213 research outputs found

    Longer Than a Telephone Wire - Voice Firewalls to Counter Ubiquitous Lie Detection

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    Mobile computing and communication devices are open to surreptitious privacy attacks using emotion detection techniques; largely utilising work carried out in the area of voice stress analysis (VSA). This paper extends some work in the area of removing emotion cues in the voice, specifically focusing on lie detection and presents the results of a pilot study indicating that the use of mobile phones in situations of stress is common and that awareness of VSA is low. Existing strategies for the removal or modification of emotion cues, based on models of synthesis are considered and weaknesses are identified

    A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users

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    There are many scenarios in which it is necessary to collect data from multiple sources in order to evaluate a system, including the collection of both quantitative data - from sensors and smart devices - and qualitative data - such as observations and interview results. However, there are currently very few systems that enable both of these data types to be combined in such a way that they can be analysed side-by-side. This paper describes an end-to-end system for the collection, analysis, storage and visualisation of qualitative and quantitative data, developed using the e-Science Central cloud analytics platform. We describe the experience of developing the system, based on a case study that involved collecting data about the built environment and its users. In this case study, data is collected from older adults living in residential care. Sensors were placed throughout the care home and smart devices were issued to the residents. This sensor data is uploaded to the analytics platform and the processed results are stored in a data warehouse, where it is integrated with qualitative data collected by healthcare and architecture researchers. Visualisations are also presented which were intended to allow the data to be explored and for potential correlations between the quantitative and qualitative data to be investigated

    The Object Shop – Using CD-ROM Multimedia To Introduce Object Concepts

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    This paper describes key features of a new multimedia CD-ROM pack produced by television makers in collaboration with computer science educators – by the BBC for the Open University Computing Department. The pack, The Object Shop, forms an early component of an undergraduate course which introduces object-oriented computing and software development to students new to computing. Building on the results of empirical evaluation, The Object Shop has been designed to help students with no programming experience to understand core object programming concepts. Throughout the CD-ROM, video, animated graphics and an underlying object-oriented simulation of a virtual shopping environment provide an accessible introduction to the central ideas of object-oriented programming. The key power of the multimedia approach is that the student-user is able to gain a sound operational understanding of concepts before learning the details of programming code or syntax. Users can continually monitor their progress through a series of task-based, assessed exercises

    Employing Object Technology to Expose Fundamental Object Concepts

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    We explore technical issues in the design of programming tools, development environments, simulations, code examples, user interface frameworks and pedagogies for a university-level course on object-oriented software development. The course, M206 Computing: An Object-Oriented Approach has been specifically developed for distance learning, and is enrolling over 5,000 students per year (average age 37) in the UK, Europe and Singapore. The course introduces computing via an object-oriented approach. M206 is substantial in extent representing one sixth of a degree. It embodies a practical, industry oriented view of computing and includes programming, analysis, design and group working. Considerable effort has been invested in making the simplicity, consistency and power of object technology accessible to and capable of being applied by beginners. A diverse set of educational media, such as CD-ROMs, TV and the Web, have been deployed as learning resources. We describe the agenda for the course; its object-oriented pedagogy and our strategy for delivery. We explain measures taken to avoid misconceptions about objects, our analysis and design method, and the Smalltalk programming environment we have developed specifically for learners and which is crucial to our approach. We outline how our adherence to the separation of view and domain model leads to technical innovations. Concluding remarks reflect on the benefits a reflexive strategy, both in education and training

    Avoiding Object Misconceptions

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    This paper identifies and describes a number of misconceptions observed in students learning about object technology, It identifies simple, concrete, measures course designers and teachers can take to avoid these misconceptions arising. The context for this work centres on an introductory undergraduate course and a postgraduate course, Both these courses are taught by distance education. These courses both use Smalltalk as an introduction to object technology. More particularly, the undergraduate course uses Smalltalk as a first programming language. Distance education can limit the amount and speed of individual feedback that can be given in the early stages of learning. For this reason, particular attention has been paid to characterizing measures for avoiding elementary misconceptions seen in beginning learners. At the same time we also address some misconceptions observed in postgraduate students. The pedagogical issues discussed are of particular importance when devising an extended series of examples for teaching or assessment, or when designing a visual microworld to be used for teaching purposes

    Exploring the impact of autonomous taxis on people with disabilities

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    Over the past two decades, transportation has become more accessible, but people with disabilities still face significant barriers to accessing these services. This research focuses on the impact of autonomous taxis on people with disabilities, an area that has seen limited improvement. The study aims to answer two research questions: 1) How do traditional taxi experiences shape expectations of autonomous taxis in terms of disability accessibility? 2) To what extent does the autonomy of self-driving taxis contribute to a perceived increase in travel freedom? Thirty-two semi-structured interviews were conducted with administrative staff from disability organizations, and the perspectives of 39,079 organization members were included. Thematic and sentiment analyses were applied to analyse the findings, which revealed three main themes: onboarding, in-vehicle conditions, and offboarding. The absence of a driver was strongly correlated with a positive sentiment of increased travel freedom, indicating that autonomous taxis could provide enhanced accessibility without the limitations or biases associated with traditional taxis. Participants expressed concerns about driver attitudes and behaviour as negative experiences with traditional taxis. In contrast, with autonomous taxis, their main concern was the availability of human assistance to meet specific user needs throughout the journey. This study emphasizes the necessity for further research into the diverse and intricate spectrum of disabilities, as well as the importance of user-centric market research in the design process. Such research is crucial in achieving the overarching goal of improved accessibility

    Using fNIRS to Verify Trust in Highly Automated Driving

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    Trust in automation is crucial for the safe and appropriate adoption of automated driving technology. Current research methods to measure trust mainly rely on subjective scales, with several intrinsic limitations. This empirical experiment proposes a novel method to measure trust objectively, using functional near-infrared spectroscopy (fNIRS). Through manipulating participants’ expectations regarding driving automation credibility, we have induced and successfully measured opposing levels of trust in automation. Most notably, our results evidence two separate yet interrelated cortical mechanisms for trust and distrust. Trust is demonstrably linked to decreased monitoring and working memory, whereas distrust is event-related and strongly tied to affective (or emotional) mechanisms. This paper evidence that trust in automation and situation awareness are strongly interrelated during driving automation usage. Our findings are crucial for developing future driver state monitoring technology that mitigates the impact of inappropriate reliance, or over trust, in automated driving systems
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