Embodying photorealistic personalized avatars that closely resemble their users has recently become technologically achievable in virtual reality (VR). While previous work highlighted several benefits of personalization, its impact on emotions, a central VR element, remains underexplored. Given their high production cost, assessing the added value of photorealistic personalized avatars is essential before their adoption as a design feature. To address this, we designed and validated (n=302) four virtual environments (VEs) that induce emotions in different quadrants of Russell’s Circumplex Model. Using these VEs, we systematically investigated the impact of avatar type (no avatar, generic avatar, personalized avatar) on perceived emotions and physiological responses (n=51). Generic avatars enhanced valence, arousal, embodiment, presence and selected physiological measures, while personalized avatars further amplified these effects and additionally increased heart rate variability, a marker of self-regulation. Our study demonstrates that photorealistic personalized avatars markedly enhance VR’s capacity to foster emotional engagement.

Freehand pointing is a fundamental gesture commonly used for cursorless interactions. Prior work in HCI often elicits the same pointing behaviour—facing the target with an outstretched dominant arm and index finger. However, freehand pointing outside of HCI shows more variability across hand pose, usage, and coordination with gaze. To understand what variability exists and how it affects pointing performance, we collected data (N = 23) using a hybrid motion capture system. To elicit a wide variety of pointing behaviours, we included different levels of user effort and attention, as well as the widest range of target placements studied. We systematically characterised and described three distinct pointing behaviours, each with three different traits, ranging from accurate stereotypical pointing observed in prior works to more casual hip fire-style pointing. Our analysis demonstrates how different pointing behaviours affect pointing performance and highlights their importance when designing interactive systems for more naturalistic freehand pointing.

Despite the growing adoption of freehand interactions in virtual reality (VR), the accessibility of default gesture implementations for individuals with upper limb motor impairments remains largely unexamined.To investigate unique accessibility challenges, we recruited adults with upper limb impairments (n=8) and a control group (n=16).We captured subjective and objective measures of impairment before participants performed common freehand interactions in VR including pinching, grasping, pressing, swiping and scrolling.Through observational analyses and semi-structured interviews, we identified usability barriers.Our findings reveal that even when gestures are functionally possible, restrictive implementations cause pain and fatigue for users with impairments.In particular, pinching -widely used in state-of-the-art systemsrelies heavily on the index finger, while both pinching and grasping are often defined by rigid performance thresholds.These factors exacerbate accessibility issues, especially when paired with the limitations of current tracking technologies.These insights highlight critical gaps in current design considerations and lay the foundation for developing more inclusive freehand interaction systems that reduce pain and better support a range of motor abilities.

Constant-and Dual-Threshold Dwell keyboards

Virtual Reality (VR) designers and researchers often need to measure emotions and presence as they evolve over time. The experience sampling method (ESM) is a common way to achieve this, however, ESM disrupts the experience and lacks granularity. We propose \tool{}, a new method for measuring subjective emotions and presence in VR, where users watch back their VR experience and retrospectively sketch a plot of their feelings. RetroSketch leaves the VR experience undisturbed and yields highly granular data, including information about salient events and qualitative descriptions of their feelings. We compared RetroSketch and ESM in a large study (n=140) using five different VR experiences over one-hour sessions. Our results show that RetroSketch and ESM measures are highly correlated with each other, as well as physiological measures indicative of emotion. The correlations are robust across different VR experiences and user demographics. They also highlight the impact of ESM on users' experience.

Healthcare artificial intelligence (HAI) robots could alleviate the current healthcare provision crisis. However, their successful deployment rests on achieving and responsibly calibrating appropriate patient trust in them. Over two user studies, we systematically investigate trust formation in and usage intentions for HAI robots. We first investigate manipulations of visual appearance in a passive observation study without healthcare-specific situational context (n=87) and then in a realistic VR scenario depicting a medical consultation with a HAI robot (n=177) that introduces such situational context (diagnosis and treatment severity). Results show that within a healthcare context, a unique combination of (i) situational (diagnosis and treatment severity), (ii) robot (perceived competence) and (iii) user characteristics (personality and attitudes) determine trust and ultimately influence usage intentions for HAI robots. Furthermore, our results emphasize the absence of HAI visual appearance effects on trust. Our findings support and inform a human centred design approach of HAI robots.

