• VRIA - A Framework for Immersive Analytics on the Web

      Butcher, Peter; John, Nigel; Ritsos, Panagiotis; University of Chester and Bangor University (ACM, 2019-05)
      We report on the design, implementation and evaluation of <VRIA>, a framework for building immersive analytics (IA) solutions inWeb-based Virtual Reality (VR), built upon WebVR, A-Frame, React and D3. The recent emergence of affordable VR interfaces have reignited the interest of researchers and developers in exploring new, immersive ways to visualize data. In particular, the use of open-standards web-based technologies for implementing VR in a browser facilitates the ubiquitous and platform-independent adoption of IA systems. Moreover, such technologies work in synergy with established visualization libraries, through the HTML document object model (DOM). We discuss high-level features of <VRIA> and present a preliminary user experience evaluation of one of our use-cases.
    • Adapting Jake Knapp’s Design Sprint Approach for AR/VR Applications in Digital Heritage

      Southall, Helen; Marmion, Maeve; Davies, Andrew; University of Chester (Springer Nature, 2019)
      Modern digital devices offer huge potential for the delivery of engaging heritage experiences to visitors, offering a better visitor experience, higher visitor numbers, and opportunities for increased tourism income. However, all software development entails risk, including the risk of developing a product which few will want, or be able, to use. Identifying user experience priorities and problems at an early stage is therefore extremely important. This chapter describes work in progress on a shortened version of Jake Knapp’s Design Sprint approach, and its application to designing VR/AR solutions for a specific heritage case study.
    • Appearance Modeling of Living Human Tissues

      Nunes, Augusto L.P.; Maciel, Anderson; Meyer, Gary W.; John, Nigel W.; Baranoski, Gladimir V.G.; Walter, Marcelo; Federal Institute of Paraná, Londrina; Universidade Federal do Rio Grande do Sul; University of Minnesota; University of Chester; University of Waterloo (Wiley, 2019)
      The visual fidelity of realistic renderings in Computer Graphics depends fundamentally upon how we model the appearance of objects resulting from the interaction between light and matter reaching the eye. In this paper, we survey the research addressing appearance modeling of living human tissue. Among the many classes of natural materials already researched in Computer Graphics, living human tissues such as blood and skin have recently seen an increase in attention from graphics research. There is already an incipient but substantial body of literature on this topic, but we also lack a structured review as presented here. We introduce a classification for the approaches using the four types of human tissues as classifiers. We show a growing trend of solutions that use first principles from Physics and Biology as fundamental knowledge upon which the models are built. The organic quality of visual results provided by these Biophysical approaches is mainly determined by the optical properties of biophysical components interacting with light. Beyond just picture making, these models can be used in predictive simulations, with the potential for impact in many other areas.
    • Towards Organisational Learning Enhancement: Assessing Software Engineering Practice

      Fannoun, Sufian; Kerins, John; University of Chester (Emerald Publishing Limited, 2018-12-17)
      • Purpose – Issues surrounding knowledge management, knowledge transfer and learning within organisations challenge continuity and resilience in the face of changing environments. While initiatives are principally applied within large organisations, there is scope to assess how the processes are handled within small and medium enterprises (SMEs) and to consider how they might be enhanced. This paper presents an evaluation of practice within an evolving software development unit to determine what has been learned and how the knowledge acquired has been utilised to further organisational development. These results provide the basis for the design and implementation of a proposed support tool to enhance professional practice. • Design/methodology/approach – A small software development unit, which has successfully delivered bespoke systems since its establishment a number of years ago, was selected for analysis. The unit operates as a team whose actions and behaviours were identified and validated by the following means: in-depth interviews were carried out with each member of the team to elicit an understanding of individual and collective development. Interview data were recorded and transcribed and subjected to qualitative analysis to identify key themes underpinning knowledge acquisition and utilisation. Samples of project documentation were scrutinised to corroborate interview data. After analysing the data, a focus-group meeting was held to validate the results and to generate further insights into learning within the team. • Findings - Qualitative analysis of the data revealed key changes in thinking and practice within the team as well as insight into the development of individual and collective contextual knowledge, tacit understanding and learning. This analysis informed the proposal of a bespoke, lightweight, web-based system to support knowledge capture and organisational learning (OL). This approach has the potential to promote resilience and to enhance practice in similar small or start-up enterprises. • Research limitations/implications – Purposeful sampling was used in selecting a small software development team. This enabled in-depth interviewing of all members of the team. This offered a rich environment from which to derive awareness and understanding of individual and collective knowledge acquisition and learning. Focusing on a single small enterprise limits the extent to which the findings can be generalised. However, the research provides evidence of effective practice and learning and has identified themes for the development of a support tool. This approach can be extended to similar domains to advance research into learning and development. • Practical implications – Results of the work undertaken so far have generated promising foundations for the proposed support tool. This offers software developers a system within which they can reflect upon, and record, key learning events affecting technical, managerial and professional practice. • Originality/value – Small enterprises have limited resources to support OL. The qualitative research undertaken so far has yielded valuable insight into the successful development of a single software development team. The construction of a support tool to enhance knowledge acquisition and learning has the capacity to consolidate valuable, and potentially scarce, expertise. It also has the potential to facilitate further research to determine how the prototype might be extended or revised to improve its contribution to the team’s development.
    • An Information-Theoretic Approach to the Cost-benefit Analysis of Visualization in Virtual Environments

