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- All Subjects: engineering
- Creators: Harrington Bioengineering Program
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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
This dissertation treats a number of related problems in control and data analysis of complex networks.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
First, in existing linear controllability frameworks, the ability to steer a network from any initiate state toward any desired state is measured by the minimum number of driver nodes. However, the associated optimal control energy can become unbearably large, preventing actual control from being realized. Here I develop a physical controllability framework and propose strategies to turn physically uncontrollable networks into physically controllable ones. I also discover that although full control can be guaranteed by the prevailing structural controllability theory, it is necessary to balance the number of driver nodes and control energy to achieve actual control, and my work provides a framework to address this issue.
Second, in spite of recent progresses in linear controllability, controlling nonlinear dynamical networks remains an outstanding problem. Here I develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another. I introduce the concept of attractor network and formulate a quantifiable framework: a network is more controllable if the attractor network is more strongly connected. I test the control framework using examples from various models and demonstrate the beneficial role of noise in facilitating control.
Third, I analyze large data sets from a diverse online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors: linear, “S”-shape and exponential growths. Inspired by cell population growth model in microbial ecology, I construct a base growth model for meme popularity in OSNs. Then I incorporate human interest dynamics into the base model and propose a hybrid model which contains a small number of free parameters. The model successfully predicts the various distinct meme growth dynamics.
At last, I propose a nonlinear dynamics model to characterize the controlling of WNT signaling pathway in the differentiation of neural progenitor cells. The model is able to predict experiment results and shed light on the understanding of WNT regulation mechanisms.
ContributorsWang, Lezhi (Author) / Lai, Ying-Cheng (Thesis advisor) / Wang, Xiao (Thesis advisor) / Papandreoou-Suppappola, Antonia (Committee member) / Brafman, David (Committee member) / Arizona State University (Publisher)
Created2017
Description
Based on James Marcia's theory, identity development in youth is the degree to which one has explored and committed to a vocation [1], [2]. During the path to an engineering identity, students will experience a crisis, when one's values and choices are examined and reevaluated, and a commitment, when the outcome of the crisis leads the student to commit to becoming an engineer. During the crisis phase, students are offered a multitude of experiences to shape their values and choices to influence commitment to becoming an engineering student. Student's identities in engineering are fostered through mentoring from industry, alumni, and peer coaching [3], [4]; experiences that emphasize awareness of the importance of professional interactions [5]; and experiences that show creativity, collaboration, and communication as crucial components to engineering. Further strategies to increase students' persistence include support in their transition to becoming an engineering student, education about professional engineers and the workplace [6], and engagement in engineering activities beyond the classroom. Though these strategies are applied to all students, there are challenges students face in confronting their current identity and beliefs before they can understand their value to society and achieve personal satisfaction. To understand student's progression in developing their engineering identity, first year engineering students were surveyed at the beginning and end of their first semester. Students were asked to rate their level of agreement with 22 statements about their engineering experience. Data included 840 cases. Items with factor loading less than 0.6 suggesting no sufficient explanation were removed in successive factor analysis to identify the four factors. Factor analysis indicated that 60.69% of the total variance was explained by the successive factors. Survey questions were categorized into three factors: engineering identity as defined by sense of belonging and self-efficacy, doubts about becoming an engineer, and exploring engineering. Statements in exploring engineering indicated student awareness, interest and enjoyment within engineering. Students were asked to think about whether they spent time learning what engineers do and participating in engineering activities. Statements about doubts about engineering to engineering indicated whether students had formed opinions about their engineering experience and had understanding about their environment. Engineering identity required thought in belonging and self-efficacy. Belonging statements called for thought about one's opinion in the importance of being an engineer, the meaning of engineering, an attachment to engineering, and self-identification as an engineer. Statements about self-efficacy required students to contemplate their personal judgement of whether they would be able to succeed and their ability to become an engineer. Effort in engineering indicated student willingness to invest time and effort and their choices and effort in their engineering discipline.
