This paper presents the use of a simulation environment as an accurate, ethical, and sustainable alternative to testing robotic prototypes in animal models and simplified phantom models, specifically developed for robotic colonoscopy devices inside the human colon. A virtual simulation of the locomotion mechanism of a prototype robotic colonoscope and the colon was created in Ansys, and robot/colon experiments were conducted on different colon surfaces to validate simulation results. The successfully simulated propulsion force generated by the prototype produced an RMSE of 7% when compared at the optimal operating condition of the device, and 25-30% when compared to a full range of device velocities. The larger RMSE is due to physical phenomena that were not present in the simulation due to the constraints applied. The simulation, however, allowed evaluation of difficult quantities to measure in a real world setting such as the normal interaction force between the device and tissue wall, and stress distribution across the locomotion mechanism, as well as a phenomenon of oscillating propulsion force resulting from the device design. This work demonstrates feasibility of using finite element simulation to shape the design and optimization of a robotic colonoscope and understands its interaction with complex human anatomy.

Recommender systems are increasingly employed by journalistic outlets to deliver personalised news, transforming news curation into a reciprocal yet insufficiently defined process influenced by editors, recommender systems, and individual user actions. To understand the tension in this dynamic and users’ preferences and perceptions of their role in personalised news curation, we conducted a study with UK participants aged 16-34. Building on a preliminary survey and interview study, which revealed a strong desire from participants for increased agency in personalisation, we designed an interactive news recommender provotype (provocative design artefact) which probed the role of agency in news curation with participants (n=16). Findings highlighted a behaviour-intention gap, indicating participants desire for agency yet reluctance to intervene actively in personalisation. Our research offers valuable insights into how users perceive their agency in personalised news curation, underscoring the importance for systems to be designed to support individuals becoming active agents in news personalisation.

Binge-watching is of academic interest, not least for the potential links between ‘excessive’ media consumption and wellbeing. This study analyses binge-watching behaviours relating to ‘The Traitors US’ using BBC iPlayer viewing data and Twitter discourse. Findings show viewing engagement increased as the finale approached, with some consumers watching over nine hours of content in one day. Twitter sentiment analysis includes themes of excitement, compulsion, and concern for spoilers. As binge-watching proliferates globally, big data analysis of real-world data may offer valuable insights into viewers’ motivations and the binge-watching phenomenon.

The increase of disinformation in scientific news across a variety of domains has generated an urgency for a robust and generalizable approach to automated scientific claim verification (SCV). Available methods of SCV are limited in either domain adaptability or scalability. To facilitate building and evaluating more robust models on SCV we propose MSVEC, a multidomain dataset containing 200 pairs of verified scientific news claims with evidence research papers. To understand the capability of large language models on the SCV task, we evaluated GPT-3.5 against MSVEC. While methods of fact-checking exist for specific domains (e.g., political and health), the use of large language models exhibits better generalizability across multiple domains and is potentially compared with state-of-the-art models based on word embeddings. The data and software used and developed for this project are available at https://github.com/lamps-lab/msvec.

From the landing page of a shopping website, to a tailored layout on a video streaming app, digital media experiences are becoming increasingly personalised, and none of us have the same experience as each other. We report on a series of in-depth interviews, with UK media users from 19 to 68 years old, exploring their awareness, feelings, expectations and concerns about the digital media being personalised ’for them’, and the language that they use when talking about it. Our repeatable, extensible methodology develops insights aligned to a framework of fundamental human values.

Certified orientation and mobility specialists (COMS) work with clients who are blind or visually impaired (BVI) to help them travel independently with confidence. Part of this process involves creating a narrative description of a route and using specific techniques to help the client internalize it. We focus on the problem of automatically generating a narrative description of an indoor route based on a recording from a smartphone. These automatically generated narrations could be used in cases where a COMS is not available or to enable clients to independently practice routes that were originally learned with the help of a COMS. Specifically, we introduce Clew3D, a mobile app that leverages LIDAR-equipped iOS devices to identify orientation and mobility (O&M) landmarks and their relative location along a recorded route. The identified landmarks are then used to provide a spoken narration modeled after traditional O&M techniques. Our solution is co-designed with COMS and uses methods and language that they employ when creating route narrations for their clients. In addition to presenting Clew3D, we report the results of an analysis conducted with COMS regarding techniques and terminology used in traditional, in-person O&M instruction. We also discuss challenges posed by vision-based systems to achieve automatic narrations that are reliable. Finally, we provide an example of an automatically generated route description and compare it with the same route provided by a COMS.

Motivated by a combination of social media, technological evolution, as well as new habits and preferences of TV content consumers, there is an increasing demand for enhancement of professional productions with user generated content. Studies have explored the potential and feasibility of this approach, indicating that footage from non-professionals can be effectively used to enrich the viewing experience. However, an important concern is whether such efforts are appealing to potential contributors, and what can actually impact their satisfaction and loyalty. Aiming to investigate these factors, this paper presents a mobile application for content contributors and a study involving 38 attendees of live events, using the application in the field. The events were hosted in two different countries, and transmitted by two well-known broadcasters. The results suggest that age, gender, technological expertise, and overall sharing attitude do not affect the satisfaction and loyalty of contributors. The differentiating factors, however, are the filming confidence and expertise of contributors, as well as the Wi-Fi/4G connectivity on-site. Implications of these findings are discussed and recommendations for similar endeavors are provided.