      Chen, Min; Gaither, Kelly; John, Nigel; McCann, Brian; University of Oxford; University of Texas at Austin; University of Chester (IEEE, 2018-08-20)
      Visualization and virtual environments (VEs) have been two interconnected parallel strands in visual computing for decades. Some VEs have been purposely developed for visualization applications, while many visualization applications are exemplary showcases in general-purpose VEs. Because of the development and operation costs of VEs, the majority of visualization applications in practice have yet to benefit from the capacity of VEs. In this paper, we examine this status quo from an information-theoretic perspective. Our objectives are to conduct cost-benefit analysis on typical VE systems (including augmented and mixed reality, theatre-based systems, and large powerwalls), to explain why some visualization applications benefit more from VEs than others, and to sketch out pathways for the future development of visualization applications in VEs. We support our theoretical propositions and analysis using theories and discoveries in the literature of cognitive sciences and the practical evidence reported in the literatures of visualization and VEs.
    • Multi-Agent Reinforcement Learning for Swarm Retrieval with Evolving Neural Network

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer-Verlag,, 2018-07-07)
      This research investigates methods for evolving swarm communica-tion in a sim-ulated colony of ants using pheromone when foriaging for food. This research implemented neuroevolution and obtained the capability to learn phero-mone communication autonomously. Building on previous literature on phero-mone communication, this research applies evolution to adjust the topology and weights of an artificial neural network (ANN) which controls the ant behaviour. Compar-ison of performance is made between a hard-coded benchmark algorithm (BM1), a fixed topology ANN and neuroevolution of the ANN topology and weights. The resulting neuroevolution produced a neural network which was suc-cessfully evolved to achieve the task objective, to collect food and return it to a location.
    • Evolution of Neural Networks for Physically Simulated Evolved Virtual Quadruped Creatures

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer-Verlag, 2018-07-07)
      This work develops evolved virtual creatures (EVCs) using neuroevolution as the controller for movement and decisions within a 3D physics simulated environ-ment. Previous work on EVCs has displayed various behaviour such as following a light source. This work is focused on complexifying the range of behaviours available to EVCs. This work uses neuroevolution for learning specific actions combined with other controllers for making higher level decisions about which action to take in a given scenario. Results include analysis of performance of the EVCs in simulated physics environment. Various controllers are compared including a hard coded benchmark, a fixed topology feed forward artificial neural network and an evolving ANN subjected to neuroevolution by applying mutations in both topology and weights. The findings showed that both fixed topology ANNs and neuroevolution did successfully control the evolved virtual creatures in the distance travelling task.
    • Evolutionary Robot Swarm Cooperative Retrieval

      Vaughan, Neil; Royal Academy of Engineering; University of Chester (Springer, 2018-07-07)
      In nature bees and leaf-cutter ants communicate to improve cooperation during food retrieval. This research aims to model communication in a swarm of auton-omous robots. When food is identified robot communication is emitted within a limited range. Other robots within the range receive the communication and learn of the location and size of the food source. The simulation revealed that commu-nication improved the rate of cooperative food retrieval tasks. However a counter-productive chain reaction can occur when robots repeat communications from other robots causing cooperation errors. This can lead to a large number of robots travelling towards the same food source at the same time. The food becomes de-pleted, before some robots have arrived. Several robots continue to communicate food presence, before arriving at the food source to find it gone. Nature-inspired communication can enhance swarm behaviour without requiring a central control-ler and may be useful in autonomous drones or vehicles.
    • Colour Coded Emotion Classification in Mental Health Social Media

