• 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, 2019-04-21)
      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.
    • Addressing problems of student retention and achievement with the help of a Virtual Learning Environment (VLE)

      Scott, Tony; University College Chester (Subject Centre for Information and Computer Sciences, Higher Education Academy, 2004)
      This article discussed methods taken during 2002-2003 to improve retention and achievement in the Introduction to Software Design module. They include e-mail feedback, study guides, and use of the college's VLE.
    • Alternative Representations of 3D-Reconstructed Heritage Data

      Miles, Helen C.; Wilson, Andrew T.; Labrosse, Frédéric; Tiddeman, Bernard; Griffiths, Seren; Edwards, Ben; Ritsos, Panagiotis D.; Mearman, Joseph W.; Moller, Katharina; Karl, Raimund; et al. (ACM, 2016-02-20)
      By collecting images of heritage assets from members of the public and processing them to create 3D-reconstructed models, the HeritageTogether project has accomplished the digital recording of nearly 80 sites across Wales, UK. A large amount of data has been collected and produced in the form of photographs, 3D models, maps, condition reports, and more. Here we discuss some of the different methods used to realize the potential of this data in different formats and for different purposes. The data are explored in both virtual and tangible settings, and—with the use of a touch table—a combination of both. We examine some alternative representations of this community-produced heritage data for educational, research, and public engagement applications.
    • An overview of thermal necrosis: present and future

      Mediouni, Mohamed; Kucklick, Theodore; Poncet, Sébastien; Madiouni, Riadh; Abouaomar, Amine; Madry, Henning; Cucchiarini, Magali; Chopko, Bohdan; Vaughan, Neil; Arora, Manit; et al. (Informa UK Limited, 2019-05-10)
    • Appearance Modeling of Living Human Tissues

      Maciel, Anderson; Meyer, Gary W.; John, Nigel W.; Walter, Marcelo; Nunes, Augusto L. P.; Baranoski, Gladimir V. G.; Federal Institute of Paraná, Londrina; Universidade Federal do Rio Grande do Sul; University of Minnesota; University of Chester; University of Waterloo (Wiley, 2019-02-27)
      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.
    • Assisting Serious Games Level Design with an Augmented Reality Application and Workflow

      Beever, Lee; John, Nigel W.; Pop, Serban R.; University of Chester (Eurographics Proceedings, 2019-09-13)
      With the rise in popularity of serious games there is an increasing demand for virtual environments based on real-world locations. Emergency evacuation or fire safety training are prime examples of serious games that would benefit from accurate location depiction together with any application involving personal space. However, creating digital indoor models of real-world spaces is a difficult task and the results obtained by applying current techniques are often not suitable for use in real-time virtual environments. To address this problem, we have developed an application called LevelEd AR that makes indoor modelling accessible by utilizing consumer grade technology in the form of Apple’s ARKit and a smartphone. We compared our system to that of a tape measure and a system based on an infra-red depth sensor and application. We evaluated the accuracy and efficiency of each system over four different measuring tasks of increasing complexity. Our results suggest that our application is more accurate than the depth sensor system and as accurate and more time efficient as the tape measure over several tasks. Participants also showed a preference to our LevelEd AR application over the depth sensor system regarding usability. Finally, we carried out a preliminary case study that demonstrates how LevelEd AR can be successfully used as part of current industry workflows for serious games level design.
    • Associating Colours with Emotions Detected in Social Media Tweets

      Harvey, Robert; Muncey, Andrew; Vaughan, Neil; 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.
    • An Augmented Reality Tool to aid Radiotherapy Set Up implemented on a Tablet Device

