Combining the power of online crowdsourcing with creative writing user interfaces

The goal of this work was to provide professional and amateur writers with a new way of enhancing their productivity and mental well-being, by helping them overcoming writers block and being able to achieve a state of optimal experience while writing. Our approach is based on bringing together different components to create what we call a creative moment. A creative moment is composed by an image, a text, a mood, a location and a color. The color presented in the creative moment varied according to the mood that was associated to the creative moment. With the creative moments we hoped that our users could have a way to easily trigger their creativity and have a kick start in their work. The prototyping of a web crowdsourcing platform, named CreativeWall, and a Microsoft Word Add-In, that was used on the user study performed, is described and their implementations are discussed. The user study reveals that our approach does have a positive influence in the productivity of the participants when compared with another existing approach. The study also revealed that our approach can ease the process of achieving a state of optimal experience by enhancing one of the dimensions presented on the Flow Theory. At the end we present what we consider would be some possible future developments for the concept created during the development of this work.

Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)

Gaining valid answers to so-called sensitive questions is an age-old problem in survey research. Various techniques have been developed to guarantee anonymity and minimize the respondent's feelings of jeopardy. Two such techniques are the randomized response technique (RRT) and the unmatched count technique (UCT). In this study we evaluate the effectiveness of different implementations of the RRT (using a forced-response design) in a computer-assisted setting and also compare the use of the RRT to that of the UCT. The techniques are evaluated according to various quality criteria, such as the prevalence estimates they provide, the ease of their use, and respondent trust in the techniques. Our results indicate that the RRTs are problematic with respect to several domains, such as the limited trust they inspire and non-response, and that the RRT estimates are unreliable due to a strong false "no" bias, especially for the more sensitive questions. The UCT, however, performed well compared to the RRTs on all the evaluated measures. The UCT estimates also had more face validity than the RRT estimates. We conclude that the UCT is a promising alternative to RRT in self-administered surveys and that future research should be directed towards evaluating and improving the technique.

Gradient-Domain Bidirectional Path Tracing

Gradient-domain path tracing has recently been introduced as an efficient realistic image synthesis algorithm. This paper introduces a bidirectional gradient-domain sampler that outperforms traditional bidirectional path tracing often by a factor of two to five in terms of squared error at equal render time. It also improves over unidirectional gradient-domain path tracing in challenging visibility conditions, similarly as conventional bidirectional path tracing improves over its unidirectional counterpart. Our algorithm leverages a novel multiple importance sampling technique and an efficient implementation of a high-quality shift mapping suitable for bidirectional path tracing. We demonstrate the versatility of our approach in several challenging light transport scenarios.

Light sheet fluorescence microscopy for in situ cell interaction analysis in mouse lymph nodes.

Reactive lymph nodes (LNs) are sites where pMHC-loaded dendritic cells (DCs) interact with rare cognate T cells, leading to their clonal expansion. While DC interactions with T cell subsets critically shape the ensuing immune response, surprisingly little is known on their spatial orchestration at physiologically T cell low precursor frequencies. Light sheet fluorescence microscopy and one of its implementations, selective plane illumination microscopy (SPIM), is a powerful method to obtain precise spatial information of entire organs of 0.5-10mm diameter, the size range of murine LNs. Yet, its usefulness for immunological research has thus far not been comprehensively explored. Here, we have tested and defined protocols that preserve fluorescent protein function during lymphoid tissue clearing required for SPIM. Reconstructions of SPIM-generated 3D data sets revealed that calibrated numbers of adoptively transferred T cells and DCs are successfully detected at a single cell level within optically cleared murine LNs. Finally, we define parameters to quantify specific interactions between antigen-specific T cells and pMHC-bearing DCs in murine LNs. In sum, our studies describe the successful application of light sheet fluorescence microscopy to immunologically relevant tissues.

