Matching Items (80)
Description
In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
Description
Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training and the other directional dot-motion training, compared to an active control group trained on Sudoku. The three training paradigms were compared on their effectiveness for altering CFFT. Directional dot-motion and contrast sensitivity training resulted in significant improvement in CFFT, while the Sudoku group did not yield significant improvement. This finding indicates that dot-motion and contrast sensitivity training similarly transfer to effect changes in CFFT. The results, combined with prior research linking CFFT to high-order cognitive processes such as reading ability, and studies showing positive impact of both dot-motion and contrast sensitivity training in reading, provide a possible mechanistic link of how these different training approaches impact reading abilities.
ContributorsZhou, Tianyou (Author) / Nanez, Jose (Author) / Zimmerman, Daniel (Author) / Holloway, Steven (Author) / Seitz, Aaron (Author) / New College of Interdisciplinary Arts and Sciences (Contributor)
Created2016-10-26
Description
Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.
ContributorsYahata, Noriaki (Author) / Morimoto, Jun (Author) / Hashimoto, Ryuichiro (Author) / Lisi, Giuseppe (Author) / Shibata, Kazuhisa (Author) / Kawakubo, Yuki (Author) / Kuwabara, Hitoshi (Author) / Kuroda, Miho (Author) / Yamada, Takashi (Author) / Megumi, Fukuda (Author) / Imamizu, Hiroshi (Author) / Nanez, Jose (Author) / Takahashi, Hidehiko (Author) / Okamoto, Yasumasa (Author) / Kasai, Kiyoto (Author) / Kato, Nobumasa (Author) / Sasaki, Yuka (Author) / Watanabe, Takeo (Author) / Kawato, Mitsuo (Author) / New College of Interdisciplinary Arts and Sciences (Contributor)
Created2016-04-14
Description
Creativity is a critical element of human cognition for which any complete explanation of the human mind must account, and it presents a unique problem to cognitive science because the apparent "something from nothing" nature of creativity confounds simple transformations of existing information. Emergentism provides a philosophical framework for explaining this feature of creativity by elaborating how novel properties of a system can be created from the complex interactions of simple elements within that system. Previous advances in cognitive science have been built the traditional information processing models of cognition. These models are limited in their ability to explain emergentism or allow for detailed behavioral measurement and understanding of cognition as it unfolds in time. In this study, I piloted the use state-of-the-art dynamical systems models of cognition and motion capture technology to measure information about cognitive and neural processes in the moments preceding creative insight. Insight problem solving refers to the phenomenon of experiencing an impasse when attempting to solve a problem that is later overcome in a flash of insight, sometimes called an "Aha!" or "Eureka!" moment. The use of these techniques to study insight problem solving provides evidence of the dynamical nature of cognition during creative tasks that may help us explore how creativity emerges from neural activity.
ContributorsHart Jr, John Thomas (Author) / Duran, Nicholas (Thesis director) / Nishimura, Joel (Committee member) / School of Social and Behavioral Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Historically, Supreme Court interpretations of the Constitution of the United States have been significantly important, impacting the lives of every American. This honors thesis seeks to understand the ways in which the Constitution has been interpreted through the lens of political ideology. Using constitutional theory, I explain how the political ideologies of classical liberalism, conservatism, libertarianism, and progressive liberalism have played a role in the interpretations of the First, Second, and Fourth Amendments. I also examine how these ideological interpretations have changed from 1776 to 2017, dividing the history of the United States into four eras: the Founding Era, the Civil War Era, the New Deal Era, and the Modern Era. First, the First Amendment's clauses on religion are examined, where I focus on the separation between church and state as well as the concepts of "establishment" and "free exercise." The First Amendment transitions from classically liberal, to conservative, to progressively liberal and classically liberal, to progressively liberal and libertarian. Next, we look at the Second Amendment's notions of a "militia" and the "right to keep and bear arms." The Second Amendment's interpretations begin classically liberal, then change to classically liberal and progressively liberal, to progressively liberal, to conservative. Finally, the analysis on the Fourth Amendment's "unreasonable searches and seizures" as well as "warrants" lends evidence to ideological interpretations. The Fourth Amendment, like the other two, starts classically liberal for two eras, then becomes libertarian, and finally ends libertarian and conservative. The implications of each of these conclusions are then discussed, with emphasis on public opinion in society during the era in question, the ways in which the ideologies in each era seem to build upon one another, the ideologies of the justices who wrote the opinions, and the ideology of the court.
