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- Genre: Academic theses
- Creators: Davulcu, Hasan
- Member of: ASU Electronic Theses and Dissertations
- Member of: Theses and Dissertations
Description
This thesis research attempts to observe, measure and visualize the communication patterns among developers of an open source community and analyze how this can be inferred in terms of progress of that open source project. Here I attempted to analyze the Ubuntu open source project's email data (9 subproject log archives over a period of five years) and focused on drawing more precise metrics from different perspectives of the communication data. Also, I attempted to overcome the scalability issue by using Apache Pig libraries, which run on a MapReduce framework based Hadoop Cluster. I described four metrics based on which I observed and analyzed the data and also presented the results which show the required patterns and anomalies to better understand and infer the communication. Also described the usage experience with Pig Latin (scripting language of Apache Pig Libraries) for this research and how they brought the feature of scalability, simplicity, and visibility in this data intensive research work. These approaches are useful in project monitoring, to augment human observation and reporting, in social network analysis, to track individual contributions.
ContributorsMotamarri, Lakshminarayana (Author) / Santanam, Raghu (Thesis advisor) / Ye, Jieping (Thesis advisor) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Source selection is one of the foremost challenges for searching deep-web. For a user query, source selection involves selecting a subset of deep-web sources expected to provide relevant answers to the user query. Existing source selection models employ query-similarity based local measures for assessing source quality. These local measures are necessary but not sufficient as they are agnostic to source trustworthiness and result importance, which, given the autonomous and uncurated nature of deep-web, have become indispensible for searching deep-web. SourceRank provides a global measure for assessing source quality based on source trustworthiness and result importance. SourceRank's effectiveness has been evaluated in single-topic deep-web environments. The goal of the thesis is to extend sourcerank to a multi-topic deep-web environment. Topic-sensitive sourcerank is introduced as an effective way of extending sourcerank to a deep-web environment containing a set of representative topics. In topic-sensitive sourcerank, multiple sourcerank vectors are created, each biased towards a representative topic. At query time, using the topic of query keywords, a query-topic sensitive, composite sourcerank vector is computed as a linear combination of these pre-computed biased sourcerank vectors. Extensive experiments on more than a thousand sources in multiple domains show 18-85% improvements in result quality over Google Product Search and other existing methods.
ContributorsJha, Manishkumar (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advanced composites are being widely used in aerospace applications due to their high stiffness, strength and energy absorption capabilities. However, the assurance of structural reliability is a critical issue because a damage event will compromise the integrity of composite structures and lead to ultimate failure. In this dissertation a novel homogenization based multiscale modeling framework using semi-analytical micromechanics is presented to simulate the response of textile composites. The novelty of this approach lies in the three scale homogenization/localization framework bridging between the constituent (micro), the fiber tow scale (meso), weave scale (macro), and the global response. The multiscale framework, named Multiscale Generalized Method of Cells (MSGMC), continuously bridges between the micro to the global scale as opposed to approaches that are top-down and bottom-up. This framework is fully generalized and capable of modeling several different weave and braids without reformulation. Particular emphasis in this dissertation is placed on modeling the nonlinearity and failure of both polymer matrix and ceramic matrix composites.
ContributorsLiu, Guang (Author) / Chattopadhyay, Aditi (Thesis advisor) / Mignolet, Marc (Committee member) / Jiang, Hanqing (Committee member) / Li, Jian (Committee member) / Rajadas, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis investigated two different thermal flow sensors for intravascular shear stress analysis. They were based on heat transfer principle, which heat convection from the resistively heated element to the flowing fluid was measured as a function of the changes in voltage. For both sensors, the resistively heated elements were made of Ti/Pt strips with the thickness 0.12 µm and 0.02 µm. The resistance of the sensing element was measured at approximately 1.6-1.7 kohms;. A linear relation between the resistance and temperature was established over the temperature ranging from 22 degree Celsius to 80 degree Celsius and the temperature coefficient of resistance (TCR) was at approximately 0.12 %/degree Celsius. The first thermal flow sensor was one-dimensional (1-D) flexible shear stress sensor. The structure was sensing element sandwiched by a biocompatible polymer "poly-para-xylylene", also known as Parylene, which provided both insulation of electrodes and flexibility of the sensors. A constant-temperature (CT) circuit was designed as the read out circuit based on 0.6 µm CMOS (Complementary metal-oxide-semiconductor) process. The 1-D shear stress sensor suffered from a large measurement error. Because when the sensor was inserted into blood vessels, it was impossible to mount the sensor to the wall as calibrated in micro fluidic channels. According to the previous simulation work, the shear stress was varying and the sensor itself changed the shear stress distribution. We proposed a three-dimensional (3-D) thermal flow sensor, with three-axis of sensing elements integrated in one sensor. It was in the similar shape as a hexagonal prism with diagonal of 1000 µm. On the top of the sensor, there were five bond pads for external wires over 500 µm thick silicon substrate. In each nonadjacent side surface, there was a bended parylene branch with one sensing element. Based on the unique 3-D structure, the sensor was able to obtain data along three axes. With computational fluid dynamics (CFD) model, it is possible to locate the sensor in the blood vessels and give us a better understanding of shear stress distribution in the presence of time-varying component of blood flow and realize more accurate assessment of intravascular convective heat transfer.
