9,414 research outputs found

    An empirical study of the “prototype walkthrough”: a studio-based activity for HCI education

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    For over a century, studio-based instruction has served as an effective pedagogical model in architecture and fine arts education. Because of its design orientation, human-computer interaction (HCI) education is an excellent venue for studio-based instruction. In an HCI course, we have been exploring a studio-based learning activity called the prototype walkthrough, in which a student project team simulates its evolving user interface prototype while a student audience member acts as a test user. The audience is encouraged to ask questions and provide feedback. We have observed that prototype walkthroughs create excellent conditions for learning about user interface design. In order to better understand the educational value of the activity, we performed a content analysis of a video corpus of 16 prototype walkthroughs held in two HCI courses. We found that the prototype walkthrough discussions were dominated by relevant design issues. Moreover, mirroring the justification behavior of the expert instructor, students justified over 80 percent of their design statements and critiques, with nearly one-quarter of those justifications having a theoretical or empirical basis. Our findings suggest that PWs provide valuable opportunities for students to actively learn HCI design by participating in authentic practice, and provide insight into how such opportunities can be best promoted

    Learning 3D Navigation Protocols on Touch Interfaces with Cooperative Multi-Agent Reinforcement Learning

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    Using touch devices to navigate in virtual 3D environments such as computer assisted design (CAD) models or geographical information systems (GIS) is inherently difficult for humans, as the 3D operations have to be performed by the user on a 2D touch surface. This ill-posed problem is classically solved with a fixed and handcrafted interaction protocol, which must be learned by the user. We propose to automatically learn a new interaction protocol allowing to map a 2D user input to 3D actions in virtual environments using reinforcement learning (RL). A fundamental problem of RL methods is the vast amount of interactions often required, which are difficult to come by when humans are involved. To overcome this limitation, we make use of two collaborative agents. The first agent models the human by learning to perform the 2D finger trajectories. The second agent acts as the interaction protocol, interpreting and translating to 3D operations the 2D finger trajectories from the first agent. We restrict the learned 2D trajectories to be similar to a training set of collected human gestures by first performing state representation learning, prior to reinforcement learning. This state representation learning is addressed by projecting the gestures into a latent space learned by a variational auto encoder (VAE).Comment: 17 pages, 8 figures. Accepted at The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2019 (ECMLPKDD 2019

    A unified operator splitting approach for multi-scale fluid-particle coupling in the lattice Boltzmann method

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    A unified framework to derive discrete time-marching schemes for coupling of immersed solid and elastic objects to the lattice Boltzmann method is presented. Based on operator splitting for the discrete Boltzmann equation, second-order time-accurate schemes for the immersed boundary method, viscous force coupling and external boundary force are derived. Furthermore, a modified formulation of the external boundary force is introduced that leads to a more accurate no-slip boundary condition. The derivation also reveals that the coupling methods can be cast into a unified form, and that the immersed boundary method can be interpreted as the limit of force coupling for vanishing particle mass. In practice, the ratio between fluid and particle mass determines the strength of the force transfer in the coupling. The integration schemes formally improve the accuracy of first-order algorithms that are commonly employed when coupling immersed objects to a lattice Boltzmann fluid. It is anticipated that they will also lead to superior long-time stability in simulations of complex fluids with multiple scales

    Developing the human-computer interface for Space Station Freedom

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    For the past two years, the Human-Computer Interaction Laboratory (HCIL) at the Johnson Space Center has been involved in prototyping and prototype reviews of in support of the definition phase of the Space Station Freedom program. On the Space Station, crew members will be interacting with multi-monitor workstations where interaction with several displays at one time will be common. The HCIL has conducted several experiments to begin to address design issues for this complex system. Experiments have dealt with design of ON/OFF indicators, the movement of the cursor across multiple monitors, and the importance of various windowing capabilities for users performing multiple tasks simultaneously

    Impact of time-variant turbulence behavior on prediction for adaptive optics systems

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    For high contrast imaging systems, the time delay is one of the major limiting factors for the performance of the extreme adaptive optics (AO) sub-system and, in turn, the final contrast. The time delay is due to the finite time needed to measure the incoming disturbance and then apply the correction. By predicting the behavior of the atmospheric disturbance over the time delay we can in principle achieve a better AO performance. Atmospheric turbulence parameters which determine the wavefront phase fluctuations have time-varying behavior. We present a stochastic model for wind speed and model time-variant atmospheric turbulence effects using varying wind speed. We test a low-order, data-driven predictor, the linear minimum mean square error predictor, for a near-infrared AO system under varying conditions. Our results show varying wind can have a significant impact on the performance of wavefront prediction, preventing it from reaching optimal performance. The impact depends on the strength of the wind fluctuations with the greatest loss in expected performance being for high wind speeds.Comment: 10 pages, 8 figures; Accepted to JOSA A March 201

    Reviewing and extending the five-user assumption: A grounded procedure for interaction evaluation

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    " © ACM, 2013. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ACM Transactions on Computer-Human Interaction (TOCHI), {VOL 20, ISS 5, (November 2013)} http://doi.acm.org/10.1145/2506210 "The debate concerning how many participants represents a sufficient number for interaction testing is well-established and long-running, with prominent contributions arguing that five users provide a good benchmark when seeking to discover interaction problems. We argue that adoption of five users in this context is often done with little understanding of the basis for, or implications of, the decision. We present an analysis of relevant research to clarify the meaning of the five-user assumption and to examine the way in which the original research that suggested it has been applied. This includes its blind adoption and application in some studies, and complaints about its inadequacies in others. We argue that the five-user assumption is often misunderstood, not only in the field of Human-Computer Interaction, but also in fields such as medical device design, or in business and information applications. The analysis that we present allows us to define a systematic approach for monitoring the sample discovery likelihood, in formative and summative evaluations, and for gathering information in order to make critical decisions during the interaction testing, while respecting the aim of the evaluation and allotted budget. This approach – which we call the ‘Grounded Procedure’ – is introduced and its value argued.The MATCH programme (EPSRC Grants: EP/F063822/1 EP/G012393/1
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