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- Genre: Academic theses
- Creators: Liu, Huan
- Creators: Goryll, Michael
- Creators: Ryan, Russell
- Member of: ASU Electronic Theses and Dissertations
- Member of: Theses and Dissertations
- Status: Published
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
There will always be a need for high current/voltage transistors. A transistor that has the ability to be both or either of these things is the silicon metal-silicon field effect transistor (MESFET). An additional perk that silicon MESFET transistors have is the ability to be integrated into the standard silicon on insulator (SOI) complementary metal oxide semiconductor (CMOS) process flow. This makes a silicon MESFET transistor a very valuable device for use in any standard CMOS circuit that may usually need a separate integrated circuit (IC) in order to switch power on or from a high current/voltage because it allows this function to be performed with a single chip thereby cutting costs. The ability for the MESFET to cost effectively satisfy the needs of this any many other high current/voltage device application markets is what drives the study of MESFET optimization. Silicon MESFETs that are integrated into standard SOI CMOS processes often receive dopings during fabrication that would not ideally be there in a process made exclusively for MESFETs. Since these remnants of SOI CMOS processing effect the operation of a MESFET device, their effect can be seen in the current-voltage characteristics of a measured MESFET device. Device simulations are done and compared to measured silicon MESFET data in order to deduce the cause and effect of many of these SOI CMOS remnants. MESFET devices can be made in both fully depleted (FD) and partially depleted (PD) SOI CMOS technologies. Device simulations are used to do a comparison of FD and PD MESFETs in order to show the advantages and disadvantages of MESFETs fabricated in different technologies. It is shown that PD MESFET have the highest current per area capability. Since the PD MESFET is shown to have the highest current capability, a layout optimization method to further increase the current per area capability of the PD silicon MESFET is presented, derived, and proven to a first order.
ContributorsSochacki, John (Author) / Thornton, Trevor J (Thesis advisor) / Schroder, Dieter (Committee member) / Vasileska, Dragica (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
ABSTRACT The purpose of this study is to demonstrate that stable lipid bilayers can be set up on an array of silicon micropores and can be used as sites for self-inserting ion-channel proteins which can be studied independently of each other. In course of this study an acrylic based holder was designed and machined to ensure leak-free fluidic access to the silicon micropores and physical isolation of the individual array channels. To measure the ion-channel currents, we simulated, designed and manufactured low-noise transimpedance amplifiers and support circuits based on published patch clamp amplifier designs, using currently available surface-mount components. This was done in order to achieve a reduction in size and costs as well as isolation of individual channels without the need for multiplexing of the input. During the experiments performed, stable bilayers were formed across an array of four vertically mounted 30 µm silicon micropores and OmpF porins were added for self insertion in each of the bilayers. To further demonstrate the independence of these bilayer recording sites, the antibiotic Ampicillin (2.5 mM) was added to one of the fluidic wells. The ionic current in each of the wells was recorded simultaneously. Sub-conductance states of Ompf porin were observed in two of the measurement sites. In addition, the conductance steps in the site containing the antibiotic could be clearly seen to be larger compared to those of the unmodified site. This is due to the transient blocking of ion flow through the porin due to translocation of the antibiotic. Based on this demonstration, ion-channel array reconstitution is a potential method for efficient electrophysiological characterization of different types of ion-channels simultaneously as well as for studying membrane permeation processes.