ContributorsTang, Rui (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Pan, George (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis focuses on the continued extension, validation, and application of combined thermal-structural reduced order models for nonlinear geometric problems. The first part of the thesis focuses on the determination of the temperature distribution and structural response induced by an oscillating flux on the top surface of a flat panel. This flux is introduced here as a simplified representation of the thermal effects of an oscillating shock on a panel of a supersonic/hypersonic vehicle. Accordingly, a random acoustic excitation is also considered to act on the panel and the level of the thermo-acoustic excitation is assumed to be large enough to induce a nonlinear geometric response of the panel. Both temperature distribution and structural response are determined using recently proposed reduced order models and a complete one way, thermal-structural, coupling is enforced. A steady-state analysis of the thermal problem is first carried out that is then utilized in the structural reduced order model governing equations with and without the acoustic excitation. A detailed validation of the reduced order models is carried out by comparison with a few full finite element (Nastran) computations. The computational expedience of the reduced order models allows a detailed parametric study of the response as a function of the frequency of the oscillating flux. The nature of the corresponding structural ROM equations is seen to be of a Mathieu-type with Duffing nonlinearity (originating from the nonlinear geometric effects) with external harmonic excitation (associated with the thermal moments terms on the panel). A dominant resonance is observed and explained. The second part of the thesis is focused on extending the formulation of the combined thermal-structural reduced order modeling method to include temperature dependent structural properties, more specifically of the elasticity tensor and the coefficient of thermal expansion. These properties were assumed to vary linearly with local temperature and it was found that the linear stiffness coefficients and the "thermal moment" terms then are cubic functions of the temperature generalized coordinates while the quadratic and cubic stiffness coefficients were only linear functions of these coordinates. A first validation of this reduced order modeling strategy was successfully carried out.
ContributorsMatney, Andrew (Author) / Mignolet, Marc (Thesis advisor) / Jiang, Hanqing (Committee member) / Spottswood, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Damage assessment and residual useful life estimation (RULE) are essential for aerospace, civil and naval structures. Structural Health Monitoring (SHM) attempts to automate the process of damage detection and identification. Multiscale modeling is a key element in SHM. It not only provides important information on the physics of failure, such as damage initiation and growth, the output can be used as "virtual sensing" data for detection and prognosis. The current research is part of an ongoing multidisciplinary effort to develop an integrated SHM framework for metallic aerospace components. In this thesis a multiscale model has been developed by bridging the relevant length scales, micro, meso and macro (or structural scale). Micro structural representations obtained from material characterization studies are used to define the length scales and to capture the size and orientation of the grains at the micro level. Parametric studies are conducted to estimate material parameters used in this constitutive model. Numerical and experimental simulations are performed to investigate the effects of Representative Volume Element (RVE) size, defect area fraction and distribution. A multiscale damage criterion accounting for crystal orientation effect is developed. This criterion is applied for fatigue crack initial stage prediction. A damage evolution rule based on strain energy density is modified to incorporate crystal plasticity at the microscale (local). Optimization approaches are used to calculate global damage index which is used for the RVE failure prediciton. Potential cracking directions are provided from the damage criterion simultaneously. A wave propagation model is incorporated with the damage model to detect changes in sensing signals due to plastic deformation and damage growth.
ContributorsLuo, Chuntao (Author) / Chattopadhyay, Aditi (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2011
Description
Navigating within non-linear structures is a challenge for all users when the space is large but the problem is most pronounced when the users are blind or visually impaired. Such users access digital content through screen readers like JAWS which read out the text on the screen. However presentation of non-linear narratives in such a manner without visual cues and information about spatial dependencies is very inefficient for such users. The NSDL Science Literacy StrandMaps are visual layouts to help students and teachers browse educational resources. A Strandmap shows relationships between concepts and how they build upon one another across grade levels. NSDL Strandmaps are non-linear narratives which need to be presented to users who are blind in an effective way. A good summary of the Strandmap can give the users an idea about the concepts that are explained in it. This can help them decide whether to view the map or not. In addition, a preview-based navigation mechanism can help users decide which direction they want to take, based on a preview of upcoming content in each direction. Given a non-linear narrative like a Strandmap which has both text and structure, and a word limit w, the goal of this thesis is to find the best way to create its summary. The following approaches are considered: – Purely Text-based Approach using a Multi-document Text Summarizer – Purely Structure-based Approach using PageRank – Approaches Combining both Text and Structure → CUTS-Based Approach (Topic Segmentation) → PageRank with Content Since no reference summaries for such structures were available, user studies were conducted to evaluate these algorithms. PageRank with Content approach performed the best. Another important conclusion was that text and structure are intertwined in a Strandmap by design.
