83 research outputs found

    High precision hybrid RF and ultrasonic chirp-based ranging for low-power IoT nodes

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    Hybrid acoustic-RF systems offer excellent ranging accuracy, yet they typically come at a power consumption that is too high to meet the energy constraints of mobile IoT nodes. We combine pulse compression and synchronized wake-ups to achieve a ranging solution that limits the active time of the nodes to 1 ms. Hence, an ultra low-power consumption of 9.015 µW for a single measurement is achieved. The operation time is estimated on 8.5 years on a CR2032 coin cell battery at a 1 Hz update rate, which is over 250 times larger than state-of-the-art RF-based positioning systems. Measurements based on a proof-of-concept hardware platform show median distance error values below 10 cm. Both simulations and measurements demonstrate that the accuracy is reduced at low signal-to-noise ratios and when reflections occur. We introduce three methods that enhance the distance measurements at a low extra processing power cost. Hence, we validate in realistic environments that the centimeter accuracy can be obtained within the energy budget of mobile devices and IoT nodes. The proposed hybrid signal ranging system can be extended to perform accurate, low-power indoor positioning

    Constrained least squares detector for OFDM/SDMA-based wireless networks

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    An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 2: impacts on organisms and ecosystems

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    New information on the lethal and sublethal effects of neonicotinoids and fipronil on organisms is presented in this review, complementing the previous WIA in 2015. The high toxicity of these systemic insecticides to invertebrates has been confirmed and expanded to include more species and compounds. Most of the recent research has focused on bees and the sublethal and ecological impacts these insecticides have on pollinators. Toxic effects on other invertebrate taxa also covered predatory and parasitoid natural enemies and aquatic arthropods. Little, while not much new information has been gathered on soil organisms. The impact on marine coastal ecosystems is still largely uncharted. The chronic lethality of neonicotinoids to insects and crustaceans, and the strengthened evidence that these chemicals also impair the immune system and reproduction, highlights the dangers of this particular insecticidal classneonicotinoids and fipronil. , withContinued large scale – mostly prophylactic – use of these persistent organochlorine pesticides has the potential to greatly decreasecompletely eliminate populations of arthropods in both terrestrial and aquatic environments. Sublethal effects on fish, reptiles, frogs, birds and mammals are also reported, showing a better understanding of the mechanisms of toxicity of these insecticides in vertebrates, and their deleterious impacts on growth, reproduction and neurobehaviour of most of the species tested. This review concludes with a summary of impacts on the ecosystem services and functioning, particularly on pollination, soil biota and aquatic invertebrate communities, thus reinforcing the previous WIA conclusions (van der Sluijs et al. 2015)

    Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

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    [This corrects the article DOI: 10.1186/s13054-016-1208-6.]

    Memory-reduced turbo decoding architecture using NII metric compression

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    This brief proposes a new compression technique of next-iteration initialization metrics for relaxing the storage demands of turbo decoders. The proposed scheme stores only the range of state metrics as well as two indexes of the maximum and minimum values, while the previous compression methods have to store all of the state metrics for initializing the following iteration. We also present a hardware-friendly recovery strategy, which can be implemented by simple multiplexing networks. Compared to the previous work, as a result, the proposed compression method reduces the required storage bits by 30% while providing the acceptable error-correcting performance in practice.110sciescopu

    Four model classes for efficient Bayesian selection

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    I consider a binary classification problem with a feature vector of high dimensionality. Spam mail filters are a popular example hereof. A Bayesian approach requires us to estimate the probability of a feature vector given the class of the object. Due to the size of the feature vector this is an unfeasible t ask. A useful approach is to split the feature space into several (conditionally) independent subspaces. This results in a new problem, namely how to find the " best" subdivision. In this paper I consider a weighing approach that will perform (asymptotically) as good as the best subdivision and still has a manageable complexit

    Parallel turbo coding interleavers: avoiding collisions in accesses to storage elements

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