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- Genre: Academic theses
- Creators: Liu, Huan
- Creators: Ryan, Russell
Description
With the rapid growth of mobile computing and sensor technology, it is now possible to access data from a variety of sources. A big challenge lies in linking sensor based data with social and cognitive variables in humans in real world context. This dissertation explores the relationship between creativity in teamwork, and team members' movement and face-to-face interaction strength in the wild. Using sociometric badges (wearable sensors), electronic Experience Sampling Methods (ESM), the KEYS team creativity assessment instrument, and qualitative methods, three research studies were conducted in academic and industry R&D; labs. Sociometric badges captured movement of team members and face-to-face interaction between team members. KEYS scale was implemented using ESM for self-rated creativity and expert-coded creativity assessment. Activities (movement and face-to-face interaction) and creativity of one five member and two seven member teams were tracked for twenty five days, eleven days, and fifteen days respectively. Day wise values of movement and face-to-face interaction for participants were mean split categorized as creative and non-creative using self- rated creativity measure and expert-coded creativity measure. Paired-samples t-tests [t(36) = 3.132, p < 0.005; t(23) = 6.49 , p < 0.001] confirmed that average daily movement energy during creative days (M = 1.31, SD = 0.04; M = 1.37, SD = 0.07) was significantly greater than the average daily movement of non-creative days (M = 1.29, SD = 0.03; M = 1.24, SD = 0.09). The eta squared statistic (0.21; 0.36) indicated a large effect size. A paired-samples t-test also confirmed that face-to-face interaction tie strength of team members during creative days (M = 2.69, SD = 4.01) is significantly greater [t(41) = 2.36, p < 0.01] than the average face-to-face interaction tie strength of team members for non-creative days (M = 0.9, SD = 2.1). The eta squared statistic (0.11) indicated a large effect size. The combined approach of principal component analysis (PCA) and linear discriminant analysis (LDA) conducted on movement and face-to-face interaction data predicted creativity with 87.5% and 91% accuracy respectively. This work advances creativity research and provides a foundation for sensor based real-time creativity support tools for teams.
ContributorsTripathi, Priyamvada (Author) / Burleson, Winslow (Thesis advisor) / Liu, Huan (Committee member) / VanLehn, Kurt (Committee member) / Pentland, Alex (Committee member) / Arizona State University (Publisher)
Created2011
Description
Throughout the history of Western art music, political and religious institutions have exerted powerful influence through their patronage and censorship. This is especially relevant to the organ, an elaborate and expensive instrument which has always depended on institutional support. The fascinating story of Polish organ culture, which has existed since the Middle Ages, reflects the dramatic changes in Polish politics throughout the centuries. An understanding of this country's history helps to construct a comprehensive view of how politics influenced the developments in organ building and organ playing. This paper describes the dynamics of the Church, government and art institutions in Poland during the years 1945-2012. A brief summary of the history of Polish organ culture sets the stage for the changes occurring after WWII. The constant struggle between the Church and the communist regime affected music making and organ culture in Poland from 1945-1989. The political détente that occurred after 1989 led to a flowering of new instruments, restorations and performance opportunities for organists. By exploring the relationship between Polish organ culture and prevailing agendas in the 20th century, the author demonstrates how a centuries-old tradition adapted to survive political and economic hardships.
