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A literature search revealed that previous research on the Attentional Blink (AB) has not examined the role of salience in AB results. I examined how salience affects the AB through multiple forms and degrees of salience in target 1 (T1) and target 2 (T2) stimuli. When examining increased size as a form of salience, results showed a more salient T2 increased recall, attenuating the AB. A more salient T1 did not differ from the control, suggesting the salience (increased size) of T2 is an important factor in the AB, while salience (increased size) of T1 does not affect the AB. Additionally, the differences in target size (50% or 100% larger) were not significantly different, showing size differences at these intervals do not affect AB results. To further explore the lack of difference in results when T1 is larger in size, I examined dynamic stimuli used as T1. T1 stimuli were presented as looming or receding. When T1 was presented as looming or receding, the AB was attenuated (T2 recall at lag 2 was significantly greater). Additionally, T2 recall was significantly worse at lags three and four (showing a larger decrease directly following the attenuated AB). When comparing looming and receding against each other, at lag 2 (when recall accuracy at its lowest) looming increased recall significantly more than receding stimuli. This is expected to be due to the immediate attentional needs related to looming stimuli. Overall, the results showed T2 salience in the form of size significantly increases recall accuracy while T1 size salience does not affect the AB results. With that, dynamic T1 stimuli increase recall accuracy at early lags (lag 2) while it decreases recall accuracy at later lags (lags 3 and 4). This result is found when the stimuli are presented at a larger size (stimuli appearing closer), suggesting the more eminent need for attention results in greater effects on the AB.
ContributorsLafko, Stacie (Author) / Becker, Vaughn (Thesis advisor) / Branaghan, Russell (Committee member) / Gray, Robert (Committee member) / Arizona State University (Publisher)
Created2019
Description
Robotic assisted devices in gait rehabilitation have not seen penetration into clinical settings proportionate to the developments in this field. A possible reason for this is due to the development and evaluation of these devices from a predominantly engineering perspective. One way to mitigate this effect is to further include the principles of neurophysiology into the development of these systems. To further include these principles, this research proposes a method for grounded evaluation of three machine learning algorithms to gain insight on what modeling approaches are able to both replicate therapist assistance and emulate therapist strategies. The algorithms evaluated in this paper include ordinary least squares regression (OLS), gaussian process regression (GPR) and inverse reinforcement learning (IRL). The results show that grounded evaluation is able to provide evidence to support the algorithms at a higher resolution. Also, it was observed that GPR is likely the most accurate algorithm to replicate therapist assistance and to emulate therapist adaptation strategies.
ContributorsSmith, Mason Owen (Author) / Zhang, Wenlong (Thesis advisor) / Ben Amor, Hani (Committee member) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2021
Description
This dissertation studies the methods to enhance the performance of foldable robots manufactured by laminated techniques. This class of robots are unique in their manufacturing process, which involves cutting and staking up thin layers of different materials with various stiffness. While inheriting the advantages of soft robots -- low weight, affordable manufacturing cost and a fast prototyping process -- a wider range of actuators is available to these mechanisms, while modeling their behavior requires less computational cost.The fundamental question this dissertation strives to answer is how to decode and leverage the effect of material stiffness in these robots. These robots' stiffness is relatively limited due to their slender design, specifically at larger scales. While compliant robots may have inherent advantages such as being safer to work around, this low rigidity makes modeling more complex. This complexity is mostly contained in material deformation since the conventional actuators such as servo motors can be easily leveraged in these robots. As a result, when introduced to real-world environments, efficient modeling and control of these robots are more achievable than conventional soft robots.
Various approaches have been taken to design, model, and control a variety of laminate robot platforms by investigating the effect of material deformation in prototypes while they interact with their working environments. The results obtained show that data-driven approaches such as experimental identification and machine learning techniques are more reliable in modeling and control of these mechanisms. Also, machine learning techniques for training robots in non-ideal experimental setups that encounter the uncertainties of real-world environments can be leveraged to find effective gaits with high performance. Our studies on the effect of stiffness of thin, curved sheets of materials has evolved into introducing a new class of soft elements which we call Soft, Curved, Reconfigurable, Anisotropic Mechanisms (SCRAMs). Like bio-mechanical systems, SCRAMs are capable of re-configuring the stiffness of curved surfaces to enhance their performance and adaptability. Finally, the findings of this thesis show promising opportunities for foldable robots to become an alternative for conventional soft robots since they still offer similar advantages in a fraction of computational expense.