Virtual Reality (VR) holds great potential for psychomotor training, with existing applications using almost exclusively a ‘learning-by-doing’ active learning approach, despite the possible benefits of incorporating observational learning. We compared active learning (n=26) with different variations of observational learning in VR for a manual assembly task. For observational learning, we considered three levels of visual similarity between the demonstrator avatar and the user, dissimilar (n=25), minimally similar (n=26), or a self-avatar (n=25), as similarity has been shown to improve learning. Our results suggest observational learning can be effective in VR when combined with ‘hands-on’ practice and can lead to better far skill transfer to real-world contexts that differ from the training context. Furthermore, we found self-similarity in observational learning can be counterproductive when focusing on a manual task, and skills decay quickly without further training. We discuss these findings and derive design recommendations for future VR training.

There is great potential for adapting Virtual Reality (VR) exergames based on a user’s affective state. However, physical activity and VR interfere with physiological sensors, making affect recognition challenging. We conducted a study (n=72) in which users experienced four emotion inducing VR exergaming environments (happiness, sadness, stress and calmness) at three different levels of exertion (low, medium, high). We collected physiological measures through pupillometry, electrodermal activity, heart rate, and facial tracking, as well as subjective affect ratings. Our validated virtual environments, data, and analyses are openly available. We found that the level of exertion influences the way affect can be recognised, as well as affect itself. Furthermore, our results highlight the importance of data cleaning to account for environmental and interpersonal factors interfering with physiological measures. The results shed light on the relationships between physiological measures and affective states and inform design choices about sensors and data cleaning approaches for affective VR.

Co-located social gaming with players and observers talking to each other is commonplace. However, it becomes less attractive when using virtual reality (VR): while VR increases players’ presence by immersing them in a virtual world, it also shuts out their observing friends. We investigate whether extended reality (XR) can improve the observer experience by giving them agency over their viewpoint in the game and personalizing the representation they see of the player. In a user study, 24 pairs of players and observers experienced co-located VR gaming. Observers either watched the player’s gameplay on a stationary screen i) from the player’s viewpoint or ii) controlling their viewpoint with a gamepad, or on an XR-enabled mobile screen controlling their viewpoint by moving the screen iii) with the player represented as a generic game avatar or iv) a personalized avatar obtained through live player footage augmentation. Results show that giving observers agency over their viewpoint with an XR-enabled mobile screen provides substantial benefits to presence and observers’ overall experience.

Designing adaptive documents that are visually appealing across various devices and for diverse viewers is a challenging task. This is due to the wide variety of devices and different viewer requirements and preferences. Alterations to a document’s content, style, or layout often necessitate numerous adjustments, potentially leading to a complete layout redesign. We introduce FlexDoc, a framework for creating and consuming documents that seamlessly adapt to different devices, author, and viewer preferences and interactions. It eliminates the need to manually create multiple document layouts, as FlexDoc enables authors to define desired document properties using templates and employs both discrete and continuous optimization in a novel comprehensive optimization process, which leverages automatic text summarization and image carving techniques to adapt both layout and content during consumption dynamically. Further, we demonstrate FlexDoc in real-world scenarios.

VR exergaming is a promising motivational tool to incentivise exercise. We present a novel VR exergaming method called social interactive feedforward. The player competes with an 'enhanced model' of one of their friends in a real-time VR environment, showing improved performance levels in a way the player can relate to. Social interactive feedforward was tested in a cycling-based VR exergame and players competed with enhanced models of themselves, their friend, and a stranger moving at the same enhanced pace. Results show that friend-modelled social interactive feedforward improves performance and intrinsic motivation the most. This indicates that the mere association of the enhanced model with their friend results in a rapid improvement in performance and motivation which implies that social feedforward was successfully elicited by using an enhanced friend's model. This widens the application of self-modelled feedforward to a wide range of social options which enables players to also reap the benefits of socialising in addition to feedforward benefits.

Videos are commonly used to support learning of new skills, to improve existing skills, and as a source of motivation for training. Video self-modelling (VSM) is a learning technique that improves performance and motivation by showing a user a video of themselves performing a skill at a level they have not yet achieved. Traditional VSM is very data and labour intensive: a lot of video footage needs to be collected and manually edited in order to create an effective self-modelling video. We address this by presenting FakeForward – a method which uses deepfakes to create self-modelling videos from videos of other people. FakeForward turns videos of better-performing people into effective, personalised training tools by replacing their face with the user’s. We investigate how FakeForward can be effectively applied and demonstrate its efficacy in rapidly improving performance in physical exercises, as well as confidence and perceived competence in public speaking.

