Transport properties of continuous-time quantum walks on Sierpinski fractals

We model quantum transport, described by continuous-time quantum walks (CTQW), on deterministic Sierpinski fractals, differentiating between Sierpinski gaskets and Sierpinski carpets, along with their dual structures. The transport efficiencies are defined in terms of the exact and the average return probabilities, as well as by the mean survival probability when absorbing traps are present. In the case of gaskets, localization can be identified already for small networks (generations). For carpets, our numerical results indicate a trend towards localization, but only for relatively large structures. The comparison of gaskets and carpets further implies that, distinct from the corresponding classical continuous-time random walk, the spectral dimension does not fully determine the evolution of the CTQW.Comment: 10 pages, 6 figure

Trans Identity Management Across Social Media Platforms

Trans people use social media for identity work, including for education on trans terms and resources, connecting with trans networks, and sharing and presenting their identities. This identity work takes place over time and across platforms. In this study, interviews were conducted with 13 trans and non-binary social media users to explore how they use different social media platforms in relation to their gender identity. Reinforcing prior research, I found that social media, and the trans networks found there, had a large impact on how participants understood and expressed their identities. Beyond that, I found social media users strategically and actively manage their social media use in relation to their trans identity by taking advantage of different platforms and accounts as well as curating their networks and content.Master of ScienceInformation, School ofUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/162556/1/Buss_Justin_Final_MTOP_Thesis_20200430.pd

Platform-based design, test and fast verification flow for mixed-signal systems on chip

This research is providing methodologies to enhance the design phase from architectural space exploration and system study to verification of the whole mixed-signal system. At the beginning of the work, some innovative digital IPs have been designed to develop efficient signal conditioning for sensor systems on-chip that has been included in commercial products. After this phase, the main focus has been addressed to the creation of a re-usable and versatile test of the device after the tape-out which is close to become one of the major cost factor for ICs companies, strongly linking it to model’s test-benches to avoid re-design phases and multi-environment scenarios, producing a very effective approach to a single, fast and reliable multi-level verification environment. All these works generated different publications in scientific literature. The compound scenario concerning the development of sensor systems is presented in Chapter 1, together with an overview of the related market with a particular focus on the latest MEMS and MOEMS technology devices, and their applications in various segments. Chapter 2 introduces the state of the art for sensor interfaces: the generic sensor interface concept (based on sharing the same electronics among similar applications achieving cost saving at the expense of area and performance loss) versus the Platform Based Design methodology, which overcomes the drawbacks of the classic solution by keeping the generality at the highest design layers and customizing the platform for a target sensor achieving optimized performances. An evolution of Platform Based Design achieved by implementation into silicon of the ISIF (Intelligent Sensor InterFace) platform is therefore presented. ISIF is a highly configurable mixed-signal chip which allows designers to perform an effective design space exploration and to evaluate directly on silicon the system performances avoiding the critical and time consuming analysis required by standard platform based approach. In chapter 3 we describe the design of a smart sensor interface for conditioning next generation MOEMS. The adoption of a new, high performance and high integrated technology allow us to integrate not only a versatile platform but also a powerful ARM processor and various IPs providing the possibility to use the platform not only as a conditioning platform but also as a processing unit for the application. In this chapter a description of the various blocks is given, with a particular emphasis on the IP developed in order to grant the highest grade of flexibility with the minimum area occupation. The architectural space evaluation and the application prototyping with ISIF has enabled an effective, rapid and low risk development of a new high performance platform achieving a flexible sensor system for MEMS and MOEMS monitoring and conditioning. The platform has been design to cover very challenging test-benches, like a laser-based projector device. In this way the platform will not only be able to effectively handle the sensor but also all the system that can be built around it, reducing the needed for further electronics and resulting in an efficient test bench for the algorithm developed to drive the system. The high costs in ASIC development are mainly related to re-design phases because of missing complete top-level tests. Analog and digital parts design flows are separately verified. Starting from these considerations, in the last chapter a complete test environment for complex mixed-signal chips is presented. A semi-automatic VHDL-AMS flow to provide totally matching top-level is described and then, an evolution for fast self-checking test development for both model and real chip verification is proposed. By the introduction of a Python interface, the designer can easily perform interactive tests to cover all the features verification (e.g. calibration and trimming) into the design phase and check them all with the same environment on the real chip after the tape-out. This strategy has been tested on a consumer 3D-gyro for consumer application, in collaboration with SensorDynamics AG