ContributorsSharifzadeh, Mohammad (Author) / Aukes, Daniel (Thesis advisor) / Sugar, Thomas (Committee member) / Zhang, Wenlong (Committee member) / Arizona State University (Publisher)
Created2021
Description
Corrosion is one of the key failure modes for stainless steel (SS) piping assets handling water resources managed by utility companies. During downtime, the costs start to incur as the field engineer procures its replacement parts. The parts may or may not be in stock depending on how old, complex, and common the part model is. As a result, water utility companies and its resilience to operate amid part failure are a strong function of the supply chain for replacement piping. Metal additive manufacturing (AM) has been widely recognized for its ability to (a) deliver small production scales, (b) address complex part geometries, (c) offer large elemental metal and alloy selections, (d) provide superior material properties. The key motive is to harvest the short lead time of metal AM to explore its use for replacement parts for legacy piping assets in utility-scale water management facilities. In this paper, the goal was to demonstrate 3D printing of stainless steel (SS) 316L parts using selective laser melting (SLM) technology. The corrosion resistance of 3D printed SS 316L was investigated using (a) Chronoamperometry (b) Cyclic Potentiodynamic Polarization (CPP) and Electrochemical Impedance Spectroscopy (EIS) and its improved resistance from wrought (conventional) part was also studied. Then the weldability of 3D printed SS 316L to wrought SS 316L was illustrated and finally, the mechanical strength of the weld and the effect of corrosion on weld strength was investigated using uniaxial tensile testing. The results show that 3D printed part compared to the wrought part has a) lower mass loss before and after corrosion, (b) higher pitting potential, and (c) higher charge transfer resistance. The tensile testing of welded dog bone specimens indicates that the 3D printed parts despite being less ductile were observed to have higher weld strength compared to the wrought part. On this basis, metal AM holds great value to be explored further for replacement piping parts owing to their better corrosion resistance and mechanical performance.
ContributorsSampath, Venkata Krishnan (Author) / Azeredo, Bruno (Thesis advisor) / Torres, Cesar (Committee member) / Mu, Bin (Committee member) / Arizona State University (Publisher)
Created2021
Description
Image segmentation is an important and challenging area of research in computer vision with various applications in medical imaging. Image segmentation refers to the process of partitioning an image into meaningful parts having similar attributes. Traditional manual segmentation approaches rely on human expertise to outline object boundaries in images which is a tedious and expensive process. In recent years, Deep Convolutional Neural Networks have demonstrated excellent performance in tasks such as detection, localization, recognition and segmentation of objects. However, these models require a large set of labeled training data which is difficult to obtain for medical images. To solve this problem, interactive segmentation techniques can be used to serve as a trade-off between fully automated and manual approaches. This allows a human expert in the loop as a form of guidance and refinement together with deep neural networks. This thesis proposes an interactive training strategy for segmentation, where a robot-user is utilized during training to mimic an actual annotator and provide corrections to the predicted masks by drawing scribbles. These scribbles are then used as supervisory signals and fed to the network; which interactively refines the segmentation map through several iterations of training. Further, the conducted experiments using various heuristic click strategies demonstrate that user interaction in the form of curves inside the organ of interest achieve optimal editing performance. Moreover, by using the popular image segmentation architectures based on U-Net as base models, segmentation performance is further improved; signifying that the accuracy gain of the interactive correction conform to the accuracy of the initial segmentation map.
ContributorsGoyal, Diksha (Author) / Liang, Jianming Dr. (Thesis advisor) / Wang, Yalin Dr. (Committee member) / Demakethepalli Venkateswara, Hemanth Kumar Dr. (Committee member) / Arizona State University (Publisher)
Created2021
Description
Granular materials demonstrate complexity in many physical attributes with various shapes and sizes, varying from several centimeters down to less than a few microns. Some materials are highly cohesive, while others are free-flowing. Despite such complexity in their physical properties, they are extremely important in industries dealing with bulk materials. Through this research, the factors affecting flowability of particulate solids and their interaction with projectiles were explored. In Part I, a novel set of characterization tools to relate various granular material properties to their flow behavior in confined and unconfined environments was investigated. Through this work, a thorough characterization study to examine the effects of particle size, particle size distribution, and moisture on bulk powder flowability were proposed. Additionally, a mathematical model to predict the flow function coefficient (FFC) was developed, based on the surface mean diameter and moisture level, which can serve as a flowability descriptor.