Virtual environments can support psychomotor learning by allowing learners to observe instructor avatars. Instructor avatars that look like the learner hold promise in enhancing learning; however, it is unclear whether this works for psychomotor tasks and how similar avatars need to be. We investigated ‘minimal’ customisation of instructor avatars, approximating a learner’s appearance by matching only key visual features: gender, skin-tone, and hair colour. These avatars can be created easily and avoid problems of highly similar avatars. Using modern dancing as a skill to learn, we compared the effects of visually similar and dissimilar avatars, considering both learning on a screen (n=59) and in VR (n=38). Our results indicate that minimal avatar customisation leads to significantly more vivid visual imagery of the dance moves than dissimilar avatars. We analyse variables affecting interindividual differences, discuss the results in relation to theory, and derive design implications for psychomotor training in virtual environments.

Presence is one of the most studied and most important variables in immersive virtual reality (VR) and it influences the effectiveness of many VR applications. Separate bodies of research indicate that presence is determined by (1) technical factors such as the visual realism of a virtual environment (VE) and the field of view (FoV), and (2) human factors such as emotions and agency. However, it remains unknown how technical and human factors may interact in the presence formation process. We conducted a user study (n=360) to investigate the effects of visual realism (high/low), FoV (high/low), emotions (focusing on fear) and agency (yes/no) on presence. Counter to previous assumptions, technical factors did not affect presence directly but were moderated through human factors. We propose TAP-Fear, a structural equation model that describes how design decisions, technical factors and human factors combine and interact in the formation of presence.

Personality characteristics can affect how much presence an individual experiences in virtual reality, and researchers have explored how it may be possible to prime users to increase their sense of presence. A personality characteristic that has yet to be explored in the VR literature is imaginative suggestibility, the ability of an individual to successfully experience an imaginary scenario as if it were real. In this paper, we explore how suggestibility and priming affect presence when consulting an ancient oracle in VR as part of an educational experience – a common VR application. We show for the first time how imaginative suggestibility is a major factor which affects presence and emotions experienced in VR, while priming cues have no effect on participants’ (n=128) user experience, contrasting results from prior work. We consider the impacts of these findings for VR design and provide guidelines based on our results.

While using VR, efficient text entry is a challenge: users cannot easily locate standard physical keyboards, and keys are often out of reach, e.g. when standing. We present TapGazer, a text entry system where users type by tapping their fingers in place. Users can tap anywhere as long as the identity of each tapping finger can be detected with sensors. Ambiguity between different possible input words is resolved by selecting target words with gaze. If gaze tracking is unavailable, ambiguity is resolved by selecting target words with additional taps. We evaluated TapGazer for seated and standing VR: seated novice users using touchpads as tap surfaces reached 44.81 words per minute (WPM), 79.17% of their QWERTY typing speed. Standing novice users tapped on their thighs with touch-sensitive gloves, reaching 45.26 WPM (71.91%). We analyze TapGazer with a theoretical performance model and discuss its potential for text input in future AR scenarios.

Street harassment is a widespread problem that can constrain people’s freedom to enjoy public spaces safely, along with many other negative psychological impacts. However, very little research has looked at how immersive technology can help in addressing it. We conducted three studies to investigate the design decisions, ethical issues and efficacy of an immersive simulation of street harassment: an online design study (n=20), an interview study with experts working in the area (n=9), and a comparative lab study investigating design, ethics and efficacy (n=44). Our results deepen understanding of the design decisions that contribute to a realistic psychological experience, such as the effects of screen-based video vs passive VR vs interactive VR. They also highlight important ethical issues such as traumatisation and potential for victim blaming, and how they can be approached in an ethical manner. Finally, they provide insights into efficacy in terms of perceived usefulness, competence and empathy.

Reverse engineering (RE) of user interfaces (UIs) plays an important role in software evolution. However, the large diversity of UI technologies and the need for UIs to be resizable make this challenging. We propose ReverseORC, a novel RE approach able to discover diverse layout types and their dynamic resizing behaviours independently of their implementation, and to specify them by using OR constraints. Unlike previous RE approaches, ReverseORC infers flexible layout constraint specifications by sampling UIs at different sizes and analyzing the differences between them. It can create specifications that replicate even some non-standard layout managers with complex dynamic layout behaviours. We demonstrate that ReverseORC works across different platforms with very different layout approaches, e.g., for GUIs as well as for the Web. Furthermore, it can be used to detect and fix problems in legacy UIs, extend UIs with enhanced layout behaviours, and support the creation of flexible UI layouts.

Arguably one of the most important characteristics of virtual reality (VR) is its ability to induce higher feelings of presence. Still, research has remained inconclusive on how presence is affected by human factors such as emotion and agency. Here we adopt a novel design to investigate their effects by testing virtual environments inducing either happiness or fear, with or without user agency. Results from 121 participants showed that the dominant emotion induced by a virtual environment is positively correlated with presence. In addition, agency had a significant positive effect on presence and, furthermore, moderated the effect of emotion on presence. We show for the first time that the effects of emotion and agency on presence are not straightforward but they can be modelled by separating design factors from subjective measures. We discuss how these findings can explain seemingly conflicting results of related work and their implications for VR design.

