2,709 research outputs found

    Design of intelligent network components to support multimedia on mobile thin clients

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    QuLa: service selection and forwarding table population in service-centric networking using real-life topologies

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    The amount of services located in the network has drastically increased over the last decade which is why more and more datacenters are located at the network edge, closer to the users. In the current Internet it is up to the client to select a destination using a resolution service (Domain Name System, Content Delivery Networks ...). In the last few years, research on Information-Centric Networking (ICN) suggests to put this selection responsibility at the network components; routers find the closest copy of a content object using the content name as input. We extend the principle of ICN to services; service routers forward requests to service instances located in datacenters spread across the network edge. To solve this problem, we first present a service selection algorithm based on both server and network metrics. Next, we describe a method to reduce the state required in service routers while minimizing the performance loss caused by this data reduction. Simulation results based on real-life networks show that we are able to find a near-optimal load distribution with only minimal state required in the service routers

    On-demand provisioning of long-tail services in distributed clouds

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    Privacy Aware Offloading of Deep Neural Networks

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    Deep neural networks require large amounts of resources which makes them hard to use on resource constrained devices such as Internet-of-things devices. Offloading the computations to the cloud can circumvent these constraints but introduces a privacy risk since the operator of the cloud is not necessarily trustworthy. We propose a technique that obfuscates the data before sending it to the remote computation node. The obfuscated data is unintelligible for a human eavesdropper but can still be classified with a high accuracy by a neural network trained on unobfuscated images.Comment: ICML 2018 Privacy in Machine Learning and Artificial Intelligence worksho

    Van arrangeren tot renseigneren: smaad en geweld van militairen tegen hun oversten tijdens de Eerste Wereldoorlog

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    This article examens two acts of indiscipline (namely violance and outrage against a superior) in the Belgian Army during the First World Wa

    Biosimilar medicines and cost-effectiveness

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    Given that biosimilars are agents that are similar but not identical to the reference biopharmaceutical, this study aims to introduce and describe specific issues related to the economic evaluation of biosimilars by focusing on the relative costs, relative effectiveness, and cost-effectiveness of biosimilars. Economic evaluation assesses the cost-effectiveness of a medicine by comparing the costs and outcomes of a medicine with those of a relevant comparator. The assessment of cost-effectiveness of a biosimilar is complicated by the fact that evidence needed to obtain marketing authorization from a registration authority does not always correspond to the data requirements of a reimbursement authority. In particular, this relates to the availability of adequately powered equivalence or noninferiority studies, the need for comparative data about the effectiveness in a real-world setting rather than the efficacy in a structured setting, and the use of health outcome measures instead of surrogate endpoints. As a biosimilar is likely to be less expensive than the comparator (eg, the reference biopharmaceutical), the assessment of the cost-effectiveness of a biosimilar depends on the relative effectiveness. If appropriately designed and powered clinical studies demonstrate equivalent effectiveness between a biosimilar and the comparator, then a cost-minimization analysis identifies the least expensive medicine. If there are differences in the effectiveness of a biosimilar and the comparator, other techniques of economic evaluation need to be employed, such as cost-effectiveness analysis or cost-utility analysis. Given that there may be uncertainty surrounding the long-term safety (ie, risk of immunogenicity and rare adverse events) and effectiveness of a biosimilar, the cost-effectiveness of a biosimilar needs to be calculated at multiple time points throughout the life cycle of the product
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