ContributorsGaur, Shruti (Author) / Candan, Kasim Selcuk (Thesis advisor) / Sundaram, Hari (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Templates are wildly used in Web sites development. Finding the template for a given set of Web pages could be very important and useful for many applications like Web page classification and monitoring content and structure changes of Web pages. In this thesis, two novel sequence-based Web page template detection algorithms are presented. Different from tree mapping algorithms which are based on tree edit distance, sequence-based template detection algorithms operate on the Prüfer/Consolidated Prüfer sequences of trees. Since there are one-to-one correspondences between Prüfer/Consolidated Prüfer sequences and trees, sequence-based template detection algorithms identify the template by finding a common subsequence between to Prüfer/Consolidated Prüfer sequences. This subsequence should be a sequential representation of a common subtree of input trees. Experiments on real-world web pages showed that our approaches detect templates effectively and efficiently.
ContributorsHuang, Wei (Author) / Candan, Kasim Selcuk (Thesis advisor) / Sundaram, Hari (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2011
Description
In contemporary society, sustainability and public well-being have been pressing challenges. Some of the important questions are:how can sustainable practices, such as reducing carbon emission, be encouraged? , How can a healthy lifestyle be maintained?Even though individuals are interested, they are unable to adopt these behaviors due to resource constraints. Developing a framework to enable cooperative behavior adoption and to sustain it for a long period of time is a major challenge. As a part of developing this framework, I am focusing on methods to understand behavior diffusion over time. Facilitating behavior diffusion with resource constraints in a large population is qualitatively different from promoting cooperation in small groups. Previous work in social sciences has derived conditions for sustainable cooperative behavior in small homogeneous groups. However, how groups of individuals having resource constraint co-operate over extended periods of time is not well understood, and is the focus of my thesis. I develop models to analyze behavior diffusion over time through the lens of epidemic models with the condition that individuals have resource constraint. I introduce an epidemic model SVRS ( Susceptible-Volatile-Recovered-Susceptible) to accommodate multiple behavior adoption. I investigate the longitudinal effects of behavior diffusion by varying different properties of an individual such as resources,threshold and cost of behavior adoption. I also consider how behavior adoption of an individual varies with her knowledge of global adoption. I evaluate my models on several synthetic topologies like complete regular graph, preferential attachment and small-world and make some interesting observations. Periodic injection of early adopters can help in boosting the spread of behaviors and sustain it for a longer period of time. Also, behavior propagation for the classical epidemic model SIRS (Susceptible-Infected-Recovered-Susceptible) does not continue for an infinite period of time as per conventional wisdom. One interesting future direction is to investigate how behavior adoption is affected when number of individuals in a network changes. The affects on behavior adoption when availability of behavior changes with time can also be examined.
ContributorsDey, Anindita (Author) / Sundaram, Hari (Thesis advisor) / Turaga, Pavan (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
A semiconductor supply chain modeling and simulation platform using Linear Program (LP) optimization and parallel Discrete Event System Specification (DEVS) process models has been developed in a joint effort by ASU and Intel Corporation. A Knowledge Interchange Broker (KIBDEVS/LP) was developed to broker information synchronously between the DEVS and LP models. Recently a single-echelon heuristic Inventory Strategy Module (ISM) was added to correct for forecast bias in customer demand data using different smoothing techniques. The optimization model could then use information provided by the forecast model to make better decisions for the process model. The composition of ISM with LP and DEVS models resulted in the first realization of what is now called the Optimization Simulation Forecast (OSF) platform. It could handle a single echelon supply chain system consisting of single hubs and single products In this thesis, this single-echelon simulation platform is extended to handle multiple echelons with multiple inventory elements handling multiple products. The main aspect for the multi-echelon OSF platform was to extend the KIBDEVS/LP such that ISM interactions with the LP and DEVS models could also be supported. To achieve this, a new, scalable XML schema for the KIB has been developed. The XML schema has also resulted in strengthening the KIB execution engine design. A sequential scheme controls the executions of the DEVS-Suite simulator, CPLEX optimizer, and ISM engine. To use the ISM for multiple echelons, it is extended to compute forecast customer demands and safety stocks over multiple hubs and products. Basic examples for semiconductor manufacturing spanning single and two echelon supply chain systems have been developed and analyzed. Experiments using perfect data were conducted to show the correctness of the OSF platform design and implementation. Simple, but realistic experiments have also been conducted. They highlight the kinds of supply chain dynamics that can be evaluated using discrete event process simulation, linear programming optimization, and heuristics forecasting models.
ContributorsSmith, James Melkon (Author) / Sarjoughian, Hessam S. (Thesis advisor) / Davulcu, Hasan (Committee member) / Fainekos, Georgios (Committee member) / Arizona State University (Publisher)
Created2012