ContributorsRamakrishnan, Shankar (Author) / Goryll, Michael (Thesis advisor) / Thornton, Trevor J (Committee member) / Blain Christen, Jennifer M (Committee member) / Arizona State University (Publisher)
Created2011
Description
In the last few years, significant advances in nanofabrication have allowed tailoring of structures and materials at a molecular level enabling nanofabrication with precise control of dimensions and organization at molecular length scales, a development leading to significant advances in nanoscale systems. Although, the direction of progress seems to follow the path of microelectronics, the fundamental physics in a nanoscale system changes more rapidly compared to microelectronics, as the size scale is decreased. The changes in length, area, and volume ratios due to reduction in size alter the relative influence of various physical effects determining the overall operation of a system in unexpected ways. One such category of nanofluidic structures demonstrating unique ionic and molecular transport characteristics are nanopores. Nanopores derive their unique transport characteristics from the electrostatic interaction of nanopore surface charge with aqueous ionic solutions. In this doctoral research cylindrical nanopores, in single and array configuration, were fabricated in silicon-on-insulator (SOI) using a combination of electron beam lithography (EBL) and reactive ion etching (RIE). The fabrication method presented is compatible with standard semiconductor foundries and allows fabrication of nanopores with desired geometries and precise dimensional control, providing near ideal and isolated physical modeling systems to study ion transport at the nanometer level. Ion transport through nanopores was characterized by measuring ionic conductances of arrays of nanopores of various diameters for a wide range of concentration of aqueous hydrochloric acid (HCl) ionic solutions. Measured ionic conductances demonstrated two distinct regimes based on surface charge interactions at low ionic concentrations and nanopore geometry at high ionic concentrations. Field effect modulation of ion transport through nanopore arrays, in a fashion similar to semiconductor transistors, was also studied. Using ionic conductance measurements, it was shown that the concentration of ions in the nanopore volume was significantly changed when a gate voltage on nanopore arrays was applied, hence controlling their transport. Based on the ion transport results, single nanopores were used to demonstrate their application as nanoscale particle counters by using polystyrene nanobeads, monodispersed in aqueous HCl solutions of different molarities. Effects of field effect modulation on particle transition events were also demonstrated.
ContributorsJoshi, Punarvasu (Author) / Thornton, Trevor J (Thesis advisor) / Goryll, Michael (Thesis advisor) / Spanias, Andreas (Committee member) / Saraniti, Marco (Committee member) / Arizona State University (Publisher)
Created2011
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
Internet sites that support user-generated content, so-called Web 2.0, have become part of the fabric of everyday life in technologically advanced nations. Users collectively spend billions of hours consuming and creating content on social networking sites, weblogs (blogs), and various other types of sites in the United States and around the world. Given the fundamentally emotional nature of humans and the amount of emotional content that appears in Web 2.0 content, it is important to understand how such websites can affect the emotions of users. This work attempts to determine whether emotion spreads through an online social network (OSN). To this end, a method is devised that employs a model based on a general threshold diffusion model as a classifier to predict the propagation of emotion between users and their friends in an OSN by way of mood-labeled blog entries. The model generalizes existing information diffusion models in that the state machine representation of a node is generalized from being binary to having n-states in order to support n class labels necessary to model emotional contagion. In the absence of ground truth, the prediction accuracy of the model is benchmarked with a baseline method that predicts the majority label of a user's emotion label distribution. The model significantly outperforms the baseline method in terms of prediction accuracy. The experimental results make a strong case for the existence of emotional contagion in OSNs in spite of possible alternative arguments such confounding influence and homophily, since these alternatives are likely to have negligible effect in a large dataset or simply do not apply to the domain of human emotions. A hybrid manual/automated method to map mood-labeled blog entries to a set of emotion labels is also presented, which enables the application of the model to a large set (approximately 900K) of blog entries from LiveJournal.
ContributorsCole, William David, M.S (Author) / Liu, Huan (Thesis advisor) / Sarjoughian, Hessam S. (Committee member) / Candan, Kasim S (Committee member) / Arizona State University (Publisher)
Created2011
Description
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 provenance methodologies and technologies providing exciting research opportunities. The guiding vision is the use of social media information itself to realize a useful amount of provenance data for information in social media. This departs from traditional approaches for data provenance which rely on a central store of provenance information. The contemporary online social media environment is an enormous and constantly updated "central store" that can be mined for provenance information that is not readily made available to the average social media user. This research introduces an approach and builds a foundation aimed at realizing a provenance data capability for social media users that is not accessible today.