Older adults can benefit from technologies that help them to complete everyday tasks. However, they are an often-under-represented population in augmented reality (AR) research. We present the results of a study in which people aged 50 years or older were asked to perform actions by interpreting visual AR prompts in a lab setting. Our results show that users were less successful at completing actions when using ARROW and HIGHLIGHT augmentations than when using ghosted OBJECT or GHOSTHAND augmentations. We found that user confidence in performing actions varied according to action and augmentation type. Users preferred combined AUDIO+TEXT prompts (our control condition) overall, but the GHOSTHAND was the most preferred visual prompt. We discuss reasons for these differences and provide insight for developers of AR content for older adults. Our work provides the first comparative study of AR with older adults in a non-industrial context.

We introduce a new neural network architecture that we call "grid-functioned" neural networks. It utilises a grid structure of network parameterisations that can be specialised for different subdomains of the problem, while maintaining smooth, continuous behaviour. The grid gives the user flexibility to prevent gross features from overshadowing important minor ones. We present a full characterisation of its computational and spatial complexity, and demonstrate its potential, compared to a traditional architecture, over a set of synthetic regression problems. We further illustrate the benefits through a real-world 3D skeletal animation case study, where it offers the same visual quality as a state-of-the-art model, but with lower computational complexity and better control accuracy.

Visual camera localization using offline maps is widespread in robotics and mobile applications. Most state-of-the-art localization approaches assume static scenes, so maps are often reconstructed once and then kept constant. However, many scenes are dynamic and as changes in the scene happen, future localization attempts may struggle or fail entirely. Therefore, it is important for successful long-term localization to update and maintain maps as new observations of the scene, and changes in it, arrive. We propose a novel method for automatically discovering which points in a map remain stable over time, and which are due to transient changes. To this end, we calculate a stability store for each point based on its visibility over time, weighted by an exponential decay over time. This allows us to consider the impact of time when scoring points, and to distinguish which points are useful for long-term localization. We evaluate our method on the CMU Extended Seasons dataset (outdoors) and a new indoor dataset of a retail shop, and show the benefit of maintaining a `live map' that integrates updates over time using our exponential decay based method over a static `base map'.

OR-constrained (ORC) graphical user interface layouts unify conventional constraint-based layouts with flow layouts, which enables the definition of flexible layouts that adapt to screens with different sizes, orientations, or aspect ratios with only a single layout specification. Unfortunately, solving ORC layouts with current solvers is time-consuming and the needed time increases exponentially with the number of widgets and constraints. To address this challenge, we propose ORCSolver, a novel solving technique for adaptive ORC layouts, based on a branch-and-bound approach with heuristic preprocessing. We demonstrate that ORCSolver simplifies ORC specifications at runtime and our approach can solve ORC layout specifications efficiently at near-interactive rates.

User experience estimation of VR exergame players by recognising their affective state could enable us to personalise and optimise their experience. Affect recognition based on psychophysiological measurements has been successful for moderate intensity activities. High intensity VR exergames pose challenges as the effects of exercise and VR headsets interfere with those measurements. We present two experiments that investigate the use of different sensors for affect recognition in a VR exergame. The first experiment compares the impact of physical exertion and gamification on psychophysiological measurements during rest, conventional exercise, VR exergaming, and sedentary VR gaming. The second experiment compares underwhelming, overwhelming and optimal VR exergaming scenarios. We identify gaze fixations, eye blinks, pupil diameter and skin conductivity as psychophysiological measures suitable for affect recognition in VR exergaming and analyse their utility in determining affective valence and arousal. Our findings provide guidelines for researchers of affective VR exergames.

VR games offer new freedom for players to interact naturally using motion. This makes it harder to design games that react to player motions convincingly. We present a framework for VR sword fighting experiences against a virtual character that simplifies the necessary technical work to achieve a convincing simulation. The framework facilitates VR design by abstracting from difficult details on the lower "physical" level of interaction, using data-driven models to automate both the identification of user actions and the synthesis of character animations. Designers are able to specify the character's behaviour on a higher "semantic" level using parameterised building blocks, which allow for control over the experience while minimising manual development work. We conducted a technical evaluation, a questionnaire study and an interactive user study. Our results suggest that the framework produces more realistic and engaging interactions than simple hand-crafted interaction logic, while supporting a controllable and understandable behaviour design.

