature. The nonmonotonic formalisms that extend first-order logic, such as circumscription and default logic, are expressive but lack efficient implementations. The nonmonotonic formalisms that are based on the declarative logic programming approach, such as Answer Set Programming (ASP), have efficient implementations but are not expressive enough for representing and reasoning with open domains. This dissertation uses the first-order stable model semantics, …

Contributors
Palla, Ravi Kiran Reddy, Lee, Joohyung, Baral, Chitta, et al.
Created Date
2012

In recent years, machine learning and data mining technologies have received growing attention in several areas such as recommendation systems, natural language processing, speech and handwriting recognition, image processing and biomedical domain. Many of these applications which deal with physiological and biomedical data require person specific or person adaptive systems. The greatest challenge in developing such systems is the subject-dependent data variations or subject-based variability in physiological and biomedical data, which leads to difference in data distributions making the task of modeling these data, using traditional machine learning algorithms, complex and challenging. As a result, despite the wide application of …

Contributors
Chattopadhyay, Rita, Panchanathan, Sethuraman, Ye, Jieping, et al.
Created Date
2013

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

In recent years, we have observed the prevalence of stream applications in many embedded domains. Stream programs distinguish themselves from traditional sequential programming languages through well defined independent actors, explicit data communication, and stable code/data access patterns. In order to achieve high performance and low power, scratch pad memory (SPM) has been introduced in today's embedded multicore processors. Current design frameworks for developing stream applications on SPM enhanced embedded architectures typically do not include a compiler that can perform automatic partitioning, mapping and scheduling under limited on-chip SPM capacities and memory access delays. Consequently, many designs are implemented manually, which …

Contributors
Che, Weijia, Chatha, Karam Singh, Chatha, Karam Singh, et al.
Created Date
2012

The holy grail of computer hardware across all market segments has been to sustain performance improvement at the same pace as silicon technology scales. As the technology scales and the size of transistors shrinks, the power consumption and energy usage per transistor decrease. On the other hand, the transistor density increases significantly by technology scaling. Due to technology factors, the reduction in power consumption per transistor is not sufficient to offset the increase in power consumption per unit area. Therefore, to improve performance, increasing energy-efficiency must be addressed at all design levels from circuit level to application and algorithm levels. …

Contributors
Hamzeh, Mahdi, Vrudhula, Sarma, Gopalakrishnan, Kailash, et al.
Created Date
2015

We are expecting hundreds of cores per chip in the near future. However, scaling the memory architecture in manycore architectures becomes a major challenge. Cache coherence provides a single image of memory at any time in execution to all the cores, yet coherent cache architectures are believed will not scale to hundreds and thousands of cores. In addition, caches and coherence logic already take 20-50% of the total power consumption of the processor and 30-60% of die area. Therefore, a more scalable architecture is needed for manycore architectures. Software Managed Manycore (SMM) architectures emerge as a solution. They have scalable …

Contributors
Bai, Ke, Shrivastava, Aviral, Chatha, Karamvir, et al.
Created Date
2014

This dissertation focuses on creating a pluralistic approach to understanding and measuring interdisciplinarity at various scales to further the study of the evolution of knowledge and innovation. Interdisciplinarity is considered an important research component and is closely linked to higher rates of innovation. If the goal is to create more innovative research, we must understand how interdisciplinarity operates. I begin by examining interdisciplinarity with a small scope, the research university. This study uses metadata to create co-authorship networks and examine how a change in university policies to increase interdisciplinarity can be successful. The New American University Initiative (NAUI) at Arizona …

Contributors
Painter, Deryc T, Laubichler, Manfred D, Maienschein, Jane, et al.
Created Date
2019

As we migrate into an era of personalized medicine, understanding how bio-molecules interact with one another to form cellular systems is one of the key focus areas of systems biology. Several challenges such as the dynamic nature of cellular systems, uncertainty due to environmental influences, and the heterogeneity between individual patients render this a difficult task. In the last decade, several algorithms have been proposed to elucidate cellular systems from data, resulting in numerous data-driven hypotheses. However, due to the large number of variables involved in the process, many of which are unknown or not measurable, such computational approaches often …

Contributors
Ramesh, Archana, Kim, Seungchan, Langley, Patrick W, et al.
Created Date
2012

Medical images constitute a special class of images that are captured to allow diagnosis of disease, and their "correct" interpretation is vitally important. Because they are not "natural" images, radiologists must be trained to visually interpret them. This training process includes implicit perceptual learning that is gradually acquired over an extended period of exposure to medical images. This dissertation proposes novel computational methods for evaluating and facilitating perceptual training in radiologists. Part 1 of this dissertation proposes an eye-tracking-based metric for measuring the training progress of individual radiologists. Six metrics were identified as potentially useful: time to complete task, fixation …

