Abstract
Consumer High Dynamic Range (HDR) displays are appearing on the market. Capable of generating a peak luminance of up to 2,000 nits, the improved dynamic range they provide can only be perceived when viewed in a dark environment. In this paper, we present a display architecture that is capable of generating a peak luminance of 10,000 nits. We demonstrate, with a subjective evaluation, that the increased peak luminance is required to perceive a high dynamic range in bright ambient environments. Furthermore, we show that by fitting a surface through the data, we can predict the dynamic range that can be perceived from the luminance and illuminance with low error. We can also invert the prediction to estimate the required peak luminance for a particular combination of dynamic range and ambient lighting.

Abstract
High dynamic range (HDR) displays are capable of displaying a wider dynamic range of values than conventional displays. As HDR content becomes more ubiquitous, the use of these displays is likely to accelerate. As HDR displays can present a wider range of values, traditional strategies for mapping HDR content to low dynamic range (LDR) displays can be replaced with either directly displaying values, or using a simple shift mapping (exposure adjustment). The latter approach is especially important when considering ambient lighting, as content viewed in a dark environment may appear substantially different to a bright one. This paper seeks to identify an exposure value which is suitable for displaying specific HDR content on an HDR display under a range of ambient lighting levels. Based on data captured with human participants, this paper establishes user preferred exposure values for a variety of maximum display brightnesses, content and ambient lighting levels. These are then used to develop two models to predict preferred exposure. The first is based on linear regression using straightforward image statistics which require minimal computation and memory to be computed, making this method suitable to be directly used in display hardware. The second is a model based on convolutional neural networks (CNN) to learn image features which best predict exposure values. The CNN model generates better results than the first model at the cost of memory and computation time.

Abstract
Among the wide application areas that Virtual Reality (VR) can have a major impact, one is Education. However, this potential is still unexplored, and one of these gaps has to do with language learning. Listening activities, which are often only supported by audio, are thought of to be demanding area when it comes to learning a second or foreign language and so therefore an interesting area for VR to take place. This pilot study therefore presents the perceptions of foreign language teachers regarding a novel medium for delivering listening activities to their students: Virtual Reality technology. The results show that foreign language teachers are of the opinion that this technology can help motivate students and potentiate the student’s learning curve regarding the listening of a foreign or second language. © Springer Nature Switzerland AG 2019.

Abstract
There are still open questions about the effectiveness of Virtual Reality (VR) in Education when compared to conventional learning methods. This paper studies the feasibility of a VR-based learning tool and the possible differences in knowledge retention across a VR learning method and a conventional audio method, when it comes to learning a foreign language. Also, the students’ sense of presence and satisfaction were studied. For such purpose, a user study was conducted and results revealed that while presence and satisfaction were higher in Virtual Reality, the knowledge retention score remains the same across both experimental conditions. © Springer Nature Switzerland AG 2019.

Abstract
Virtual Reality is becoming more popular over the years because it allows the user to be the main actor in another environment and interact with it in real time. New interaction methods are being studied, like tangible interfaces, but there is little work done related to small distances when grabbing objects through a virtual environment. This study is important because, in our perspective, interaction in virtual reality will be at arms reach, meaning that the user will interact within very close distances (under 1 m). In this paper, the research team further evaluate distance perception using gender, the presence of avatar and height (fixed or personalised). The sample consisted of 64 participants (32 females and 32 males) evenly distributed between all four conditions (8 males and 8 females for each condition). Results revealed that gender does have an impact on small distance estimation; height does not have an impact on distance estimation; and avatar does make a difference when trying to grab a real object through the virtual environment. © Springer Nature Switzerland AG 2019.

Abstract
Distance Education (DE) still have some challenges to be considered similar to the face-to-face mode of instruction regarding the quality of learning, including the lack in promoting the sense of presence. This research investigates whether a differentiated media support, complementary to the traditional Virtual Learning Environment (VLE), composed by the integration of 3D Virtual Worlds (3DVW) and Conversational Agents, in the role of a Virtual Companions, can promote the student’s sense of presence in order to contribute with the learning process in DE. A quasi-experiment pilot study was conducted with 36 students enrolled in the Financial Management discipline from a DE formal course. A 3DVW was developed in the light of the pedagogical model of Experiential Learning, in the form of a role-play simulation. The results reveal that although the students positively evaluated the experience in the 3DVW, it did not stimulate the sense of presence as expected. However, better performance rates were diagnosed for students who had the help of the Virtual Companion. © 2019, Springer Nature Switzerland AG.