ContributorsKubiaczyk-Adler, Ilona (Author) / Marshall, Kimberly (Thesis advisor) / Micklich, Albie (Committee member) / Rockmaker, Jody (Committee member) / Rogers, Rodney (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2012
Description
The organ is in a continued state of evolution, tonally and mechanically, designed by the builder to meet certain expectations related to the musical aesthetics of the time. Organ building in the United States has been influenced by both European organ building traditions and American innovations. During the early twentieth century, Ernest M. Skinner emerged as one of the greatest organ builders in America. Throughout his life, Skinner's quest was to create an "ideal organ," capable of playing a variety of music. Skinner's vision was rooted in the Romantic Movement and influenced by the dynamic gradations and rich, colorful sonorities of orchestral and operatic music of the era. A number of technological developments were applied to the design of the organ which made the romantic organ possible. The prominent European organ builders of the nineteenth century created organs that defined the romantic-style instrument in their respective countries. By the end of the century, American organ builders were creating their own versions. Skinner traveled to Europe to learn what he could from the foreign builders. Skinner built organs that synthesized European and American elements, along with his own innovations, as continuation of nineteenth-century trends that brought the romantic-symphonic organ to its fullest realization. Additionally, Skinner developed many new organ timbres, including a number of stops that imitate various orchestral instruments. The result of Skinner's creative work is the the American symphonic organ. This paper attempts to illustrate how the tonal designs of organs built by Walcker, Cavaillé-Coll, and Willis influenced the work of Skinner and the American symphonic organ. The work of each builder is discussed with descriptions of their designs. The designs and innovations of Skinner are examined as related to these European builders. A number of organ specifications are provided to supplement the information presented here. Today, American symphonic organs, particularly those built by Skinner, are revered for their warmth and charm and are inspiring the work of present day organ builders who are incorporating elements of this style into their own designs.
ContributorsGerber, James Theodore (Author) / Marshall, Kimberly (Thesis advisor) / Pagano, Caio (Committee member) / Ryan, Russell (Committee member) / Rogers, Rodney (Committee member) / Rockmaker, Jody (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of this research paper is to discuss John Carter's Cantata, the musical development of this composition, and provide a brief history of this African American musician and composer. Presently, there exists very little research regarding Carter's life and compositions. From a musician's perspective, this paper discusses the challenges of singing and performing the Cantata for future performers and provides a reference for their preparation. This project also examines John Carter's musical style and analyzes the structure of the Cantata. African-American folk songs were an inspiration to Carter's compositions, especially this particular work. As an African-American, his life and background played a role in his inspiration of composition. With borrowed music, he reveals a basic truth about this period of American history; how the lives of slaves influenced in the development of this particular genre. Additionally, John Carter's style of composition is examined, including the application of jazz and modal scales in his Cantata. Performance practice is examined for both the singer and pianist in a way that best represents the composer's original and unique intent. From vocal safety to breath control, a singer may find several challenges when performing this eclectic piece. This paper provides a guide for singers. A brief overview of the pianist's role in the Cantata is also included. Characteristic words of the African-American vernacular found in Carter's Cantata are briefly discussed and identified (i.e. "them" vs. "dem"). It is essential that any performer, both beginning and advanced, should have a proper understanding of the concepts that Carter had so carefully crafted. This paper endeavors to provide a deeper sense of understanding to what Carter had intended for both the performer and the listener.
ContributorsNa, Bora (Author) / Britton, David (Thesis advisor) / Bush, Jeffrey (Committee member) / Campbell, Andrew (Committee member) / Rogers, Rodney (Committee member) / Ryan, Russell (Committee member) / Arizona State University (Publisher)
Created2012
Description
This paper investigates the origins of the piano recital as invented by Franz Liszt, presents varying strategies for program design, and compares Liszt's application of the format with current trends. In addition it examines the concepts of program music, musical ekphrasis, and Gesamtkunstwerk and proposes a new multimedia piano concert format in which music combines with the mediums of literature and the visual arts; Picturing Rachmaninoff, and Picturing Ravel provide two recent examples of this format.
ContributorsCook, Stephen Barry (Author) / Hamilton, Robert (Thesis advisor) / DeMars, James (Committee member) / Ryan, Russell (Committee member) / Pagano, Caio (Committee member) / Cosand, Walter (Committee member) / Arizona State University (Publisher)
Created2012
Description
This thesis deals with the analysis of interpersonal communication dynamics in online social networks and social media. Our central hypothesis is that communication dynamics between individuals manifest themselves via three key aspects: the information that is the content of communication, the social engagement i.e. the sociological framework emergent of the communication process, and the channel i.e. the media via which communication takes place. Communication dynamics have been of interest to researchers from multi-faceted domains over the past several decades. However, today we are faced with several modern capabilities encompassing a host of social media websites. These sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information, our modes of social engagement, and mechanisms of how the media characteristics impact our interactional behavior. The outcomes of this research are manifold. We present our contributions in three parts, corresponding to the three key organizing ideas. First, we have observed that user context is key to characterizing communication between a pair of individuals. However interestingly, the probability of future communication seems to be more sensitive to the context compared to the delay, which appears to be rather habitual. Further, we observe that diffusion of social actions in a network can be indicative of future information cascades; that might be attributed to social influence or homophily depending on the nature of the social action. Second, we have observed that different modes of social engagement lead to evolution of groups that have considerable predictive capability in characterizing external-world temporal occurrences, such as stock market dynamics as well as collective political sentiments. Finally, characterization of communication on rich media sites have shown that conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Based on all these outcomes, we believe that this research can make significant contribution into a better understanding of how we communicate online and how it is redefining our collective sociological behavior.