ContributorsBarbier, Geoffrey P (Author) / Liu, Huan (Thesis advisor) / Bell, Herbert (Committee member) / Li, Baoxin (Committee member) / Sen, Arunabha (Committee member) / Arizona State University (Publisher)
Created2011
Description
In very small electronic devices the alternate capture and emission of carriers at an individual defect site located at the interface of Si:SiO2 of a MOSFET generates discrete switching in the device conductance referred to as a random telegraph signal (RTS) or random telegraph noise (RTN). In this research work, the integration of random defects positioned across the channel at the Si:SiO2 interface from source end to the drain end in the presence of different random dopant distributions are used to conduct Ensemble Monte-Carlo ( EMC ) based numerical simulation of key device performance metrics for 45 nm gate length MOSFET device. The two main performance parameters that affect RTS based reliability measurements are percentage change in threshold voltage and percentage change in drain current fluctuation in the saturation region. It has been observed as a result of the simulation that changes in both and values moderately decrease as the defect position is gradually moved from source end to the drain end of the channel. Precise analytical device physics based model needs to be developed to explain and assess the EMC simulation based higher VT fluctuations as experienced for trap positions at the source side. A new analytical model has been developed that simultaneously takes account of dopant number variations in the channel and depletion region underneath and carrier mobility fluctuations resulting from fluctuations in surface potential barriers. Comparisons of this new analytical model along with existing analytical models are shown to correlate with 3D EMC simulation based model for assessment of VT fluctuations percentage induced by a single interface trap. With scaling of devices beyond 32 nm node, halo doping at the source and drain are routinely incorporated to combat the threshold voltage roll-off that takes place with effective channel length reduction. As a final study on this regard, 3D EMC simulation method based computations of threshold voltage fluctuations have been performed for varying source and drain halo pocket length to illustrate the threshold voltage fluctuations related reliability problems that have been aggravated by trap positions near the source at the interface compared to conventional 45 nm MOSFET.
ContributorsAshraf, Nabil Shovon (Author) / Vasileska, Dragica (Thesis advisor) / Schroder, Dieter (Committee member) / Goodnick, Stephen (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2011
Description
The past two decades have been monumental in the advancement of microchips designed for a diverse range of medical applications and bio-analysis. Owing to the remarkable progress in micro-fabrication technology, complex chemical and electro-mechanical features can now be integrated into chip-scale devices for use in biosensing and physiological measurements. Some of these devices have made enormous contributions in the study of complex biochemical processes occurring at the molecular and cellular levels while others overcame the challenges of replicating various functions of human organs as implant systems. This thesis presents test data and analysis of two such systems. First, an ISFET based pH sensor is characterized for its performance in a continuous pH monitoring application. Many of the basic properties of ISFETs including I-V characteristics, pH sensitivity and more importantly, its long term drift behavior have been investigated. A new theory based on frequent switching of electric field across the gate oxide to decrease the rate of current drift has been successfully implemented with the help of an automated data acquisition and switching system. The system was further tested for a range of duty cycles in order to accurately determine the minimum length of time required to fully reset the drift. Second, a microfluidic based vestibular implant system was tested for its underlying characteristics as a light sensor. A computer controlled tilt platform was then implemented to further test its sensitivity to inclinations and thus it‟s more important role as a tilt sensor. The sensor operates through means of optoelectronics and relies on the signals generated from photodiode arrays as a result of light being incident on them. ISFET results show a significant drop in the overall drift and good linear characteristics. The drift was seen to reset at less than an hour. The photodiodes show ideal I-V comparison between photoconductive and photovoltaic modes of operation with maximum responsivity at 400nm and a shunt resistance of 394 MΩ. Additionally, post-processing of the tilt sensor to incorporate the sensing fluids is outlined. Based on several test and fabrication results, a possible method of sealing the open cavity of the chip using a UV curable epoxy has been discussed.
ContributorsMamun, Samiha (Author) / Christen, Jennifer Blain (Thesis advisor) / Goryll, Michael (Committee member) / Yu, Hongyu (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms.
ContributorsSun, Liang (Author) / Ye, Jieping (Thesis advisor) / Li, Baoxin (Committee member) / Liu, Huan (Committee member) / Mittelmann, Hans D. (Committee member) / Arizona State University (Publisher)
Created2011