Part II of this research focuses on the impact dynamics of low velocity projectiles on granular media. Interaction of granular media with external foreign bodies occurs in everyday events like a human footprint on the beach. Several studies involving numerical and experimental methods have focused on the study of impact dynamics in both dry and wet granular media. However, most of the studies involving impact dynamics considered spherical projectiles under different conditions, while practical models should involve more complex, realistic shapes. Different impacting geometries with conserved density, volume, and velocity on a granular bed may experience contrasting drag forces upon penetration. This is due to the difference in the surface areas coming into contact with the granular media. In this study, a set of non-spherical geometries comprising cuboids, cylinders, hexagonal prisms and triangular prisms with constant density, volume, and impact velocities, were released onto a loosely packed, non-cohesive, dry granular bed. From these experimental results, a model to determine the penetration depth of projectiles upon impact was developed and how it is influenced by the release height and surface area of the projectiles in contact with the granular media was studied.
ContributorsVajrala, Spandana (Author) / Emady, Heather N (Thesis advisor) / Marvi, Hamidreza (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
This research focuses mainly on employing tunable materials to achieve dynamic radiative properties for spacecraft and building thermal management. A secondary objective is to investigate tunable materials for optical propulsion applications. The primary material investigated is vanadium dioxide (VO2), which is a thermochromic material with an insulator-to-metal phase transition. VO2 typically undergoes a dramatic shift in optical properties at T = 341 K, which can be reduced through a variety of techniques to a temperature more suitable for thermal control applications. A VO2-based Fabry-Perot variable emitter is designed, fabricated, characterized, and experimentally demonstrated. The designed emitter has high emissivity when the radiating surface temperature is above 345 K and low emissivity when the temperature is less than 341 K. A uniaxial transfer matrix method and Bruggeman effective medium theory are both introduced to model the anisotropic properties of the VO2 to facilitate the design of multilayer VO2-based devices. A new furnace oxidation process is developed for fabricating high quality VO2 and the resulting thin films undergo comprehensive material and optical characterizations. The corresponding measurement platform is developed to measure the temperature-dependent transmittance and reflectance of the fabricated Fabry-Perot samples. The variable heat rejection of the fabricated samples is demonstrated via bell jar and cryothermal vacuum calorimetry measurements. Thermal modeling of a spacecraft equipped with variable emittance radiators is also conducted to elucidate the requirements and the impact for thermochromic variable emittance technology.
The potential of VO2 to be used as an optical force modulating device is also investigated for spacecraft micropropulsion. The preliminary design considers a Fabry-Perot cavity with an anti-reflection coating which switches between an absorptive “off” state (for insulating VO2) and a reflective “on” state (for metallic VO2), thereby modulating the incident solar radiation pressure. The visible and near-infrared optical properties of the fabricated vanadium dioxide are examined to determine if there is a sufficient optical property shift in those regimes for a tunable device.
The potential of VO2 to be used as an optical force modulating device is also investigated for spacecraft micropropulsion. The preliminary design considers a Fabry-Perot cavity with an anti-reflection coating which switches between an absorptive “off” state (for insulating VO2) and a reflective “on” state (for metallic VO2), thereby modulating the incident solar radiation pressure. The visible and near-infrared optical properties of the fabricated vanadium dioxide are examined to determine if there is a sufficient optical property shift in those regimes for a tunable device.
ContributorsTaylor, Sydney June (Author) / Wang, Liping (Thesis advisor) / Wells, Valana (Committee member) / Yu, Hongbin (Committee member) / Wang, Robert (Committee member) / Thangavelautham, Jekanthan (Committee member) / Massina, Christopher J (Committee member) / Arizona State University (Publisher)
Created2020
Description
The first task faced by many teams endeavoring to solve complex scientific problems is to seek funding for their research venture. Often, this necessitates forming new, geographically dispersed teams of researchers from multiple disciplines. While the team science and organizational management fields have studied project teams extensively, nascent teams are underrepresented in the literature. Nonetheless, understanding proposal team dynamics is important because if left unaddressed, obstacles may persist beyond the funding decision and undermine the possibility of team successes adjunctive to funding. Participant observation of more than 100 multi-investigator proposal teams and semi-structured interviews with six leaders of multidisciplinary proposal teams identified investigator motivations for collaboration, obstacles to collaboration, and indicators of proposal team success. The motivations ranged from technical interests in the research question to a desire to have impact beyond oneself. The obstacles included inconsistent or non-existent communication protocols, unclear processes for producing and reviewing documents, ad hoc file and citation management systems, short and stressful time horizons, ambiguous decision-making procedures, and uncertainty in establishing a shared vision. While funding outcome was the most objective indicator of a proposal team’s success, other success indicators emerged, including whether the needs of the team member(s) had been met and the willingness of team members to continue collaborating. This multi-dimensional definition of success makes it possible for teams to simultaneously be considered successes and failures. As a framework to analyze and overcome obstacles, this work turned to the United States military’s command and control (C2) approach, which relies on specifying the following elements to increase an organization’s agility: patterns of interaction, distribution of information, and allocation of decision rights. To address disciplinary differences and varied motivations for collaboration, this work added a fourth element: shared meaning-making. The broader impact of this work is that by implementing a C2 framework to uncover and address obstacles, the proposal experience—from team creation, to idea generation, to document creation, to final submittal—becomes more rewarding for faculty, leading to greater job satisfaction. This in turn will change how university research enterprises create, organize, and share knowledge to solve complex problems in the post-industrial information age.