Seeing the Invisible: Understanding the Implications of Social Media Invisible Responses for Well-Being and Relational Development

Large swathes of current social media scholarship monolithically treats browsing behaviors as passive behaviors, per the passive versus active behaviors approach to social media activities. Such labeling fails to capture the numerous ways that people respond to social media sharing beyond visible clicks on the platform, such as relational distancing or switching channels to respond. Moreover, understanding what people do with information seen on social media platforms and how they respond to such information is integral to theorizing the implications of using these platforms. My dissertation tackles these challenges by first proposing the concept of invisible responses to unify the diverse approaches of responding possible to social media. Specifically, I define invisible responses as reactions to social media sharing by viewers that are invisible along any of the following dimensions: (1) to the original platform, (2) to the sharer, and (3) to the viewer’s imagined audience of third parties. The dissertation presents three empirical studies to investigate the different dimensions of invisible responses. Study 1 examines viewing time and visible clicks while browsing Facebook feeds. While viewing time—a proxy for visual attention—is largely invisible, public feedback of clicks are visible to everyone. Study 1 reveals that the combination of these two types of responses, along with the amount of social content in feeds, can predict important well-being outcome, namely self-esteem. Study 2 explores how people practice self-presentation and relational maintenance in an environment where responses are invisible to third parties. These findings suggest that, given responses that are invisible to third parties, sharers feel lower self-presentational pressure. However, what remains unchanged compared to public feedback is the emphasis on the amount of attention and effort as signaling investment in a relationship. Finally, Study 3 investigates when and why people would make their reception of a social media post invisible or not to the original sharer of the post. Once again, the findings underscore that sending signals of attention and effort is meaningful for relational maintenance. Together, the studies in this dissertation illustrate the importance of invisible responses in understanding well-being and relational outcomes of social media use, as well as opening up future avenues for research. Specifically, responding to the research agenda outlined by the communication visibility theory (Treem, Leonardi, & van den Hooff, 2020), I highlight questions around the management of visibility on social media.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/162891/1/dieptl_1.pd

Designing for Lived Health: Engaging the Sociotechnical Complexity of Care Work

As healthcare is increasingly shaped by everyday interaction with data and technologies, there is a widespread interest in creating information systems that help people actively participate in managing their own health and wellness. To date, personal health technologies are largely designed as large-scale “patient-centered” systems, grounded in a biomedical model of care and clinical processes and/or commercial “self-care” technologies, that seek to facilitate individual behavior change through activities like fitness tracking. Through investigating the lived experience of chronic illness—multiple, messy, and often the site of uncomfortable dependencies—my thesis empirically and theoretically engages the limitations of such popular design narratives to address sociotechnical complexities in personal health management. My findings, drawn from people’s care practices across three distinct field sites, argue for a need to contend with lived health: the ways in which everyday health and wellness activities are connected to wider ecologies of care that include the emotional labor of family and friends, entanglements of data, machineries and bodies, localized networks of resources and expertise, and contested forms of information work. My thesis contributes to the literature of Information and Computer Science in the fields of Human-Computer Interaction and Computer-Supported Cooperative Work by offering an alternative analytical lens for designing health systems that support a wider range of people’s social and emotional needs.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146030/1/eskaziu_1.pd

Algorithms for Large Scale Problems in Eigenvalue and Svd Computations and in Big Data Applications