      Cosentino, Francesco; Vaarkamp, Japp; John, Nigel W.; University of Chester, North Wales Cancer Treatment Centre (International Conference on the use of Computers in Radiation Therapy, 2016-06)
      The accurate daily set up of patients for radiotherapy treatment remains a challenge for which the development of new strategies and solutions continues to be an area of active research. We have developed an augmented reality tool to view the real world scene, i.e. the patient on a treatment couch, combined with computer graphics content, such as planning image data and any defined outlines of organ structures. We have built this on widely available hand held consumer tablet devices and describe here the implementation and initial experience. We suggest that, in contrast to other augmented reality tools explored for radiotherapy[1], due to the wide availability and low cost of the hardware platform the application has further potential as a tool for patients to visualize their treatment and demonstrate to patients e.g. the importance of compliance with instructions around bladder filling and rectal suppositories.
    • Building Immersive Data Visualizations for the Web

      Butcher, Peter; Ritsos, Panagiotis D.; University of Chester; Bangor University (IEEE Conference Publications, 2017-09)
      We present our early work on building prototype applications for Immersive Analytics using emerging standards-based web technologies for VR. For our preliminary investigations we visualize 3D bar charts that attempt to resemble recent physical visualizations built in the visualization community. We explore some of the challenges faced by developers in working with emerging VR tools for the web, and in building effective and informative immersive 3D visualizations.
    • CAB - Collaboration across borders: Peer evaluation for collaborative learning

      Whatley, Janice; Bell, Frances; Shaylor, Jan P.; Zaitseva, Elena; Zakrzewska, Danuta (The Informing Science Institute, 2005)
    • 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.
    • Comparing and combining time series trajectories using Dynamic Time Warping

      Vaughan, Neil; Gabrys, Bogdan; Bournemouth University (Elsevier, 2016-09-04)
      This research proposes the application of dynamic time warping (DTW) algorithm to analyse multivariate data from virtual reality training simulators, to assess the skill level of trainees. We present results of DTW algorithm applied to trajectory data from a virtual reality haptic training simulator for epidural needle insertion. The proposed application of DTW algorithm serves two purposes, to enable (i) two trajectories to be compared as a similarity measure and also enables (ii) two or more trajectories to be combined together to produce a typical or representative average trajectory using a novel hierarchical DTW process. Our experiments included 100 expert and 100 novice simulator recordings. The data consists of multivariate time series data-streams including multi-dimensional trajectories combined with force and pressure measurements. Our results show that our proposed application of DTW provides a useful time-independent method for (i) comparing two trajectories by providing a similarity measure and (ii) combining two or more trajectories into one, showing higher performance compared to conventional methods such as linear mean. These results demonstrate that DTW can be useful within virtual reality training simulators to provide a component in an automated scoring and assessment feedback system.
    • Context-Aware Mixed Reality: A Learning-based Framework for Semantic-level Interaction

      Chen, Long; Tang, Wen; Zhang, Jian Jun; John, Nigel W.; Bournemouth University; University of Chester; University of Bradford
      Mixed Reality (MR) is a powerful interactive technology for new types of user experience. We present a semantic-based interactive MR framework that is beyond current geometry-based approaches, offering a step change in generating high-level context-aware interactions. Our key insight is that by building semantic understanding in MR, we can develop a system that not only greatly enhances user experience through object-specific behaviors, but also it paves the way for solving complex interaction design challenges. In this paper, our proposed framework generates semantic properties of the real-world environment through a dense scene reconstruction and deep image understanding scheme. We demonstrate our approach by developing a material-aware prototype system for context-aware physical interactions between the real and virtual objects. Quantitative and qualitative evaluation results show that the framework delivers accurate and consistent semantic information in an interactive MR environment, providing effective real-time semantic level interactions.
    • Contextual Network Navigation to provide Situational Awareness for Network Administrators

