33,605 research outputs found

    User-centric Privacy Engineering for the Internet of Things

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    User privacy concerns are widely regarded as a key obstacle to the success of modern smart cyber-physical systems. In this paper, we analyse, through an example, some of the requirements that future data collection architectures of these systems should implement to provide effective privacy protection for users. Then, we give an example of how these requirements can be implemented in a smart home scenario. Our example architecture allows the user to balance the privacy risks with the potential benefits and take a practical decision determining the extent of the sharing. Based on this example architecture, we identify a number of challenges that must be addressed by future data processing systems in order to achieve effective privacy management for smart cyber-physical systems.Comment: 12 Page

    Conceptual information processing: A robust approach to KBS-DBMS integration

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    Integrating the respective functionality and architectural features of knowledge base and data base management systems is a topic of considerable interest. Several aspects of this topic and associated issues are addressed. The significance of integration and the problems associated with accomplishing that integration are discussed. The shortcomings of current approaches to integration and the need to fuse the capabilities of both knowledge base and data base management systems motivates the investigation of information processing paradigms. One such paradigm is concept based processing, i.e., processing based on concepts and conceptual relations. An approach to robust knowledge and data base system integration is discussed by addressing progress made in the development of an experimental model for conceptual information processing

    AVEID: Automatic Video System for Measuring Engagement In Dementia

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    Engagement in dementia is typically measured using behavior observational scales (BOS) that are tedious and involve intensive manual labor to annotate, and are therefore not easily scalable. We propose AVEID, a low cost and easy-to-use video-based engagement measurement tool to determine the engagement level of a person with dementia (PwD) during digital interaction. We show that the objective behavioral measures computed via AVEID correlate well with subjective expert impressions for the popular MPES and OME BOS, confirming its viability and effectiveness. Moreover, AVEID measures can be obtained for a variety of engagement designs, thereby facilitating large-scale studies with PwD populations

    BlogForever D2.6: Data Extraction Methodology

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    This report outlines an inquiry into the area of web data extraction, conducted within the context of blog preservation. The report reviews theoretical advances and practical developments for implementing data extraction. The inquiry is extended through an experiment that demonstrates the effectiveness and feasibility of implementing some of the suggested approaches. More specifically, the report discusses an approach based on unsupervised machine learning that employs the RSS feeds and HTML representations of blogs. It outlines the possibilities of extracting semantics available in blogs and demonstrates the benefits of exploiting available standards such as microformats and microdata. The report proceeds to propose a methodology for extracting and processing blog data to further inform the design and development of the BlogForever platform

    Information and modeling issues in designing water and sanitation subsidy schemes

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    In designing a rational scheme for subsidizing water services, it is important to support the choice of design parameters with empirical analysis that stimulates the impact of subsidy options on the target population. Otherwise, there is little guarantee that the subsidy program will meet its objectives. But such analysis is informationally demanding. Ideally, researchers should have access to a single, consistent data set containing household-level information on consumption, willingness to pay, and a range of socioeconomic characteristics. Such a comprehensive data set will rarely exist. The authors suggest overcoming this data deficiency by collating, and imaginatevily manipulating different sources of data to generate estimates of the missing variables. The most valuable sources of information, they explain, are likely to be the following: 1) Customer databases of the water company, which provide robust information on the measured consumption of formal customers, but little information on unmeasured consumption, informal customers, willingness to pay, or socioeconomic variables. 2) General socioeconomic household surveys, which are an excellent source of socioeconomic information, but tend to record water expenditure rather than physical consumption. 3) Willingness-to-pay surveys, which are generally tailored to a specific project, are very flexible, and may be the only source of willingness-to-pay data. However, they are expensive to undertake, and the information collected is based on hypothetical rather than real behavior. Where such surveys are unavailable, international benchmark values on willingness to pay may be used. Combining data sets requires some effort and creativity, and creates difficulties of its own. But once a suitable data set has been constructed, a simulation model can be created using simple spreadsheet software. The model used to design Panama's water subsidy proposal addressed these questions: a) What are the targeting properties of different eligibility criteria for the subsidy? b) How large should the subsidy be? c) How much will the subsidy scheme cost, including administrative costs? Armed with the above information, policymakers should be in a position to design a subsidy program that reaches the intended beneficiaries, provides them with the level of financial support that is strictly necessary, meets the overall budget restrictions, and does not waste an excessive amount of funding on administrative costs.Water Conservation,Environmental Economics&Policies,Health Economics&Finance,Economic Theory&Research,Decentralization,Water Supply and Sanitation Governance and Institutions,Economic Theory&Research,Environmental Economics&Policies,Town Water Supply and Sanitation,Health Economics&Finance

    Provenance-based validation of E-science experiments

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    E-Science experiments typically involve many distributed services maintained by different organisations. After an experiment has been executed, it is useful for a scientist to verify that the execution was performed correctly or is compatible with some existing experimental criteria or standards. Scientists may also want to review and verify experiments performed by their colleagues. There are no existing frameworks for validating such experiments in today's e-Science systems. Users therefore have to rely on error checking performed by the services, or adopt other ad hoc methods. This paper introduces a platform-independent framework for validating workflow executions. The validation relies on reasoning over the documented provenance of experiment results and semantic descriptions of services advertised in a registry. This validation process ensures experiments are performed correctly, and thus results generated are meaningful. The framework is tested in a bioinformatics application that performs protein compressibility analysis
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