Contributors
Alzubaidi, Mohammad Abdulhadi Moh'D, Panchanathan, Sethuraman, Black, John A, et al.
Created Date
2012

Human movement is a complex process influenced by physiological and psychological factors. The execution of movement is varied from person to person, and the number of possible strategies for completing a specific movement task is almost infinite. Different choices of strategies can be perceived by humans as having different degrees of quality, and the quality can be defined with regard to aesthetic, athletic, or health-related ratings. It is useful to measure and track the quality of a person's movements, for various applications, especially with the prevalence of low-cost and portable cameras and sensors today. Furthermore, based on such measurements, feedback …

Contributors
Wang, Qiao, Turaga, Pavan, Spanias, Andreas, et al.
Created Date
2018

A myriad of social media services are emerging in recent years that allow people to communicate and express themselves conveniently and easily. The pervasive use of social media generates massive data at an unprecedented rate. It becomes increasingly difficult for online users to find relevant information or, in other words, exacerbates the information overload problem. Meanwhile, users in social media can be both passive content consumers and active content producers, causing the quality of user-generated content can vary dramatically from excellence to abuse or spam, which results in a problem of information credibility. Trust, providing evidence about with whom users …

Contributors
Tang, Jiliang, Liu, Huan, Xue, Guoliang, et al.
Created Date
2015

In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in unencrypted forms to remote machines owned and operated by third-party service providers, there are risks of unauthorized use of the users' sensitive data by service providers. Although there are many techniques for protecting users' data from outside attackers, currently there is no effective way to protect users' sensitive data from service providers. In this dissertation, an …

Contributors
An, Hogeun, Yau, Sik-Sang, Huang, Dijiang, et al.
Created Date
2012

Rapid intraoperative diagnosis of brain tumors is of great importance for planning treatment and guiding the surgeon about the extent of resection. Currently, the standard for the preliminary intraoperative tissue analysis is frozen section biopsy that has major limitations such as tissue freezing and cutting artifacts, sampling errors, lack of immediate interaction between the pathologist and the surgeon, and time consuming. Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor …

Contributors
Izady Yazdanabadi, Mohammadhassan, Preul, Mark, Yang, Yezhou, et al.
Created Date
2019

In most social networking websites, users are allowed to perform interactive activities. One of the fundamental features that these sites provide is to connecting with users of their kind. On one hand, this activity makes online connections visible and tangible; on the other hand, it enables the exploration of our connections and the expansion of our social networks easier. The aggregation of people who share common interests forms social groups, which are fundamental parts of our social lives. Social behavioral analysis at a group level is an active research area and attracts many interests from the industry. Challenges of my …

Contributors
Wang, Xufei, Liu, Huan, Kambhampati, Subbarao, et al.
Created Date
2013

Quad-dominant (QD) meshes, i.e., three-dimensional, 2-manifold polygonal meshes comprising mostly four-sided faces (i.e., quads), are a popular choice for many applications such as polygonal shape modeling, computer animation, base meshes for spline and subdivision surface, simulation, and architectural design. This thesis investigates the topic of connectivity control, i.e., exploring different choices of mesh connectivity to represent the same 3D shape or surface. One key concept of QD mesh connectivity is the distinction between regular and irregular elements: a vertex with valence 4 is regular; otherwise, it is irregular. In a similar sense, a face with four sides is regular; otherwise, …

Contributors
Peng, Chi-Han, Wonka, Peter, Maciejewski, Ross, et al.
Created Date
2014

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

Audio signals, such as speech and ambient sounds convey rich information pertaining to a user’s activity, mood or intent. Enabling machines to understand this contextual information is necessary to bridge the gap in human-machine interaction. This is challenging due to its subjective nature, hence, requiring sophisticated techniques. This dissertation presents a set of computational methods, that generalize well across different conditions, for speech-based applications involving emotion recognition and keyword detection, and ambient sounds-based applications such as lifelogging. The expression and perception of emotions varies across speakers and cultures, thus, determining features and classification methods that generalize well to different conditions …

Contributors
Shah, Mohit, Spanias, Andreas, Chakrabarti, Chaitali, et al.
Created Date
2015

Text mining of biomedical literature and clinical notes is a very active field of research in biomedical science. Semantic analysis is one of the core modules for different Natural Language Processing (NLP) solutions. Methods for calculating semantic relatedness of two concepts can be very useful in solutions solving different problems such as relationship extraction, ontology creation and question / answering [1–6]. Several techniques exist in calculating semantic relatedness of two concepts. These techniques utilize different knowledge sources and corpora. So far, researchers attempted to find the best hybrid method for each domain by combining semantic relatedness techniques and data sources …

Contributors
Emadzadeh, Ehsan, Gonzalez, Graciela, Greenes, Robert, et al.
Created Date
2016

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