ContributorsSmith, Charlene Anne (Author) / Lennon, Tara (Thesis director) / Hudson, Jill (Committee member) / New College of Interdisciplinary Arts and Sciences (Contributor) / School of Criminology and Criminal Justice (Contributor) / School of Social and Behavioral Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Individuals with psychogenic non-epileptic seizures (PNES) show signs of emotion-related dysfunction and disrupted interpersonal relationships. Affectionate touch is an important form of non-verbal communication in relationships that may foster emotion regulation and emotional awareness. The present online survey study included 62 individuals with PNES and 80 seizure-free trauma-exposed controls high (n=40) or low (n=40) in overall symptoms of psychopathology. As hypothesized, PNES individuals reported experiencing less frequent affectionate touch and less interoceptive awareness than either control group. They also reported more somatic symptoms, more emotion regulation difficulties, and less positive emotion than the low psychopathology group. Unexpectedly, there were no group differences in emotional awareness difficulties, nor in initiation of affectionate touch. Across participants, lower interoceptive awareness was associated with lower affectionate touch frequency, indicating that if one has difficulty understanding and being aware of their own body, affectionate touch sensations may not necessarily be understood as pleasant and may be minimized or avoided. Emotional awareness difficulties surprisingly were associated with greater affectionate touch frequency among PNES (versus the expected pattern of awareness difficulties associated with less affectionate touch, as found among controls), suggesting affectionate touch may be used as an attempt to try and understand one’s own feelings, or to compensate for, or even mask a lack of understanding. Findings indicate a distinct difference in physical affection frequency and interoceptive awareness among PNES individuals even when matched to a group similar in psychiatric distress/psychopathology. These findings offer insight into the relationships between interoceptive awareness, affectionate touch, and emotion regulation more broadly.
ContributorsVillarreal, Lucia (Author) / Roberts, Nicole A (Thesis advisor) / Burleson, Mary H (Committee member) / Duran, Nicholas (Committee member) / Arizona State University (Publisher)
Created2021
Description
To reveal opinions people may not explicitly portray, researchers have implemented a methodology called the Implicit Associations Test (IAT). While this test saw widespread use after its inception, recent problems have undermined the reliability of the measure. Researchers have begun to address these limitations by evaluating different approaches, such as the Action Dynamics paradigm. Like the IAT, the aim of action dynamics is to assess underlying activation and competition amongst beliefs as they unfold in real-time, while adding a number of more sensitive measures, in addition to those used in an IAT. The trajectories of participants’ computer mouse cursors are tracked as they move from a stimulus statement to a response, providing data of the real-time decisions people are making across a number of variables. For this thesis study, the aim was to use an action dynamics paradigm to explore whether implicit biases exist toward transgender people from a larger cisgender population, even if they explicitly support or oppose others with transgender identities. These potential biases were assessed by evaluating the statements people were asked to confirm or disconfirm. There were also a number of analyses conducted in order to investigate whether such predictors such as
participants’ gender or political ideology predicted differences in responses. Although differences were seen in the reaction time to statements of a certain category, the other trajectory measures showed that participants’ implicit and explicit attitudes toward transgender people were aligned. Implications, limitations, and future directions of this
work are then discussed.
ContributorsHamlett, Mara Carol (Author) / Duran, Nicholas (Thesis advisor) / Mickelson, Kristin (Committee member) / Hall, Deborah (Committee member) / Arizona State University (Publisher)
Created2022
Description
Emotions are an important part of persuasion. Experimental research suggests that White and male jurors can use emotion to increase their influence, while other jurors cannot. This research builds on prior research by examining the relationship between naturally occurring emotion during mock jury deliberations and the influence that jurors hold. Participants (N = 708) in 153 mock juries watched a murder trial video and deliberated on a verdict. Participants self-reported their experienced emotions and rated their perceptions of the other jurors’ emotion and influence. After data was collected, I extracted acoustic indicators of expressed emotion from each deliberation and used a speech emotion recognition model to classify each mock juror’s emotional expression. I hypothesized that there would be an overall effect of emotional expression on influence such that as mock jurors’ emotion increased, their influence would also increase. However, I hypothesized that a juror’s race and gender would moderate the relationship between emotion and influence such that White male jurors will be seen as more influential when they are more emotional, and that female jurors and jurors of color will be seen as less influential when they are more emotional. I also hypothesized that female jurors of color will be doubly penalized for being emotional, due to their “double-minority” status. Bayesian model averaging suggested that the data was most probable under models that included perceived emotion, race, and the interaction between the two, compared to models that did not. Consistent with the hypothesis, as participants were perceived as more emotional, their influence increased. In contrast to the hypotheses, being perceived as more emotional increased influence for both White and non-White mock jurors but the effect was stronger for non-White jurors. In other words, while all jurors benefited from being perceived as more emotional, non-White jurors benefited more than White jurors. Male jurors were more influential than female jurors, and gender did not interact with emotion.. Although being perceived as more emotional predicted increased influence for all participants, this research demonstrates that there are racial and gender disparities in the level of influence that someone might hold on a jury.
ContributorsPhalen, Hannah J (Author) / Salerno, Jessica (Thesis advisor) / Schweitzer, Nicholas (Committee member) / Duran, Nicholas (Committee member) / Arizona State University (Publisher)
Created2023