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- Genre: Academic theses
- Creators: Liu, Huan
- Creators: Yu, Hongbin
- Resource Type: Text
- Status: Published
Description
A workload-aware low-power neuromorphic controller for dynamic power and thermal management in VLSI systems is presented. The neuromorphic controller predicts future workload and temperature values based on the past values and CPU performance counters and preemptively regulates supply voltage and frequency. System-level measurements from stateof-the-art commercial microprocessors are used to get workload, temperature and CPU performance counter values. The controller is designed and simulated using circuit-design and synthesis tools. At device-level, on-chip planar inductors suffer from low inductance occupying large chip area. On-chip inductors with integrated magnetic materials are designed, simulated and fabricated to explore performance-efficiency trade offs and explore potential applications such as resonant clocking and on-chip voltage regulation. A system level study is conducted to evaluate the effect of on-chip voltage regulator employing magnetic inductors as the output filter. It is concluded that neuromorphic power controller is beneficial for fine-grained per-core power management in conjunction with on-chip voltage regulators utilizing scaled magnetic inductors.
ContributorsSinha, Saurabh (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Yu, Hongbin (Committee member) / Christen, Jennifer B. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Given the process of tumorigenesis, biological signaling pathways have become of interest in the field of oncology. Many of the regulatory mechanisms that are altered in cancer are directly related to signal transduction and cellular communication. Thus, identifying signaling pathways that have become deregulated may provide useful information to better understanding altered regulatory mechanisms within cancer. Many methods that have been created to measure the distinct activity of signaling pathways have relied strictly upon transcription profiles. With advancements in comparative genomic hybridization techniques, copy number data has become extremely useful in providing valuable information pertaining to the genomic landscape of cancer. The purpose of this thesis is to develop a methodology that incorporates both gene expression and copy number data to identify signaling pathways that have become deregulated in cancer. The central idea is that copy number data may significantly assist in identifying signaling pathway deregulation by justifying the aberrant activity being measured in gene expression profiles. This method was then applied to four different subtypes of breast cancer resulting in the identification of signaling pathways associated with distinct functionalities for each of the breast cancer subtypes.
ContributorsTrevino, Robert (Author) / Kim, Seungchan (Thesis advisor) / Ringner, Markus (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2011
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
CMOS technology is expected to enter the 10nm regime for future integrated circuits (IC). Such aggressive scaling leads to vastly increased variability, posing a grand challenge to robust IC design. Variations in CMOS are often divided into two types: intrinsic variations and process-induced variations. Intrinsic variations are limited by fundamental physics. They are inherent to CMOS structure, considered as one of the ultimate barriers to the continual scaling of CMOS devices. In this work the three primary intrinsic variations sources are studied, including random dopant fluctuation (RDF), line-edge roughness (LER) and oxide thickness fluctuation (OTF). The research is focused on the modeling and simulation of those variations and their scaling trends. Besides the three variations, a time dependent variation source, Random Telegraph Noise (RTN) is also studied. Different from the other three variations, RTN does not contribute much to the total variation amount, but aggregate the worst case of Vth variations in CMOS. In this work a TCAD based simulation study on RTN is presented, and a new SPICE based simulation method for RTN is proposed for time domain circuit analysis. Process-induced variations arise from the imperfection in silicon fabrication, and vary from foundries to foundries. In this work the layout dependent Vth shift due to Rapid-Thermal Annealing (RTA) are investigated. In this work, we develop joint thermal/TCAD simulation and compact modeling tools to analyze performance variability under various layout pattern densities and RTA conditions. Moreover, we propose a suite of compact models that bridge the underlying RTA process with device parameter change for efficient design optimization.
ContributorsYe, Yun, Ph.D (Author) / Cao, Yu (Thesis advisor) / Yu, Hongbin (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2011
Description
In this work, I worked on the synthesis and characterization of nanowires and belts, grown using different materials, in Chemical Vapor Deposition (CVD) system with catalytic growth method. Through this thesis, I utilized the Photoluminescence (PL), Secondary Electron Microscopy (SEM), Energy Dispersive Spectroscopy (EDS) and X-ray diffraction (XRD) analyses to find out the properties of Erbium Chloride Silicate (ECS) and two segment CdS-CdSe samples. In the first part of my research, growth of very new material, Erbium Chloride Silicate (ECS), in form of core/shell Si/ECS and pure ECS nanowires, was demonstrated. This new material has very fascinating properties for new Si based photonic devices. The Erbium density in those nanowires is which is very high value compared to the other Erbium doped materials. It was shown that the luminescence peaks of ECS nanowires are very sharp and stronger than their counterparts. Furthermore, both PL and XRD peaks get sharper and stronger as growth temperature increases and this shows that crystalline quality of ECS nanowires gets better with higher temperature. In the second part, I did a very detail research for growing two segment axial nanowires or radial belts and report that the structure type mostly depends on the growth temperature. Since our final step is to create white light LEDs using single axial nanowires which have three different regions grown with distinct materials and give red, green and blue colors simultaneously, we worked on growing CdS-CdSe nanowires or belts for the first step of our aim. Those products were successfully grown and they gave two luminescence peaks with maximum 160 nm wavelength separation depending on the growth conditions. It was observed that products become more likely belt once the substrate temperature increases. Also, dominance between VLS and VS is very critical to determine the shape of the products and the substitution of CdS by CdSe is very effective; hence, CdSe growth time should be chosen accordingly. However, it was shown two segmented products can be synthesized by picking the right conditions and with very careful analyses. We also demonstrated that simultaneous two colors lasing from a single segmented belt structures is possible with strong enough-pumping-power.