Customised avatars are a powerful tool to increase identification, engagement and intrinsic motivation in digital games. We investigated the effects of customisation in a self-competitive VR exergame by modelling players and their previous performance in the game with customised avatars. In a first study we found that, similar to non-exertion games, customisation significantly increased identification and intrinsic motivation, as well as physical performance in the exergame. In a second study we identified a more complex relationship with the customisation style: idealised avatars increased wishful identification but decreased exergame performance compared to realistic avatars. In a third study, we found that 'enhancing' realistic avatars with idealised characteristics increased wishful identification, but did not have any adverse effects. We discuss the findings based on feedforward and self-determination theory, proposing notions of intrinsic identification (fostering a sense of self) and extrinsic identification (drawing away from the self) to explain the results.

Participating in competitive races can be a thrilling experience for athletes, involving a rush of excitement and sensations of flow, achievement, and self-fulfilment. However, for non-athletes, the prospect of competition is often a scary one which affects intrinsic motivation negatively, especially for less fit, less competitive individuals. We propose a novel method making the positive racing experience accessible to non-athletes using a high-intensity cycling VR exergame: by recording and replaying all their previous gameplay sessions simultaneously, including a projected future performance, players can race against a crowd of "ghost" avatars representing their individual fitness journey. The experience stays relevant and exciting as every race adds a new competitor. A longitudinal study over four weeks and a cross-sectional study found that the new method improves physical performance, intrinsic motivation, and flow compared to a non-competitive exergame. Additionally, the longitudinal study provides insights into the longer-term effects of VR exergames.

Spreadsheets are one of the most widely used data management tools. Although intuitive and easy to use, they suffer from a number of issues. Numerous publications indicate that most spreadsheets contain errors and that spreadsheet-based data shadow systems lead to problems such as the “spreadmart dilemma” creating inconsistent views on organizational data. In this paper, we describe “ The Semantic Spreadsheet ”, a new data model for a semantically accurate spreadsheet system. Unlike the existing data models, the described model is a presentation independent data model based on the Resource Description Framework (RDF) that avoids the spreadmart dilemma by providing a semantically sound data structure. We describe the set-theoretic and relational algebraic operations on the data model and show how it can improve data integrity.

Human performance augmentation through technology has been a recurring theme in science and culture, aiming to increase human capabilities and accessibility. We investigate a related concept: virtual performance augmentation (VPA), using VR to give users the illusion of greater capabilities than they actually have. We propose a method for VPA of running and jumping, based on in place movements, and studied its effects in a VR exergame. We found that in place running and jumping in VR can be used to create a somewhat natural experience and can elicit medium to high physical exertion in an immersive and intrinsically motivating manner. We also found that virtually augmenting running and jumping can increase intrinsic motivation, perceived competence and flow, and may also increase motivation for physical activity in general. We discuss implications of VPA for safety and accessibility, with initial evidence suggesting that VPA may help users with physical impairments enjoy the benefits of exergaming.

We propose a novel approach for constraint-based graphical user interface (GUI) layout based on OR-constraints (ORC) in standard soft/hard linear constraint systems. ORC layout unifies grid layout and flow layout, supporting both their features as well as cases where grid and flow layouts individually fail. We describe ORC design patterns that enable designers to safely create flexible layouts that work across different screen sizes and orientations. We also present the ORC Editor, a GUI editor that enables designers to apply ORC in a safe and effective manner, mixing grid, flow and new ORC layout features as appropriate. We demonstrate that our prototype can adapt layouts to screens with different aspect ratios with only a single layout specification, easing the burden of GUI maintenance. Finally, we show that ORC specifications can be modified interactively and solved efficiently at runtime.

Navigating source code, an activity common in software development, is time consuming and in need of improvement. We present CodeGazer, a prototype for source code navigation using eye gaze for common navigation functions. These functions include actions such as "Go to Definition'' and "Find All Usages'' of an identifier, navigate to files and methods, move back and forth between visited points in code and scrolling. We present user study results showing that many users liked and even preferred the gaze-based navigation, in particular the "Go to Definition'' function. Gaze-based navigation is also holding up well in completion time when compared to traditional methods. We discuss how eye gaze can be integrated into traditional mouse & keyboard applications in order to make "look up'' tasks more natural.

