Smart home inhabitants can specify trigger-condition-action rules to control the home's behavior. As the number of rules and their complexity grow, however, so does the probability of issues such as inconsistencies and redundancies. These can lead to unintended behavior, including security vulnerabilities and wasted resources, which harms the inhabitants' trust in the system. Existing approaches to handle unintended behavior typically require inhabitants to define all-encompassing, permanent solutions by modifying the rules. Although this is fitting in certain situations, some unforeseen situations might occur. We argue that the user always must have the last word to avoid unwanted behaviors, without altering the overall behavior. With FortClash, we present an approach to predict many different types of unintended behavior, and contribute four novel mechanisms to mediate them that rely on making one-time exceptions. With FortClash, inhabitants gain a new tool to deal with unintended behavior in the short-term that is compatible with existing long-term approaches such as editing rules.

Abstract Feedback and feedforward are two fundamental mechanisms that support users’ activities while interacting with computing devices. While feedback can be easily solved by providing information to the users following the triggering of an action, feedforward is much more complex as it must provide information before an action is performed. For interactive applications where making a mistake has more impact than just reduced user comfort, correct feedforward is an essential step toward correctly informed, and thus safe, usage. Our approach, Fortunettes, is a generic mechanism providing a systematic way of designing feedforward addressing both action and presentation problems. Including a feedforward mechanism significantly increases the complexity of the interactive application hardening developers’ tasks to detect and correct defects. We build upon an existing formal notation based on Petri Nets for describing the behavior of interactive applications and present an approach that allows for adding correct and consistent feedforward.

Over-the-top (OTT) streaming services like YouTube and Netflix induce massive amounts of video data, hereby putting substantial pressure on network infrastructure. This paper describes a demonstration of the object-based video (OBV) methodology that allows for the quality-variant MPEG-DASH streaming of respectively the background and foreground object(s) of a video scene. The OBV methodology is inspired by research into human visual attention and foveated compression, in that it allows to adaptively and dynamically assign bitrate to those portions of the visual scene that have the highest utility in terms of perceptual quality. Using a content corpus of interview-like video footage, the described demonstration proves the OBV methodology's potential to downsize video bitrate requirements while incurring at most marginal perceptual impact (i.e., in terms of subjective video quality). Thanks to its standards-compliant Web implementation, the OBV methodology is directly and broadly deployable without requiring capital expenditure.

Over-the-top (OTT) streaming services like YouTube and Netflix induce massive amounts of video traffic. To combat the resulting network load, this article empirically explores the use of the object-based video (OBV) methodology that allows for the quality-variant HTTP Adaptive Streaming of respectively the background and foreground object(s) of a video scene. In particular, we study two alternative video object representation methods where the first meticulously follows the object contour, while the second uses axis-aligned bounding box enclosures. We subjectively compare both techniques to traditional, frame-based video compression in the context of live action content featuring talking persons. The resulting mixed methods data shows that (i) OBV-informed users tolerate substantial background quality degradations, and (ii) at an average bitrate reduction of 14 percent, perceptual differences between respectively contour-based OBV and traditional encoding are small or even non-existing for the non-movie content in our corpus. Although our evaluation focuses on interview-like footage, our qualitative data hints that the presented results might be extrapolatable to other video genres. As such, our findings inform content owners and network operators about video bitrate saving opportunities with marginal perceptual impact.

Feedback is commonly used to explain what happened in an interface. What if questions, on the other hand, remain mostly unanswered. In this paper, we present the concept of enhanced widgets capable of visualizing their future state, which helps users to understand what will happen without committing to an action. We describe two approaches to extend GUI toolkits to support widget-level feedforward, and illustrate the usefulness of widget-level feedforward in a standardized interface to control the weather radar in commercial aircraft. In our evaluation, we found that users require less clicks to achieve tasks and are more confident about their actions when feedforward information was available. These findings suggest that widget-level feedforward is highly suitable in applications the user is unfamiliar with, or when high confidence is desirable.

Translation environments offer various translation aids to support professional translators. However, translation aids typically provide only limited justification for the translation suggestions they propose. In this paper we present Intellingo, a translation environment that explores intelligibility for translation aids, to enable more sensible usage of translation suggestions. We performed a comparative study between an intelligible version and a non-intelligible version of Intellingo. The results show that although adding intelligibility does not necessarily result in significant changes to the user experience, translators can better assess translation suggestions without a negative impact on their performance. Intelligibility is preferred by translators when the additional information it conveys benefits the translation process and when this information is not part of the translator's readily available knowledge.

We present the highlights of the now finished 4-year SCATE project. It was completed in February 2018 and funded by the Flemish Government IWT-SBO, project No. 130041.1

In this paper, we set out to find what encompasses an appropriate visual language for information presented on near-eye out-of-focus displays. These displays are positioned in a user's peripheral view, very near to the user's eyes, for example on the inside of the temples of a pair of glasses. We explored the usable display area, the role of spatial and retinal variables, and the influence of motion and interaction for such a language. Our findings show that a usable visual language can be accomplished by limiting the possible shapes and by making clever use of orientation and meaningful motion. We found that especially motion is very important to improve perception and comprehension of what is being displayed on near-eye out-of-focus displays, and that perception is further improved if direct interaction with the content is allowed.