ContributorsPassantino, Laurel (Author) / Seager, Thomas P (Thesis advisor) / Cantwell, Elizabeth R (Committee member) / Johnston, Erik (Committee member) / Arizona State University (Publisher)
Created2021
Description
Two fatigue life prediction methods using the energy-based approach have been proposed. A number of approaches have been developed in the past five decades. This study reviews some common models and discusses the model that is most suitable for each different condition, no matter whether the model is designed to solve uniaxial, multiaxial, or biaxial loading paths in fatigue prediction. In addition, different loading cases such as various loading and constant loading are also discussed. These models are suitable for one or two conditions in fatigue prediction. While most of the existing models can only solve single cases, the proposed new energy-based approach not only can deal with different loading paths but is applicable for various loading cases. The first energy-based model using the linear cumulative rule is developed to calculate random loading cases. The method is developed by combining Miner’s rule and the rainflow-counting algorithm. For the second energy-based method, I propose an alternative method and develop an approach to avert the rainflow-counting algorithm. Specifically, I propose to use an energy-based model by directly using the time integration concept. In this study, first, the equivalent energy concept that can transform three-dimensional loading into an equivalent loading will be discussed. Second, the new damage propagation method modified by fatigue crack growth will be introduced to deal with cycle-based fatigue prediction. Third, the time-based concept will be implemented to determine fatigue damage under every cycle in the random loading case. The formulation will also be explained in detail. Through this new model, the fatigue life can be calculated properly in different loading cases. In addition, the proposed model is verified with experimental datasets from several published studies. The data include both uniaxial and multiaxial loading paths under constant loading and random loading cases. Finally, the discussion and conclusion based on the results, are included. Additional loading cases such as the spectrum including both elastic and plastic regions will be explored in future research.
ContributorsTien, Shih-Chuan (Author) / Liu, Yongming (Thesis advisor) / Nian, Qiong (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021
Description
The Inverted Pendulum on a Cart is a classical control theory problem that helps understand the importance of feedback control systems for a coupled plant. In this study, a custom built pendulum system is coupled with a linearly actuated cart and a control system is designed to show the stability of the pendulum. The three major objectives of this control system are to swing up the pendulum, balance the pendulum in the inverted position (i.e. $180^\circ$), and maintain the position of the cart. The input to this system is the translational force applied to the cart using the rotation of the tires. The main objective of this thesis is to design a control system that will help in balancing the pendulum while maintaining the position of the cart and implement it in a robot. The pendulum is made free rotating with the help of ball bearings and the angle of the pendulum is measured using an Inertial Measurement Unit (IMU) sensor. The cart is actuated by two Direct Current (DC) motors and the position of the cart is measured using encoders that generate pulse signals based on the wheel rotation. The control is implemented in a cascade format where an inner loop controller is used to stabilize and balance the pendulum in the inverted position and an outer loop controller is used to control the position of the cart. Both the inner loop and outer loop controllers follow the Proportional-Integral-Derivative (PID) control scheme with some modifications for the inner loop. The system is first mathematically modeled using the Newton-Euler first principles method and based on this model, a controller is designed for specific closed-loop parameters. All of this is implemented on hardware with the help of an Arduino Due microcontroller which serves as the main processing unit for the system.
ContributorsNamasivayam, Vignesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Shafique, Md. Ashfaque Bin (Committee member) / Arizona State University (Publisher)
Created2021