When a user needs to reposition the cursor during text editing, this is often done using the mouse. For experienced typists especially, the switch between keyboard and mouse can slow down the keyboard editing workflow considerably. To address this we propose ReType, a new gaze-assisted positioning technique combining keyboard with gaze input based on a new 'patching' metaphor. ReType allows users to perform some common editing operations while keeping their hands on the keyboard. We present the result of two studies. A free-use study indicated that ReType enhances the user experience of text editing. ReType was liked by many participants, regardless of their typing skills. A comparative user study showed that ReType is able to match or even beat the speed of mouse-based interaction for small text edits. We conclude that the gaze-augmented user interface can make common interactions more fluent, especially for professional keyboard users.

Exergames commonly use low to moderate intensity exercise protocols. Their effectiveness in implementing high intensity protocols remains uncertain. We propose a method for improving performance while maintaining intrinsic motivation in high intensity VR exergaming. Our method is based on an interactive adaptation of the feedforward method: a psychophysical training technique achieving rapid improvement in performance by exposing participants to self models showing previously unachieved performance levels. We evaluated our method in a cycling-based exergame. Participants competed against (i) a self model which represented their previous speed; (ii) a self model representing their previous speed but increased resistance therefore requiring higher performance to keep up; or (iii) a virtual competitor at the same two levels of performance. We varied participants' awareness of these differences. Interactive feedforward led to improved performance while maintaining intrinsic motivation even when participants were aware of the interventions, and was superior to competing against a virtual competitor.

Program analysis is the process of gathering deeper insights about a source code and analysing them to resolve software problems of arbitrary complexity. The key challenge in program analysis is to keep it fast, precise and straightforward. This research focuses on three key objectives to achieve an efficient program analysis: (i) expressive data representation, (ii) optimised data structure and (iii) fast data processing mechanisms. State of the art technologies such as Resource Description Framework (RDF) as data representation format, triplestores as the storage & processing layer, and datalog to represent program analysis rules are considered in our research. diagram(BDD) to be embedded in the triplestore. Additionally, an ontology is being designed to standardise the definitions of concepts and representation of the knowledge in the program analysis domain.

Semi-stream join algorithms join a continuous stream with a large disk-based relation. While there are efficient semi-stream equijoins for exact matches in the joined data, there are currently no semi-stream similarity joins for approximate matches. The existing similarity join algorithms work either offline (on datasets that are fully known) or on several streams (using a join window), and are less suitable for applications where continuous, immediate and complete similarity join results are required. To address this gap we propose S3J, the first semi-stream similarity join algorithm. To utilize disk and CPU optimally, S3J combines a disk-intensive queue-based semi-stream join approach with a CPU-intensive similarity matching algorithm. The similarity matching algorithm is based on tries to minimize the memory footprint. Moreover, it supports parallel execution to utilize modern multicore CPUs. We provide a cost model for S3J and evaluate its performance empirically.

OAuth has become a widespread authorization protocol to allow inter-enterprise sharing of user preferences and data: a Consumer that wants access to a user's protected resources held by a Service Provider can use OAuth to ask for the user's authorization for access to these resources. However, it can be tedious for a Consumer to use OAuth as a way to organize user identities, since doing so requires supporting all Service Providers that the Consumer would recognize as users' "identity providers". Each Service Provider added requires extra work, at the very least, registration at that Service Provider. Different Service Providers may differ slightly in the API they offer, their authentication/authorization process or even their supported version of OAuth. The use of different OAuth Service Providers also creates privacy, security and integration problems. Therefore OAuth is an ideal candidate for Software as a Service, while posing interesting challenges at the same time. We use conceptual modelling to derive new high-level models and provide an analysis of the solution space. We address the aforementioned problems by introducing a trusted intermediary -- OAuth Hub -- into this relationship and contrast it with a variant, OAuth Proxy. Instead of having to support and control different OAuth providers, Consumers can use OAuth Hub as a single trusted intermediary to take care of managing and controlling how authentication is done and what data is shared. OAuth Hub eases development and integration issues by providing a consolidated API for a range of services. We describe how a trusted intermediary such as OAuth Hub can fit into the overall OAuth architecture and discuss how it can satisfy demands on security, reliability and usability.

Whilst Model Based Testing (MBT) is an improvement over manual test specification, the leap from it to MBT can be hard. Only recently MBT tools for Web applications have emerged that can recover models from existing manually specified test cases. However, there are further requirements for supporting both MBT and manually specified tests. First, we need support for the generation of test initialization procedures. Also, we want to identify areas of the system that are not testable due to defects. We present Form Tester, a new MBT tool addressing these limitations. An evaluation with real Web applications shows that Form Tester helps to reduce the time spent on developing test cases.

Eye gaze tracking is a promising input method which is gradually finding its way into the mainstream. An obvious question to arise is whether it can be used for point-and-click tasks, as an alternative for mouse or touch. Pointing with gaze is both fast and natural, although its accuracy is limited. There are still technical challenges with gaze tracking, as well as inherent physiological limitations. Furthermore, providing an alternative to clicking is challenging.

