7,626 research outputs found

    Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

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    © 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

    A Framework for Responsive Environments

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    In this paper, we define Responsive Environments as adaptive ven- ues that possess context awareness, deliver ubiquitous computing and natural interaction. They also yield a pre-determined User Experience. We propose a framework for the development and assessment of such environments and we discuss applying the framework to some examples. Highlighting benefits and usefulness of the framework

    Research challenges in applying intelligent wireless sensors in the oil, gas and resources industries

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    The monitoring of oil, gas and resources plant performance and the operational environment through sensors allows for greater insight into potential safety problems and operational requirements. Such solutions promote a safe and healthy work environment for all stakeholders and optimized operations. Intelligent techniques and the monitoring of key historical operational properties can be used to realize certain characteristics and patterns in operation data. Such solutions may enhance operational visualization, foresight, forecasting and maintenance schedules for effective and efficient operation and maintenance. This optimizes plant safety, production, turnarounds, shutdowns and maintenance and improves error tolerance and recovery.However, the development of robust devices that are able to perform in these remote and hostile requirements along with the intelligent solutions to structure, store, process and retrieve this information are difficult to realize. This paper investigates the use of wireless sensors and the related intelligent solutions in the oil, gas and resource industries

    A Framework for Responsive Environments

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    In this paper, we define Responsive Environments as adaptive ven- ues that possess context awareness, deliver ubiquitous computing and natural interaction. They also yield a pre-determined User Experience. We propose a framework for the development and assessment of such environments and we discuss applying the framework to some examples. Highlighting benefits and usefulness of the framework

    Analysis and verification of ECA rules in intelligent environments

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    Intelligent Environments (IEs) are physical spaces where Information Technology (IT) and other pervasive computing technologies are combined in order to achieve specific goals for the users and the environment. IEs have the goal of enriching user experience, increasing awareness of the environment. A number of applications are currently being deployed in domains ranging from smart homes to e-health and autonomous vehicles. Quite often IE support human activities, thus essential requirements to be ensured are correctness, reliability, safety and security. In this paper we present how a set of techniques and tools that have been developed for the verification of software can be employed in the verification of IE described by means of event-condition-action rules. More precisely, we reduce the problem of verifying key properties of these rules to satisfiability and termination problems that can be addressed using state-of-the-art Satisfiability Modulo Theory (SMT) solvers and program analysers. Our approach has been implemented in a tool called vIRONy. Our approach has been validated on a number of case studies from the literature

    Immersive simulations with extreme teams

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    Extreme teams (ETs) work in challenging, high pressured contexts, where poor performance can have severe consequences. These teams must coordinate their skill sets, align their goals, and develop shared awareness, all under stressful conditions. How best to research these teams poses unique challenges as researchers seek to provide applied recommendations while conducting rigorous research to test how teamwork models work in practice. In this article, we identify immersive simulations as one solution to this, outlining their advantages over existing methodologies and suggesting how researchers can best make use of recent advances in technology and analytical techniques when designing simulation studies. We conclude that immersive simulations are key to ensuring ecological validity and empirically reliable research with ETs
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