      Vaughan, Neil; Mulvenna, Maurice; Bond, Raymond; Royal Academy of Engineering; University of Chester (BCS, The Chartered Institute for IT, ACM Proceedings, 2018-07-06)
      This research applies emotion detection to messages from online mental health social media. In particular, this focusses on specialised social media for users to report health or mental health problems. Automatically detecting the emotion in social media can help to rapidly identify any concerning problems which could benefit from intervention aiming to prevent self-harming or suicide. Detecting emotions enables messages to be colour coordinated according to the emotion to enhance the human-computer interaction. A supervised classification method is applied to a labelled dataset and results presented. A prototype user interface system is developed based on detecting emotion, colour coding the message to display detected emotions to users in real-time.
    • Evaluating current practice and proposing a system to enhance knowledge assets within a small software development unit

      Fannoun, Sufian; Kerins, John; The University of Chester (IEEE, 2018-06-25)
      Knowledge management and knowledge transfer within organisations challenge continuity and resilience in the face of changing environments. While issues are principally addressed within large organisations, there is scope to evaluate how knowledge assets are managed within small and medium enterprises and to consider how the process might be enhanced. The research reported here aimed to evaluate practice within an evolving software development unit to understand how knowledge has been acquired and utilised to further organisational development. In-depth interviews were carried out with members of the unit to elicit an understanding of individual and collective learning. Qualitative analysis of the data revealed key changes in thinking and practice as well as insight into the development of individuals' contextual knowledge and tacit understanding. This analysis led to the proposal of a bespoke, lightweight web-based system to support knowledge capture and organisational learning. This work is still in progress but it is anticipated that the results will provide a potentially novel and beneficial method for enhancing knowledge assets in small enterprises and consolidating valuable, and potentially scarce, expertise.
    • Swarm Communication by Evolutionary Algorithms

      Vaughan, Neil; University of Chester (IEEE, 2018-05-27)
      This research has applied evolutionary algorithms to evolve swarm communication. Controllers were evolved for colonies of artificial simulated ants during a food foriaging task which communicate using pheromone. Neuroevolution enables both weights and the topology of the artificial neural networks to be optimized for food foriaging. The developed model results in evolution of ants which communicate using pheromone trails. The ants successfully collect and return food to the nest. The controller has evolved to adjust the strength of pheromone which provides a signal to guide the direction of other ants in the colony by hill climbing strategy. A single ANN controller for ant direction successfully evolved which exhibits many separate skills including food search, pheromone following, food collection and retrieval to the nest.
    • Associating Colours with Emotions Detected in Social Media Tweets

      Harvey, R.; Muncey, A.; Vaughan, N.; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This project involves two major areas of work, the detection of emotions in text from Twitter posts (tweets), and the association of that emotion with colour. Emotion mining is the field of natural language processing which is concerned with the detection and classification. It is a subfield of semantic analysis which contains both emotion and opinion mining. Both tasks depend on an emotion model to classify detected emotions and to associate a colour depending on the location of the emotion in the model. This research paper demonstrates preliminary results from classification of tweets to assign emotion labels. Also designs are presented for a prototype web interface for displaying the assigned colour and emotion associated with tweets.
    • Morphogenetic Engineering For Evolving Ant Colony Pheromone Communication

      Vaughan, Neil; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This research investigates methods for evolving swarm communication in a simulated colony of ants using pheromone when foriaging for food. This research implemented neuroevolution and obtained the capability to learn pheromone communication autonomously. Building on previous literature on pheromone communication, this research applies evolution to adjust the topology and weights of an artificial neural network which controls the ant behaviour. Comparison of performance is made between a hard-coded benchmark algorithm, a fixed topology ANN and neuroevolution of the ANN topology and weights. The resulting neuroevolution produced a neural network which was successfully evolved to achieve the task objective, to collect food and return it to the nest.
    • How effective is Ant Colony Optimisation at Robot Path Planning