ContributorsDe Choudhury, Munmun (Author) / Sundaram, Hari (Thesis advisor) / Candan, K. Selcuk (Committee member) / Liu, Huan (Committee member) / Watts, Duncan J. (Committee member) / Seligmann, Doree D. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-task learning (MTL) aims to improve the generalization performance (of the resulting classifiers) by learning multiple related tasks simultaneously. Specifically, MTL exploits the intrinsic task relatedness, based on which the informative domain knowledge from each task can be shared across multiple tasks and thus facilitate the individual task learning. It is particularly desirable to share the domain knowledge (among the tasks) when there are a number of related tasks but only limited training data is available for each task. Modeling the relationship of multiple tasks is critical to the generalization performance of the MTL algorithms. In this dissertation, I propose a series of MTL approaches which assume that multiple tasks are intrinsically related via a shared low-dimensional feature space. The proposed MTL approaches are developed to deal with different scenarios and settings; they are respectively formulated as mathematical optimization problems of minimizing the empirical loss regularized by different structures. For all proposed MTL formulations, I develop the associated optimization algorithms to find their globally optimal solution efficiently. I also conduct theoretical analysis for certain MTL approaches by deriving the globally optimal solution recovery condition and the performance bound. To demonstrate the practical performance, I apply the proposed MTL approaches on different real-world applications: (1) Automated annotation of the Drosophila gene expression pattern images; (2) Categorization of the Yahoo web pages. Our experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
ContributorsChen, Jianhui (Author) / Ye, Jieping (Thesis advisor) / Kumar, Sudhir (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2011
Description
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 the current methods and delineate the ideas of these methods and illuminate their shortcomings which posed challenges during practical implementation. Based on the experiments conducted and the research carried out, I propose an approach which illustrates the business problems with higher accuracy and provides a broader view of the process. It is then applied to different case studies highlighting the different aspects to this approach.
ContributorsAnand, Aneeth (Author) / Liu, Huan (Thesis advisor) / Kempf, Karl G. (Thesis advisor) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2012
Description
As the information available to lay users through autonomous data sources continues to increase, mediators become important to ensure that the wealth of information available is tapped effectively. A key challenge that these information mediators need to handle is the varying levels of incompleteness in the underlying databases in terms of missing attribute values. Existing approaches such as Query Processing over Incomplete Autonomous Databases (QPIAD) aim to mine and use Approximate Functional Dependencies (AFDs) to predict and retrieve relevant incomplete tuples. These approaches make independence assumptions about missing values--which critically hobbles their performance when there are tuples containing missing values for multiple correlated attributes. In this thesis, I present a principled probabilis- tic alternative that views an incomplete tuple as defining a distribution over the complete tuples that it stands for. I learn this distribution in terms of Bayes networks. My approach involves min- ing/"learning" Bayes networks from a sample of the database, and using it do both imputation (predict a missing value) and query rewriting (retrieve relevant results with incompleteness on the query-constrained attributes, when the data sources are autonomous). I present empirical studies to demonstrate that (i) at higher levels of incompleteness, when multiple attribute values are missing, Bayes networks do provide a significantly higher classification accuracy and (ii) the relevant possible answers retrieved by the queries reformulated using Bayes networks provide higher precision and recall than AFDs while keeping query processing costs manageable.
ContributorsRaghunathan, Rohit (Author) / Kambhampati, Subbarao (Thesis advisor) / Liu, Huan (Committee member) / Lee, Joohyung (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