As ”big data” has increasing influence on our daily life and research activities, it poses significant challenges on various research areas. Some applications often demand a fast solution of large, sparse eigenvalue and singular value problems; In other applications, extracting knowledge from large-scale data requires many techniques such as statistical calculations, data mining, and high performance computing. In this dissertation, we develop efficient and robust iterative methods and software for the computation of eigenvalue and singular values. We also develop practical numerical and data mining techniques to estimate the trace of a function of a large, sparse matrix and to detect in real-time blob-filaments in fusion plasma on extremely large parallel computers. In the first work, we propose a hybrid two stage SVD method for efficiently and accurately computing a few extreme singular triplets, especially the ones corresponding to the smallest singular values. The first stage achieves fast convergence while the second achieves the final accuracy. Furthermore, we develop a high-performance preconditioned SVD software based on the proposed method on top of the state-of-the-art eigensolver PRIMME. The method can be used with or without preconditioning, on parallel computers, and is superior to other state-of-the-art SVD methods in both efficiency and robustness. In the second study, we provide insights and develop practical algorithms to accomplish efficient and accurate computation of interior eigenpairs using refined projection techniques in non-Krylov iterative methods. By analyzing different implementations of the refined projection, we propose a new hybrid method to efficiently find interior eigenpairs without compromising accuracy. Our numerical experiments illustrate the efficiency and robustness of the proposed method. In the third work, we present a novel method to estimate the trace of matrix inverse that exploits the pattern correlation between the diagonal of the inverse of the matrix and that of some approximate inverse. We leverage various sampling and fitting techniques to fit the diagonal of the approximation to that of the inverse. Our method may serve as a standalone kernel for providing a fast trace estimate or as a variance reduction method for Monte Carlo in some cases. An extensive set of experiments demonstrate the potential of our method. In the fourth study, we provide first results on applying outlier detection techniques to effectively tackle the fusion blob detection problem on extremely large parallel machines. We present a real-time region outlier detection algorithm to efficiently find and track blobs in fusion experiments and simulations. Our experiments demonstrated we can achieve linear time speedup up to 1024 MPI processes and complete blob detection in two or three milliseconds

Multiscale Experimental Approaches to Li-ion Battery Research: From Particle Analysis to Optimized Battery Design.

We approach the challenges in Li-ion battery research through multiscale experiments: a small but macro scale Li-ion battery was designed for an implantable surgical device for distraction osteogenesis, while in particle- to micro-scale, the baseline cathode materials for Li-ion batteries were investigated for their structural and electrochemical characteristics. For the optimized battery design study, we first identified the power / energy requirements for a common clinical protocol using a novel distraction device developed in parallel to its battery design, and then ran an algorithm to select a commercially available battery with minimal volume that satisfied the system demands. A polymer Li-ion battery was selected due to high power and energy densities as well as its favorable geometry. A bench-top prototype device, integrating an actuator, a control circuit, and a battery, was fabricated to test its functionality and reliability, and eventually will be ready for animal implantation studies. Particle- to micro- scale experimental studies of Li-ion insertion metal oxide cathode materials were conducted using simple forms of the baseline materials, such as thin films and dispersed single particles, aiming to understand their structural characteristics and electrochemical properties. Various characterization techniques including SEM, TEM, XRD, and AFM were used to observe external and internal microscopic morphology of primary particles from candidate cathode materials for EV applications, such as LiFePO4, Li[Ni1/3Co1/3Mn1/3]O2, and LiMn2O4. Their anisotropic and inhomogeneous nature was revealed due to the hierarchic structure consisting of crystal grains and grain boundaries. Thin film study of LiMn2O4 also showed similarly complex microstructures that were found to be determined by their fabrication conditions, including substrate material and annealing temperature. In an experimental study with single LiMn2O4 particles, we take one step toward precise modeling and control of large format cells in EV applications by generating and incorporating accurate model parameters, including diffusion coefficients from CV and PITT methods, and realistic particle geometries from AFM scanning data. Simulation of Li-ion intercalation with the implemented experimental measurements showed that LiMn2O4 particles could be under higher intercalation-induced stress due to slower diffusion and local stress concentration at the grain boundaries.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/64736/1/mdchung_1.pd

Sur la conception de solveurs linéaires hybrides pour les architectures parallèles modernes