Recently, a number of semi-stream join algorithms have been published. The typical system setup for these consists of one fast stream input that has to be joined with a disk-based relation R. These semi-stream join approaches typically perform the join with a limited main memory partition assigned to them, which is generally not large enough to hold the whole relation R. We propose a caching approach that can be used as a front-stage for different semi-stream join algorithms, resulting in significant performance gains for common applications. We analyze our approach in the context of a seminal semi-stream join, MESHJOIN (Mesh Join), and provide a cost model for the resulting semi-stream join algorithm, which we call CMESHJOIN (Cached Mesh Join). The algorithm takes advantage of skewed distributions; this article presents results for Zipfian distributions of the type that appears in many applications.

The increasing cost of healthcare represents a serious challenge to most developed countries. Telehealth has been widely promoted as a technology to make healthcare more effective and affordable. However, current telehealth systems suffer from vendor lock-in and high cost, and are designed for managing chronic diseases, rather than preventing them. In this paper we evaluate technologies for supporting senior health consumers. Based on this we propose a framework for a novel telehealth system overcoming many of the shortcomings of existing technologies. The new system is web-based, has a Facebook-like plug-in architecture for adding new health applications, and incorporates social networking functionalities. We discuss the challenges in implementing the system, and summarize a user study evaluating the system. Our results demonstrate that health consumers have a positive view of this new telehealth technology, and that it can positively change the attitude of users towards their health.

An increasing number of applications require 3D content. However, its creation from real-world data either necessitates expensive equipment, artistic skills, or is constrained, for example, by the range of the utilized sensors. Image-based modeling is rapidly increasing in popularity since cameras are very affordable, widely available, and have a wide image acquisition range suitable for objects of vastly different size. The technique is especially suitable for mobile robotics involving low cost equipment and robots with a light payload, for example, small UAVs. In this paper we describe a novel image-based modeling system, which produces high-quality 3D content automatically from a collection of unconstrained and uncalibrated 2D images. The system estimates camera parameters and a 3D scene geometry using Structure-from-Motion (SfM) and Bundle Adjustment techniques. The point cloud density of 3D scene components is enhanced by exploiting silhouette information of the scene. This hybrid approach dramatically improves the reconstruction of objects with few visual features, for example, unicolored objects, and improves surface smoothness. A high quality texture is created by parameterizing the reconstructed objects using a segmentation and charting approach which also works for objects which are not homeomorphic to a sphere. The resulting parameter space contains one chart for each surface segment. A texture map is created by back projecting the best fitting input images onto each surface segment, and smoothly fusing them together over the corresponding chart by using graph-cut techniques.

The Kaczmarz method is an iterative method for solving large systems of equations that projects iterates orthogonally onto the solution space of each equation. In contrast to direct methods such as Gaussian elimination or QR-factorization, this algorithm is efficient for problems with sparse matrices, as they appear in constraint-based user interface (UI) layout specifications. However, the Kaczmarz method as described in the literature has its limitations: it considers only equality constraints and does not support soft constraints, which makes it inapplicable to the UI layout problem. In this paper we extend the Kaczmarz method for solving specifications containing soft constraints, using the prioritized IIS detection algorithm. Furthermore, the performance and convergence of the proposed algorithms are evaluated empirically using randomly generated UI layout specifications of various sizes. The results show that these methods offer improvements in performance over standard methods like Matlab's LINPROG, a well-known efficient linear programming solver.

Layout managers are used to control the placement of widgets in graphical user interfaces (GUIs). Constraint-based layout managers are among the most powerful. However, they are also more complex and their layouts are prone to problems such as over-constrained specifications and widget overlap. This poses challenges for GUI builder tools, which ideally should address these issues automatically. We present a new GUI builderthe Auckland Layout Editor (ALE)that addresses these challenges by enabling GUI designers to specify constraint-based layouts using simple, mouse-based operations. We give a detailed description of ALE's edit operations, which do not require direct constraint editing. ALE guarantees that all edit operations lead to sound specifications, ensuring solvable and non-overlapping layouts. To achieve that, we present a new algorithm that automatically generates the constraints necessary to keep a layout non-overlapping. Furthermore, we discuss how our innovations can be combined with manual constraint editing in a sound way. Finally, to aid designers in creating layouts with good resize behavior, we propose a novel automatic layout preview. This displays the layout at its minimum and in an enlarged size, which allows visualizing potential resize issues directly. All these features permit GUI developers to focus more on the overall UI design.