Open-Source Computerized Patient-Reported Outcomes: Case Studies Illustrating Fifteen Years of Evolution

Thesis (Master's)--University of Washington, 2016-06

Layer 2.5 Network Coding to Improve 802.11 Network Efficiency

Thesis (Master's)--University of Washington, 2016-06

L.I.F.E. Landscape: A Co-created Healing Environment for Vulnerable Maasai Youth

Thesis (Master's)--University of Washington, 2016-06

Aerogravity-assist maneuvering of a tethered satellite system

Two new implementations of a tethered satellite system to provide aeroassist during a planetary flyby are investigated. In each mission scenario the interaction of the Martian atmosphere with an aerodynamic lifting surface, which is tethered to an orbiter, is used to perturb the flight path of the system. The aerodynamic forces generated by interacting with the atmosphere augment the gravity assist provided by the planet. In the first aerogravity-assist maneuver the tethered satellite system has congruent post- and preflyby configurations. The second scenario, which is referred to as a dual-destination mission, involves the system mass being separated during the flyby. Both of these aerogravity-assist maneuvers are shown to facilitate significant, propellant-free velocity changes.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focussed recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the best choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy. (C) 2004 Elsevier B.V. All rights reserved.

Numerical methods for strong solutions of stochastic differential equations: an overview

This paper gives a review of recent progress in the design of numerical methods for computing the trajectories (sample paths) of solutions to stochastic differential equations. We give a brief survey of the area focusing on a number of application areas where approximations to strong solutions are important, with a particular focus on computational biology applications, and give the necessary analytical tools for understanding some of the important concepts associated with stochastic processes. We present the stochastic Taylor series expansion as the fundamental mechanism for constructing effective numerical methods, give general results that relate local and global order of convergence and mention the Magnus expansion as a mechanism for designing methods that preserve the underlying structure of the problem. We also present various classes of explicit and implicit methods for strong solutions, based on the underlying structure of the problem. Finally, we discuss implementation issues relating to maintaining the Brownian path, efficient simulation of stochastic integrals and variable-step-size implementations based on various types of control.

Distance measures to compare real and ideal quantum processes

With growing success in experimental implementations it is critical to identify a gold standard for quantum information processing, a single measure of distance that can be used to compare and contrast different experiments. We enumerate a set of criteria that such a distance measure must satisfy to be both experimentally and theoretically meaningful. We then assess a wide range of possible measures against these criteria, before making a recommendation as to the best measures to use in characterizing quantum information processing.

The correspondence framework for 3D surface matching algorithms

Beyond the inherent technical challenges, current research into the three dimensional surface correspondence problem is hampered by a lack of uniform terminology, an abundance of application specific algorithms, and the absence of a consistent model for comparing existing approaches and developing new ones. This paper addresses these challenges by presenting a framework for analysing, comparing, developing, and implementing surface correspondence algorithms. The framework uses five distinct stages to establish correspondence between surfaces. It is general, encompassing a wide variety of existing techniques, and flexible, facilitating the synthesis of new correspondence algorithms. This paper presents a review of existing surface correspondence algorithms, and shows how they fit into the correspondence framework. It also shows how the framework can be used to analyse and compare existing algorithms and develop new algorithms using the framework's modular structure. Six algorithms, four existing and two new, are implemented using the framework. Each implemented algorithm is used to match a number of surface pairs. Results demonstrate that the correspondence framework implementations are faithful implementations of existing algorithms, and that powerful new surface correspondence algorithms can be created. (C) 2004 Elsevier Inc. All rights reserved.

Demonstration of a simple entangling optical gate and its use in bell-state analysis

We demonstrate a new architecture for an optical entangling gate that is significantly simpler than previous realizations, using partially polarizing beam splitters so that only a single optical mode-matching condition is required. We demonstrate operation of a controlled-z gate in both continuous-wave and pulsed regimes of operation, fully characterizing it in each case using quantum process tomography. We also demonstrate a fully resolving, nondeterministic optical Bell-state analyzer based on this controlled-z gate. This new architecture is ideally suited to guided optics implementations of optical gates.

A note on the Balanced method

Recently the Balanced method was introduced as a class of quasi-implicit methods for solving stiff stochastic differential equations. We examine asymptotic and mean-square stability for several implementations of the Balanced method and give a generalized result for the mean-square stability region of any Balanced method. We also investigate the optimal implementation of the Balanced method with respect to strong convergence.

Supporting the software testing process through specification animation

Achieving consistency between a specification and its implementation is an important part of software development. In this paper, we present a method for generating passive test oracles that act as self-checking implementations. The implementation is verified using an animation tool to check that the behavior of the implementation matches the behavior of the specification. We discuss how to integrate this method into a framework developed for systematically animating specifications, which means a tester can significantly reduce testing time and effort by reusing work products from the animation. One such work product is a testgraph: a directed graph that partially models the states and transitions of the specification. Testgraphs are used to generate sequences for animation, and during testing, to execute these same sequences on the implementation.