ContributorsNguyen, Amanda (Author) / Ganesh, Tirupalavanam (Thesis director) / Robinson, Carrie (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This creative project created and implemented a seven-day STEM curriculum that ultimately encouraged engagement in STEM subjects in students ages 5 through 11. The activities were incorporated into Arizona State University's Kids' Camp over the summer of 2017, every Tuesday afternoon from 4 to 6 p.m. with each activity running for roughly 40 minutes. The lesson plans were created to cover a myriad of scientific topics to account for varied student interest. The topics covered were plant biology, aerodynamics, zoology, geology, chemistry, physics, and astronomy. Each lesson was scaffolded to match the learning needs of the three age groups (5-6 year olds, 7-8 year olds, 9-11 year olds) and to encourage engagement. "Engagement" was measured by pre- and post-activity surveys approved by IRB. The surveys were in the form of statements where the children would totally agree, agree, be undecided, disagree, or totally disagree with it. To more accurately test engagement, the smiley face Likert scale was incorporated with the answer choices. After implementation of the intervention, two-tailed paired t-tests showed that student engagement significantly increased for the two lesson plans of Aerodynamics and Chemistry.
ContributorsHunt, Allison Rene (Co-author) / Belko, Sara (Co-author) / Merritt, Eileen (Thesis director) / Ankeny, Casey (Committee member) / Division of Teacher Preparation (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
The Phoenix CubeSat is a 3U Earth imaging CubeSat which will take infrared (IR) photos of cities in the United Stated to study the Urban Heat Island Effect, (UHI) from low earth orbit (LEO). It has many different components that need to be powered during the life of its mission. The only power source during the mission will be its solar panels. It is difficult to calculate power generation from solar panels by hand because of the different orientations the satellite will be positioned in during orbit; therefore, simulation will be used to produce power generation data. Knowing how much power is generated is integral to balancing the power budget, confirming whether there is enough power for all the components, and knowing whether there will be enough power in the batteries during eclipse. This data will be used to create an optimal design for the Phoenix CubeSat to accomplish its mission.
ContributorsBarakat, Raymond John (Author) / White, Daniel (Thesis director) / Kitchen, Jennifer (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Parkinson's disease is a neurodegenerative disorder in the central nervous system that affects a host of daily activities and involves a variety of symptoms; these include tremors, slurred speech, and rigid muscles. It is the second most common movement disorder globally. In Stage 3 of Parkinson's, afflicted individuals begin to develop an abnormal gait pattern known as freezing of gait (FoG), which is characterized by decreased step length, shuffling, and eventually complete loss of movement; they are unable to move, and often results in a fall. Surface electromyography (sEMG) is a diagnostic tool to measure electrical activity in the muscles to assess overall muscle function. Most conventional EMG systems, however, are bulky, tethered to a single location, expensive, and primarily used in a lab or clinical setting. This project explores an affordable, open-source, and portable platform called Open Brain-Computer Interface (OpenBCI). The purpose of the proposed device is to detect gait patterns by leveraging the surface electromyography (EMG) signals from the OpenBCI and to help a patient overcome an episode using haptic feedback mechanisms. Previously designed devices with similar intended purposes utilize accelerometry as a method of detection as well as audio and visual feedback mechanisms in their design.
ContributorsAnantuni, Lekha (Author) / McDaniel, Troy (Thesis director) / Tadayon, Arash (Committee member) / Harrington Bioengineering Program (Contributor) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
To supplement lectures, various resources are available to students; however, little research has been done to look systematically at which resources studies find most useful and the frequency at which they are used. We have conducted a preliminary study looking at various resources available in an introductory material science course over four semesters using a custom survey called the Student Resource Value Survey (SRVS). More specifically, the SRVS was administered before each test to determine which resources students use to do well on exams. Additionally, over the course of the semester, which resources students used changed. For instance, study resources for exams including the use of homework problems decreased from 81% to 50%, the utilization of teaching assistant for exam studying increased from 25% to 80%, the use of in class Muddiest Points for exam study increased form 28% to 70%, old exams and quizzes only slightly increased for exam study ranging from 78% to 87%, and the use of drop-in tutoring services provided to students at no charge decreased from 25% to 17%. The data suggest that students thought highly of peer interactions by using those resources more than tutoring centers. To date, no research has been completed looking at courses at the department level or a different discipline. To this end, we adapted the SRVS administered in material science to investigate resource use in thirteen biomedical engineering (BME) courses. Here, we assess the following research question: "From a variety of resources, which do biomedical engineering students feel addresses difficult concept areas, prepares them for examinations, and helps in computer-aided design (CAD) and programming the most and with what frequency?" The resources considered include teaching assistants, classroom notes, prior exams, homework problems, Muddiest Points, office hours, tutoring centers, group study, and the course textbook. Results varied across the four topical areas: exam study, difficult concept areas, CAD software, and math-based programming. When preparing for exams and struggling with a learning concept, the most used and useful resources were: 1) homework problems, 2) class notes and 3) group studying. When working on math-based programming (Matlab and Mathcad) as well as computer-aided design, the most used and useful resources were: 1) group studying, 2) engineering tutoring center, and 3) undergraduate teaching assistants. Concerning learning concepts and exams in the BME department, homework problems and class notes were considered some of the highest-ranking resources for both frequency and usefulness. When comparing to the pilot study in MSE, both BME and MSE students tend to highly favor peer mentors and old exams as a means of studying for exams at the end of the semester1. Because the MSE course only considered exams, we cannot make any comparisons to BME data concerning programming and CAD. This analysis has highlighted potential resources that are universally beneficial, such as the use of peer work, i.e. group studying, engineering tutoring center, and teaching assistants; however, we see differences by both discipline and topical area thereby highlighting the need to determine important resources on a class-by-class basis as well.