Linear relaxation is a common method for solving linear problems as they occur in science and engineering. In contrast to direct methods such as Gauss-elimination or QR-factorization, linear relaxation is inherently efficient for problems with sparse matrices as they are often encountered, for instance, in the application domain of constraint-based UI layout. However, the linear relaxation method as described in the literature has its limitations: it works only with square matrices and does not support soft constraints, which makes it inapplicable to the UI layout problem. In this paper we extend linear relaxation to non-square matrices and soft constraints, and identify pivot assignment as the major issue to overcome in this process. We propose two algorithms for pivot assignment: random pivot assignment, and a more complex deterministic pivot assignment algorithm. Compared to the standard pivot assignment, which selects the elements on the diagonal of the problem matrix as pivot elements, these algorithms make the solving process more robust and make it possible to solve non-square matrices. Furthermore, we propose two algorithms for solving specifications containing soft constraints: constraint insertion and constraint removal. With these algorithms, it is possible to prioritize constraints. That is, if there are conflicting constraints in a specification as is commonly the case for UI layout, only the constraints with lower priority are violated to resolve the conflict. The performance and convergence of the proposed algorithms are evaluated empirically using randomly generated UI layout specifications of various sizes. The results show that our best linear relaxation algorithm performs significantly better than that of LP-Solve, which is a well-known efficient linear programming solver, and QR-decomposition.

Designing healthcare systems for the elderly is a challenging endeavour. Telehealth systems are gaining popularity among elderly users, but such applications are mostly doctor-centric and are predominantly used for managing and/or treating diseases instead of preventing them. They do little to motivate patients to change their lifestyle and proactively manage their health. To address these shortcomings, we propose a web-based telehealth system, which uses Web 2.0 technologies in order to add social support and user defined content. In this study, we determine the functional and interface requirements of the system by conducting open individual semi-structured interviews with eight elderly people of age range 60 to 87. A paper prototype and three interfaces of existing Web 2.0 health applications were used to determine the optimum user interface design of the system. A qualitative content analysis was used to evaluate the responses. Overall, the respondents were positive about the idea of using the web to manage their healthcare from home and made several suggestions such as including applications to manage their diet, physiotherapy exercises to improve their health conditions and simple network games to reduce loneliness.

Single sign-on (SSO) protocols allow one person to use the same login credentials for several organizations. Enterprises face increasing competitive pressure to position themselves with regard to SSO, yet the ramifications of a move to SSO are not fully understood. In this paper we discuss OpenID, a relatively new SSO protocol that is gaining traction on the web. We apply enterprise application modelling techniques to OpenID in order to obtain well-founded decision aids for enterprises: we show how published modelling approaches can be used to analyse risks in OpenID, and show that these can identify security problems with common OpenID practice. Finally, we propose analysis principles that condense important general insights of authentication modelling.

This report details the attempt to form a complete workflow model for an ICT company in order to achieve a Capability Maturity Model Integration (CMMI) maturity rating of three. During this project, business processes across the company's core and auxiliary sectors were documented and extended using modern enterprise modeling tools and a The Open Group Architectural Framework (TOGAF) methodology. Different challenges were encountered with regard to process customization and tool support for enterprise modeling. In particular, there were problems with the reuse of process models, the integration of different project management methodologies and the integration of the Rational Unified Process (RUP) development process framework that had to be solved. We report on these challenges and point out research directions that could help to improve the situation in the future.

Load testing of Web applications can be specified by simulating realistic user behavior with stochastic form-oriented analysis models. Stochastic models have advantages over load test models that simply play back recorded session data: they are easier to specify and achieve a higher coverage of the different operational paths. There are challenges when specifying load tests such as the generation of form parameters and the recognition of pages returned by the system. We propose how these challenges can be overcome by adding additional specifications to a form-oriented model. Furthermore, we discuss several workload models and explain why some commonly used workload models are in fact unrealistic and produce misleading results. The stochastic form-oriented load testing approach can be generalized to deal with other submit-response systems such as those consisting of Web services.

GUIDs are globally unique identifiers that can be generated independently. They play an important role in many distributed systems. However, compared to most local identifiers, they are relatively large (16 bytes). We discuss techniques that can make the use of GUIDs more efficient, so that they become more viable as a ubiquitous solution for large distributed databases and similar applications relying on artificial identifiers. The proposed techniques include canonical GUIDs for primitive values and a compression scheme for timestamp-based GUIDs. The techniques have been implemented and can be used in different programming languages. Furthermore, general aspects and potential problems of GUIDs as defined in the RFC 4122 are discussed.