ContributorsTurkdogan, Sunay (Author) / Ning, Cun-Zheng (Thesis advisor) / Tao, Meng (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Studying charge transport through single molecules tethered between two metal electrodes is of fundamental importance in molecular electronics. Over the years, a variety of methods have been developed in attempts of performing such measurements. However, the limitation of these techniques is still one of the factors that prohibit one from gaining a thorough understanding of single molecule junctions. Firstly, the time resolution of experiments is typically limited to milli to microseconds, while molecular dynamics simulations are carried out on the time scale of pico to nanoseconds. A huge gap therefore persists between the theory and the experiments. This thesis demonstrates a nanosecond scale measurement of the gold atomic contact breakdown process. A combined setup of DC and AC circuits is employed, where the AC circuit reveals interesting observations in nanosecond scale not previously seen using conventional DC circuits. The breakdown time of gold atomic contacts is determined to be faster than 0.1 ns and subtle atomic events are observed within nanoseconds. Furthermore, a new method based on the scanning tunneling microscope break junction (STM-BJ) technique is developed to rapidly record thousands of I-V curves from repeatedly formed single molecule junctions. 2-dimensional I-V and conductance-voltage (G-V) histograms constructed using the acquired data allow for more meaningful statistical analysis to single molecule I-V characteristics. The bias voltage adds an additional dimension to the conventional single molecule conductance measurement. This method also allows one to perform transition voltage spectra (TVS) for individual junctions and to study the correlation between the conductance and the tunneling barrier height. The variation of measured conductance values is found to be primarily determined by the poorly defined contact geometry between the molecule and metal electrodes, rather than the tunnel barrier height. In addition, the rapid I-V technique is also found useful in studying thermoelectric effect in single molecule junctions. When applying a temperature gradient between the STM tip and substrate in air, the offset current at zero bias in the I-V characteristics is a measure of thermoelectric current. The rapid I-V technique allows for statistical analysis of such offset current at different temperature gradients and thus the Seebeck coefficient of single molecule junctions is measured. Combining with single molecule TVS, the Seebeck coefficient is also found to be a measure of tunnel barrier height.
ContributorsGuo, Shaoyin (Author) / Tao, Nongjian (Thesis advisor) / Bennett, Peter (Committee member) / Ning, Cun-Zheng (Committee member) / Yu, Hongbin (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
As the 3rd generation solar cell, quantum dot solar cells are expected to outperform the first 2 generations with higher efficiency and lower manufacture cost. Currently the main problems for QD cells are the low conversion efficiency and stability. This work is trying to improve the reliability as well as the device performance by inserting an interlayer between the metal cathode and the active layer. Titanium oxide and a novel nitrogen doped titanium oxide were compared and TiOxNy capped device shown a superior performance and stability to TiOx capped one. A unique light anneal effect on the interfacial layer was discovered first time and proved to be the trigger of the enhancement of both device reliability and efficiency. The efficiency was improved by 300% and the device can retain 73.1% of the efficiency with TiOxNy when normal device completely failed after kept for long time. Photoluminescence indicted an increased charge disassociation rate at TiOxNy interface. External quantum efficiency measurement also inferred a significant performance enhancement in TiOxNy capped device, which resulted in a higher photocurrent. X-ray photoelectron spectrometry was performed to explain the impact of light doping on optical band gap. Atomic force microscopy illustrated the effect of light anneal on quantum dot polymer surface. The particle size is increased and the surface composition is changed after irradiation. The mechanism for performance improvement via a TiOx based interlayer was discussed based on a trap filling model. Then Tunneling AFM was performed to further confirm the reliability of interlayer capped organic photovoltaic devices. As a powerful tool based on SPM technique, tunneling AFM was able to explain the reason for low efficiency in non-capped inverted organic photovoltaic devices. The local injection properties as well as the correspondent topography were compared in organic solar cells with or without TiOx interlayer. The current-voltage characteristics were also tested at a single interested point. A severe short-circuit was discovered in non capped devices and a slight reverse bias leakage current was also revealed in TiOx capped device though tunneling AFM results. The failure reason for low stability in normal devices was also discussed comparing to capped devices.
ContributorsYu, Jialin (Author) / Jabbour, Ghassan E. (Thesis advisor) / Alford, Terry L. (Thesis advisor) / Yu, Hongbin (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