In the context of this thesis, our focus is on numerical linear algebra, more precisely on solution of large sparse systems of linear equations. We focus on designing efficient parallel implementations of MaPHyS, an hybrid linear solver based on domain decomposition techniques. First we investigate the MPI+threads approach. In MaPHyS, the first level of parallelism arises from the independent treatment of the various subdomains. The second level is exploited thanks to the use of multi-threaded dense and sparse linear algebra kernels involved at the subdomain level. Such an hybrid implementation of an hybrid linear solver suitably matches the hierarchical structure of modern supercomputers and enables a trade-off between the numerical and parallel performances of the solver. We demonstrate the flexibility of our parallel implementation on a set of test examples. Secondly, we follow a more disruptive approach where the algorithms are described as sets of tasks with data inter-dependencies that leads to a directed acyclic graph (DAG) representation. The tasks are handled by a runtime system. We illustrate how a first task-based parallel implementation can be obtained by composing task-based parallel libraries within MPI processes throught a preliminary prototype implementation of our hybrid solver. We then show how a task-based approach fully abstracting the hardware architecture can successfully exploit a wide range of modern hardware architectures. We implemented a full task-based Conjugate Gradient algorithm and showed that the proposed approach leads to very high performance on multi-GPU, multicore and heterogeneous architectures.Dans le contexte de cette thèse, nous nous focalisons sur des algorithmes pour l’algèbre linéaire numérique, plus précisément sur la résolution de grands systèmes linéaires creux. Nous mettons au point des méthodes de parallélisation pour le solveur linéaire hybride MaPHyS. Premièrement nous considerons l'aproche MPI+threads. Dans MaPHyS, le premier niveau de parallélisme consiste au traitement indépendant des sous-domaines. Le second niveau est exploité grâce à l’utilisation de noyaux multithreadés denses et creux au sein des sous-domaines. Une telle implémentation correspond bien à la structure hiérarchique des supercalculateurs modernes et permet un compromis entre les performances numériques et parallèles du solveur. Nous démontrons la flexibilité de notre implémentation parallèle sur un ensemble de cas tests. Deuxièmement nous considérons un approche plus innovante, où les algorithmes sont décrits comme des ensembles de tâches avec des inter-dépendances, i.e., un graphe de tâches orienté sans cycle (DAG). Nous illustrons d’abord comment une première parallélisation à base de tâches peut être obtenue en composant des librairies à base de tâches au sein des processus MPI illustrer par un prototype d’implémentation préliminaire de notre solveur hybride. Nous montrons ensuite comment une approche à base de tâches abstrayant entièrement le matériel peut exploiter avec succès une large gamme d’architectures matérielles. À cet effet, nous avons implanté une version à base de tâches de l’algorithme du Gradient Conjugué et nous montrons que l’approche proposée permet d’atteindre une très haute performance sur des architectures multi-GPU, multicoeur ainsi qu’hétérogène

Designing a Wise Home: Leveraging Lightweight Dialogue, Proactive Coaching, Guided Experimentation and Mutual-learning to Support Mixed-initiative Homes --Comfort-aware Thermostats as a Case

Science fiction writers have been dreaming of homes that can understand our preferences, assist our daily chores and teach us to be healthier, more sustainable and more knowledgeable. While we are still far from achieving this dream, the recent development of mobile devices, wearable interfaces, smart home appliances, and machine learning offer unprecedented opportunities for homes to better understand our goals, preferences and contexts, as well as to facilitate our everyday tasks and decision making. These recent advancement open a new possibility to create homes beyond simple automation: they enable creation of homes to coach us to achieve our better selves. That is, homes that are not just smart, but wise as well. However, to develop a wise home, there are still two key questions: How can a wise home coach its occupants while considering their different goals and needs? How can a home integrates emerging sensors, devices and interfaces to better understand their goals, preferences and contexts in order to support coaching? To answer these two questions, in this dissertation I use residential heating and cooling control as a lens to advance the development of wiser homes. Based on the three studies conducted, this thesis provides three contributions. First, I show that we can integrate a diverse class of emerging devices, including mobile phones, smartwatches, in-home sensors and home appliances to capture important user contexts, such as individual preferences for thermal comfort. The integration of these emerging devices enables a home to better coach its occupants and potentially better support automation. Secondly, I show that mixed-initiative interaction is an effective approach in the design of a wise home, and further propose four design strategies to support mixed-initiative homes, namely, lightweight dialogue, proactive coaching, guided experimentation and mutual-learning. Finally, I demonstrate a novel system that integrates the above-mentioned strategies to support the development of wise homes, facilitating home occupants to identify actions to achieve a better balance between their comfort and savings goals.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153457/1/chuanche_1.pd