      Wolfenden, A.; Vaughan, Neil; University of Chester (The Society for the Study of Artificial Intelligence and Simulation for Behaviour (AISB), 2018-04-06)
      This project involves investigation of the problem robot path planning using ant colony optimisation heuristics to construct the quickest path from the starting point to the end. The project has developed a simulation that successfully simulates as well as demonstrates visually through a graphical user interface, robot path planning using ant colony optimisation. The simulation shows an ability to traverse an unknown environment from a start point to an end and successfully construct a route for others to follow both when the terrain is dynamic and static
    • Double-diffusive natural convection in a differentially heated wavy cavity under thermophoresis effect

      Grosan, Teodor; Sheremet, Mikhail A.; Pop, Ioan; Pop, Serban R.; Babes-Bolyai University; Tomsk State University; University of Chester (American Institute of Aeronautics and Astronautics, 2018-02-28)
      A numerical analysis is made for thermophoretic transport of small particles through the convection in a differentially heated square cavity with a wavy wall. The governing gas-particle partial differential equations are solved numerically for some values of the considered parameters to investigate their influence on the flow, heat, and mass transfer patterns. It is found that the effect of thermophoresis can be quite significant in appropriate situations. The number of undualtions can essentially modify the heat transfer rate and fluid flow intensity.
    • SLAM-based dense surface reconstruction in monocular Minimally Invasive Surgery and its application to Augmented Reality

      Chen, Long; Tang, Wen; John, Nigel W.; Wan, Tao R.; Zhang, Jian J.; Bournemouth University; University of Chester; University of Bradford (Elsevier, 2018-02-08)
      Background and Objective While Minimally Invasive Surgery (MIS) offers considerable benefits to patients, it also imposes big challenges on a surgeon's performance due to well-known issues and restrictions associated with the field of view (FOV), hand-eye misalignment and disorientation, as well as the lack of stereoscopic depth perception in monocular endoscopy. Augmented Reality (AR) technology can help to overcome these limitations by augmenting the real scene with annotations, labels, tumour measurements or even a 3D reconstruction of anatomy structures at the target surgical locations. However, previous research attempts of using AR technology in monocular MIS surgical scenes have been mainly focused on the information overlay without addressing correct spatial calibrations, which could lead to incorrect localization of annotations and labels, and inaccurate depth cues and tumour measurements. In this paper, we present a novel intra-operative dense surface reconstruction framework that is capable of providing geometry information from only monocular MIS videos for geometry-aware AR applications such as site measurements and depth cues. We address a number of compelling issues in augmenting a scene for a monocular MIS environment, such as drifting and inaccurate planar mapping. Methods A state-of-the-art Simultaneous Localization And Mapping (SLAM) algorithm used in robotics has been extended to deal with monocular MIS surgical scenes for reliable endoscopic camera tracking and salient point mapping. A robust global 3D surface reconstruction framework has been developed for building a dense surface using only unorganized sparse point clouds extracted from the SLAM. The 3D surface reconstruction framework employs the Moving Least Squares (MLS) smoothing algorithm and the Poisson surface reconstruction framework for real time processing of the point clouds data set. Finally, the 3D geometric information of the surgical scene allows better understanding and accurate placement AR augmentations based on a robust 3D calibration. Results We demonstrate the clinical relevance of our proposed system through two examples: a) measurement of the surface; b) depth cues in monocular endoscopy. The performance and accuracy evaluations of the proposed framework consist of two steps. First, we have created a computer-generated endoscopy simulation video to quantify the accuracy of the camera tracking by comparing the results of the video camera tracking with the recorded ground-truth camera trajectories. The accuracy of the surface reconstruction is assessed by evaluating the Root Mean Square Distance (RMSD) of surface vertices of the reconstructed mesh with that of the ground truth 3D models. An error of 1.24mm for the camera trajectories has been obtained and the RMSD for surface reconstruction is 2.54mm, which compare favourably with previous approaches. Second, in vivo laparoscopic videos are used to examine the quality of accurate AR based annotation and measurement, and the creation of depth cues. These results show the potential promise of our geometry-aware AR technology to be used in MIS surgical scenes. Conclusions The results show that the new framework is robust and accurate in dealing with challenging situations such as the rapid endoscopy camera movements in monocular MIS scenes. Both camera tracking and surface reconstruction based on a sparse point cloud are eff active and operated in real-time. This demonstrates the potential of our algorithm for accurate AR localization and depth augmentation with geometric cues and correct surface measurements in MIS with monocular endoscopes.
    • Quantification of the pressures generated during insertion of an epidural needle in labouring women of varying body mass indices