ContributorsMalkoc, Aldin (Author) / Ankeny, Casey (Thesis director) / Krause, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Engineering is a heavily male-dominated field and females are significantly less likely to choose an engineering-related major or career path. At the age of six years old, females start believing that their male peers are smarter than them, leading them to pursue less ambitious careers. The children's book Lyla B. An Engineering Legacy was created to encourage more young girls to discover their own potential and pursue engineering as a career. To explore the efficacy of the book on its target consumers, a pilot study was performed with first and second grade children. The participants' engineering knowledge; fixed and failure mindset beliefs; STEM (Science, Technology, Engineering, and Math) interest, competency, and career aspirations; and stereotype beliefs were evaluated before and after being read the book to determine if the story has a positive impact on children. Additionally, the satisfaction of the participants towards both the book and main character were analyzed quantitatively and qualitatively. Overall, the results of the study suggest that the book has a positive impact on the interest and competency of STEM fields and the stereotype beliefs that the children had towards engineers. The study also suggests that the book decreases fixed and failure mindsets and that the participants were satisfied with the overall concept of the book and main character, Lyla.
ContributorsPiatak, Catherine (Co-author) / Seelhammer, Marissa Leigh (Co-author) / Torrence, Kelly (Co-author) / Miller, Cindy (Thesis director) / Jordan, Shawn (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Current technology does not allow for the full amount of power produced by solar arrays (PV) on spacecraft to be utilized. The arrays are designed with non-reconfigurable architectures and sent on fifteen to twenty year long missions. They cannot be changed once they are in space, so the arrays are designed for the end of life. Throughout their lifetime, solar arrays can degrade in power producing capabilities anywhere from 20% to 50%. Because there is such a drastic difference in the beginning and end of life power production, and because they cannot be reconfigured, a new design has been found necessary in order to increase power production. Reconfiguration allows the solar arrays to achieve maximum power producing capabilities at both the beginning and end of their lives. With the potential to increase power production by 50%, the reconfiguration design consists of a switching network to be able to utilize any combination of cells. The design for reconfiguration must meet the power requirements of the solar array. This thesis will explore different designs for reconfiguration, as well as possible switches for implementation. It will also review other methods to increase power production, as well as discuss future work in this field.
ContributorsJohnson, Everett Hope (Author) / Kitchen, Jennifer (Thesis director) / Ozev, Sule (Committee member) / School of International Letters and Cultures (Contributor) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In this paper, we propose an autonomous throwing and catching system to be developed as a preliminary step towards the refinement of a robotic arm capable of improving strength and motor function in the limb. This will be accomplished by first autonomizing simpler movements, such as throwing a ball. In this system, an autonomous thrower will detect a desired target through the use of image processing. The launch angle and direction necessary to hit the target will then be calculated, followed by the launching of the ball. The smart catcher will then detect the ball as it is in the air, calculate its expected landing location based on its initial trajectory, and adjust its position so that the ball lands in the center of the target. The thrower will then proceed to compare the actual landing position with the position where it expected the ball to land, and adjust its calculations accordingly for the next throw. By utilizing this method of feedback, the throwing arm will be able to automatically correct itself. This means that the thrower will ideally be able to hit the target exactly in the center within a few throws, regardless of any additional uncertainty in the system. This project will focus of the controller and image processing components necessary for the autonomous throwing arm to be able to detect the position of the target at which it will be aiming, and for the smart catcher to be able to detect the position of the projectile and estimate its final landing position by tracking its current trajectory.
ContributorsLundberg, Kathie Joy (Co-author) / Thart, Amanda (Co-author) / Rodriguez, Armando (Thesis director) / Berman, Spring (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05