The use of mobile devices during television viewing is now commonplace, and broadcasters are increasingly supplying programme-related ‘companion content’. To produce an optimal user experience, it is important to determine how the delivery of companion content affects and is perceived by the viewer — without this we risk distracting the viewer, leading to frustration and disengagement. We present a controlled study investigating how attention, cognitive load (as measured by the NASA TLX), and users’ preferences are affected by the provision of two different content delivery modes: pushed and pulled . We find that delivery mode affected the temporal distribution of gaze to the tablet, with a consistent viewing pattern for pushed updates, which attracted attention within a few seconds, and a more diverse set of viewing patterns when updates were pulled. Cognitive load was similar in both conditions, and there was no consensus as to which mode was preferred, but users showed strong, polarised individual preferences. The advantages of each delivery mode are presented as a set of recommendations for the delivery of companion content.

Rich metadata is becoming a key part of the broadcast production pipeline. This information can be used to deliver compelling new consumption experiences which are personalized, location-aware, interactive and multi-screen. However, media producers are struggling to generate the metadata required for such experiences, using inefficient post-production solutions which are limited in how much of the original context they can capture. In response, we present Media of Things (MoT), a tool for on-location media productions. MoT enables practical and flexible generation of sensor based point-of-capture metadata. We demonstrate how embedded ubiquitous sensing technologies such as the Internet of Things can be leveraged to produce context rich, time sequenced metadata in a production studio. We reflect on how this workflow can be integrated within the constraints of broadcast production and the possibilities that emerge from access to rich data at the beginning of the production lifecycle to produce well described media for reconfigurable consumption.

Abstract Mobile devices enable users to consume media with audio content in a wide range of contexts, with environmental noise being present in many of these. Several methods exist that aim to improve the experience of mobile listening by utilising information about the environmental noise, such as volume and dynamic range adaptation. This paper explores a fundamentally different approach to improving the mobile listening experience by using the object-based audio paradigm, where individual audio sources are mixed in response to each specific listening context. Three experimental studies, containing both quantitative and qualitative aspects, are presented which investigate whether environmental noise influences preference of background-foreground audio object balance in a mix. The results indicate that environmental noise can influence the preferred audio mix and that the nature of the adaptations made is dependent upon both audio content and user. Additionally, qualitative analysis provides an understanding of the role of environmental noise on preferred audio mix. It is believed that the content adaptation method explored in this paper is a simple yet useful tool for adapting content to suit both the context and the user.

A physical hardware prototype--The Button was developed as a research probe to understand how radio audiences could discover, organise and consume music radio content at the touch of a physical button, the only control on a tiny handheld device. The Button allows listeners to tag tracks they like via a simple one-touch interaction method, and save them to a non-commercial online playlist service: BBC Playlister. Users can then export these tags to other music streaming platforms, such as Spotify, Deezer, etc. Following a user-centric design process, a large in-the-wild study was conducted over several weeks to investigate the value of the Button in aiding listeners' discovery of music. One group of participants was given a mobile phone app designed to facilitate tagging music heard on BBC radio stations; two other groups were given both the app and a Button (in one of two hardware versions). The findings revealed that Button users made significantly more tags on average than app users, indicating that a physical device could add significant value for radio listeners who want to tag music. Participants valued the simple one-touch interaction method, especially in situations where their smartphones were out of reach or contextual constraints meant that interaction with a complex device was undesirable or difficult.

So many people are now using handheld second screens whilst watching TV that application developers and broadcasters are designing companion applications Second screen content that accompanies a TV programme. The nature of such dual-screen use cases inherently causes attention to be split, somewhat unpredictably. Dual-screen complexity, a clear factor in this attention split, is largely unexplored by the literature and will have an unknown (and likely negative) impact on user experience (UX). Therefore, we use empirical techniques to investigate the objective and subjective effect of dual-screen visual complexity on attention distribution in a companion content scenario. Our sequence of studies culminates in the deployment of a companion application prototype that supports adjustment of complexity (by either content curator or viewer) to allow convergence on optimum experience. Our findings assist the effective design of dual-screen content, informing content providers how to manage dual second screen complexity for enhanced UX through a more blended, complementary dual-screen experience.

There is increasing interest in providing content to users on secondary devices while they watch TV. This material, termed companion content, can be anything from textual information, to interactive quiz games. It can be delivered throughout a broadcast and often directly relates to specific scenes in a show. This new scenario has exposed a challenging design space for creators of both the content and the enabling technology. A key question when introducing content on a secondary device is how much it detracts from, or enhances, the show the user is currently engaged with. To examine this, we investigated methods for mediating attention from the TV and onto a secondary device. By examining a typical use case we have been able to gain new insights into how best to design additional stimuli to alert users to companion content from both a broadcasting, and an HCI perspective.

We describe a framework for comprehensive electronic QA currently under development in the department of Radiation Oncology at the Montreal General Hospital. When complete, the system will incorporate all data generated within the department. It will allow for easy access to all aspects of a patient's treatment and to the state of all relevant equipment at the time of treatment. Quality control will be achieved through automated Shewhart-type control charting with appropriate statistical analysis. Machine learning methods will be used to examine the data in order to search for errors, inconsistencies and unnecessary treatment delays. The system will entail a web interface internal to the clinic and written in PERL.

We describe an initiative under way at Warwick to provide a technical foundation for computer-aided learning and computer-assisted assessment tools, which allows a rich dialogue sensitive to individual students' response patterns. The system distinguishes between dialogues for individual problems and the linking of problems. This enables a subject specialist to craft individual questions and units of learning material, while allowing the order of presentation of the units to depend on a student's interaction history. We develop a markup language, specified as an XML DTD, to enable the storage of data for use in such systems.