      Gray, Cameron C.; Ritsos, Panagiotis D.; Roberts, Jonathan C.; Bangor University; University of Chester (IEEE, 2015-10-26)
      One of the goals of network administrators is to identify and block sources of attacks from a network steam. Various tools have been developed to help the administrator identify the IP or subnet to be blocked, however these tend to be non-visual. Having a good perception of the wider network can aid the administrator identify their origin, but while network maps of the Internet can be useful for such endeavors, they are difficult to construct, comprehend and even utilize in an attack, and are often referred to as being “hairballs”. We present a visualization technique that displays pathways back to the attacker; we include all potential routing paths with a best-efforts identification of the commercial relationships involved. These two techniques can potentially highlight common pathways and/or networks to allow faster, more complete resolution to the incident, as well as fragile or incomplete routing pathways to/from a network. They can help administrators re-profile their choice of IP transit suppliers to better serve a target audience.
    • A Cost-Effective Virtual Environment for Simulating and Training Powered Wheelchairs Manoeuvres

      Headleand, Christopher J.; Day, Thomas W.; Pop, Serban R.; Ritsos, Panagiotis D.; John, Nigel W.; Bangor University and University of Chester (IOS Press, 2016-04-07)
      Control of a powered wheelchair is often not intuitive, making training of new users a challenging and sometimes hazardous task. Collisions, due to a lack of experience can result in injury for the user and other individuals. By conducting training activities in virtual reality (VR), we can potentially improve driving skills whilst avoiding the risks inherent to the real world. However, until recently VR technology has been expensive and limited the commercial feasibility of a general training solution.We describe Wheelchair-Rift, a cost effective prototype simulator that makes use of the Oculus Rift head mounted display and the Leap Motion hand tracking device. It has been assessed for face validity by a panel of experts from a local Posture and Mobility Service. Initial results augur well for our cost-effective training solution.
    • Dance Bands in Chester & North Wales, 1930 – 1970: Revealing a Hidden History

      Southall, Helen; University of Chester (2016-01-11)
      Dance bands in Chester and North Wales, 1930 - 1970 : Revealing a Hidden History “… the work of local amateur musicians is not just haphazard or formless, the result of individual whim or circumstance. On the contrary, a consistent - if sometimes changing - structure lies behind these surface activities. The public events … are part of an invisible but organised system through which individuals make their contribution to both the changes and the continuities of English music today.” (Finnegan, 2007) Chester (UK) in the period around World War II had a thriving live dance music scene, in which most of the music-making was done by local semi-professional musicians. Although they were busiest in the 1940s and 50s, many of the bands involved continued to operate alongside groups playing rock 'n' roll and pop, often in the same venues and sometimes at the same events, and the infrastructure which had supported the dance bands is an essential, if under-recorded, part of the history of rock 'n' roll and beat bands in the area (including the Beatles). This presentation looks at evidence from a recently-completed Ph.D. project to investigate how this local dance band scene worked, including the nature and evolution of its 'invisible but organised' underlying structure. The majority of the data was collected from private sources, with the aim of recording information which was not available in a single, academically-accessible archive. Fieldwork included over 30 recorded interviews with musicians, promoters and dancers. It also yielded more than 200 photographs and images which helped to illuminate the world of the bands, musicians and venues mentioned, and to produce a comprehensive snapshot of the local dance band scene, covering as wide a range as possible of social and musical backgrounds and experiences. Inspirations for this oral history project include The Hidden Musicians (Finnegan, 2007), Jazz Places (Becker, 2004), Rock Culture in Liverpool (Cohen, 1991), Other Voices (Brocken, 2010) and Victory Through Harmony (Baade, 2013). It is hoped that combining ideas from these and other sources with a detailed investigation of this specific local scene, as this work has done, will contribute further to a better understanding of amateur and semi-professional music-making in an urban landscape. Becker, Howard S. (2004). Jazz Places. In A. Bennett & R. A. Peterson (Eds.), Music Scenes: Local, Translocal and Virtual (pp. 17 - 27): Vanderbilt University Press. Brocken, Michael. (2010). Other voices : hidden histories of Liverpool's popular music scenes, 1930s - 1970s: Ashgate Publishing Ltd. Cohen, Sara. (1991). Rock Culture in Liverpool : Popular Music in the Making: Oxford University Press. Finnegan, Ruth H. . (2007). The Hidden Musicians: Music-Making in an English Town: Wesleyan University Press.
    • Dance bands in Chester (1930 - 1970) : An evolving professional network