      Wee, M. Y. K.; Isaacs, R.; Vaughan, Neil; Dubey, V. N.; Parker, B.; University of Chester; Bournemouth University; Poole Hospital NHS Trust; West Hertfordshire NHS Trust; Southampton University Hospital (Heighten Science Publications, 2017-12-01)
      Objective: The primary aim of this study was to measure pressure generated on a Tuohy needle during the epidural procedure in labouring women of varying body mass indices (BMI) with a view of utilising the data for the future development of a high fi delity epidural simulator. High-fi delity epidural simulators have a role in improving training and safety but current simulators lack a realistic experience and can be improved. Methods: This study was approved by the National Research Ethics Service Committee South Central, Portsmouth (REC reference 11/SC/0196). After informed consent epidural needle insertion pressure was measured using a Portex 16-gauge Tuohy needle, loss-of-resistance syringe, a three-way tap, pressure transducer and a custom-designed wireless transmitter. This was performed in four groups of labouring women, stratified according to BMI kg/m2: 18-24.9; 25-34.9; 35-44.9 and >=45. One-way ANOVA was used to compare difference in needle insertion pressure between the BMI groups. A paired t-test was performed between BMI group 18-24.9 and the three other BMI groups. Ultrasound images of the lumbar spine were undertaken prior to the epidural procedure and lumbar magnetic resonance imaging (MRI) was performed within 72h post-delivery. These images will be used in the development of a high fi delity epidural simulator. Results: The mean epidural needle insertion pressure of labouring women with BMI 18-24.9 was 461mmHg; BMI 25-34.9 was 430mmHg; BMI 35-44.9 was 415mmHg and BMI >=45 was 376mmHg, (p=0.52). Conclusion: Although statistically insignifi cant, the study did show a decreasing trend of epidural insertion pressure with increasing body mass indices.
    • Real-time Geometry-Aware Augmented Reality in Minimally Invasive Surgery

      Chen, Long; Tang, Wen; John, Nigel W.; Bournemouth University; University of Chester (IET, 2017-10-27)
      The potential of Augmented Reality (AR) technology to assist minimally invasive surgeries (MIS) lies in its computational performance and accuracy in dealing with challenging MIS scenes. Even with the latest hardware and software technologies, achieving both real-time and accurate augmented information overlay in MIS is still a formidable task. In this paper, we present a novel real-time AR framework for MIS that achieves interactive geometric aware augmented reality in endoscopic surgery with stereo views. Our framework tracks the movement of the endoscopic camera and simultaneously reconstructs a dense geometric mesh of the MIS scene. The movement of the camera is predicted by minimising the re-projection error to achieve a fast tracking performance, while the 3D mesh is incrementally built by a dense zero mean normalised cross correlation stereo matching method to improve the accuracy of the surface reconstruction. Our proposed system does not require any prior template or pre-operative scan and can infer the geometric information intra-operatively in real-time. With the geometric information available, our proposed AR framework is able to interactively add annotations, localisation of tumours and vessels, and measurement labelling with greater precision and accuracy compared with the state of the art approaches.
    • Recent Developments and Future Challenges in Medical Mixed Reality

      Chen, Long; Day, Thomas; Tang, Wen; John, Nigel W.; Bournemouth University and University of Chester (2017-10)
      Mixed Reality (MR) is of increasing interest within technology driven modern medicine but is not yet used in everyday practice. This situation is changing rapidly, however, and this paper explores the emergence of MR technology and the importance of its utility within medical applications. A classification of medical MR has been obtained by applying an unbiased text mining method to a database of 1,403 relevant research papers published over the last two decades. The classification results reveal a taxonomy for the development of medical MR research during this period as well as suggesting future trends. We then use the classification to analyse the technology and applications developed in the last five years. Our objective is to aid researchers to focus on the areas where technology advancements in medical MR are most needed, as well as providing medical practitioners with a useful source of reference.
    • Wheelchair-MR: A Mixed Reality Wheelchair Training Environment

      Day, Thomas; University of Chester (2017-09-20)
      In previous work we have demonstrated that Virtual Reality can be used to help train driving skills for users of a powered wheelchair. However, cybersickness was a particular problem. This work-in-progress paper presents a Mixed Reality alternative to our wheelchair training software, which overcomes this problem. The design and implementation of this application is discussed. Early results shows some promise and overcomes the cybersickness issue. More work is needed before a larger scale study can be undertaken.