      Southall, Helen; University of Chester (2011-09)
      Headings are: the city of Chester; a hidden history; jazz places; economic places; social networks; methodology and findings.
    • Data aggregation in wireless sensor networks with minimum delay and minimum use of energy: A comparative study

      Qayyum, Bushra; Saeed, Mohammed; Roberts, Jason A.; University of Chester ; Al Khawarizmi University College ; University of Chester (British Computer Society, 2015)
      The prime objective of deploying large- scale wireless sensor networks is to collect information from to control systems associated with these networks. Wireless sensor networks are widely used in application domains such as security and inspection, environmental monitoring, warfare, and other situations especially where immediate responses are required such as disasters and medical emergency. Whenever there is a growth there are challenges and to cope with these challenges strategies and solutions must be developed. This paper discusses the recently addressed issues of data aggregation through presenting a comparative study of different research work done on minimizing delay in different structures of wireless sensor networks. Finally we introduce our proposed method to minimize both delay and power consumption using a tree based clustering scheme with partial data aggregation.
    • De-smokeGCN: Generative Cooperative Networks for Joint Surgical Smoke Detection and Removal

      Chen, Long; Tang, Wen; John, Nigel W.; Wan, Tao Ruan; Zhang, Jian Jun; Bournemouth University; University of Chester; University of Bradford (IEEE XPlore, 2019-11-15)
      Surgical smoke removal algorithms can improve the quality of intra-operative imaging and reduce hazards in image-guided surgery, a highly desirable post-process for many clinical applications. These algorithms also enable effective computer vision tasks for future robotic surgery. In this paper, we present a new unsupervised learning framework for high-quality pixel-wise smoke detection and removal. One of the well recognized grand challenges in using convolutional neural networks (CNNs) for medical image processing is to obtain intra-operative medical imaging datasets for network training and validation, but availability and quality of these datasets are scarce. Our novel training framework does not require ground-truth image pairs. Instead, it learns purely from computer-generated simulation images. This approach opens up new avenues and bridges a substantial gap between conventional non-learning based methods and which requiring prior knowledge gained from extensive training datasets. Inspired by the Generative Adversarial Network (GAN), we have developed a novel generative-collaborative learning scheme that decomposes the de-smoke process into two separate tasks: smoke detection and smoke removal. The detection network is used as prior knowledge, and also as a loss function to maximize its support for training of the smoke removal network. Quantitative and qualitative studies show that the proposed training framework outperforms the state-of-the-art de-smoking approaches including the latest GAN framework (such as PIX2PIX). Although trained on synthetic images, experimental results on clinical images have proved the effectiveness of the proposed network for detecting and removing surgical smoke on both simulated and real-world laparoscopic images.
    • Dead-zone logic in autonomic systems

      Eze, Thaddeus; Anthony, Richard; University of Chester and University of Greenwich (IEEE, 2014-07-31)
      Dead-Zone logic is a mechanism to prevent autonomic managers from unnecessary, inefficient and ineffective control brevity when the system is sufficiently close to its target state. It provides a natural and powerful framework for achieving dependable self-management in autonomic systems by enabling autonomic managers to smartly carry out a change (or adapt) only when it is safe and efficient to do so-within a particular (defined) safety margin. This paper explores and evaluates the performance impact of dead-zone logic in trustworthy autonomic computing. Using two case example scenarios, we present empirical analyses that demonstrate the effectiveness of dead-zone logic in achieving stability, dependability and trustworthiness in adaptive systems. Dynamic temperature target tracking and autonomic datacentre resource request and allocation management scenarios are used. Results show that dead-zone logic can significantly enhance the trustability of autonomic systems.