2,219 research outputs found

    Adaptive online/offline RFID scheme for supply chain management systems

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    Ultra-lightweight Mutual Authentication Protocols: Weaknesses and Countermeasures

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    Metagenomic sequencing unravels gene fragments with phylogenetic signatures of O2-tolerant NiFe membrane-bound hydrogenases in lacustrine sediment

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    Many promising hydrogen technologies utilising hydrogenase enzymes have been slowed by the fact that most hydrogenases are extremely sensitive to O2. Within the group 1 membrane-bound NiFe hydrogenase, naturally occurring tolerant enzymes do exist, and O2 tolerance has been largely attributed to changes in iron–sulphur clusters coordinated by different numbers of cysteine residues in the enzyme’s small subunit. Indeed, previous work has provided a robust phylogenetic signature of O2 tolerance [1], which when combined with new sequencing technologies makes bio prospecting in nature a far more viable endeavour. However, making sense of such a vast diversity is still challenging and could be simplified if known species with O2-tolerant enzymes were annotated with information on metabolism and natural environments. Here, we utilised a bioinformatics approach to compare O2-tolerant and sensitive membrane-bound NiFe hydrogenases from 177 bacterial species with fully sequenced genomes for differences in their taxonomy, O2 requirements, and natural environment. Following this, we interrogated a metagenome from lacustrine surface sediment for novel hydrogenases via high-throughput shotgun DNA sequencing using the Illumina™ MiSeq platform. We found 44 new NiFe group 1 membrane-bound hydrogenase sequence fragments, five of which segregated with the tolerant group on the phylogenetic tree of the enzyme’s small subunit, and four with the large subunit, indicating de novo O2-tolerant protein sequences that could help engineer more efficient hydrogenases

    Weighted p-bits for FPGA implementation of probabilistic circuits

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    Probabilistic spin logic (PSL) is a recently proposed computing paradigm based on unstable stochastic units called probabilistic bits (p-bits) that can be correlated to form probabilistic circuits (p-circuits). These p-circuits can be used to solve problems of optimization, inference and also to implement precise Boolean functions in an "inverted" mode, where a given Boolean circuit can operate in reverse to find the input combinations that are consistent with a given output. In this paper we present a scalable FPGA implementation of such invertible p-circuits. We implement a "weighted" p-bit that combines stochastic units with localized memory structures. We also present a generalized tile of weighted p-bits to which a large class of problems beyond invertible Boolean logic can be mapped, and how invertibility can be applied to interesting problems such as the NP-complete Subset Sum Problem by solving a small instance of this problem in hardware

    Matching pursuit-based compressive sensing in a wearable biomedical accelerometer fall diagnosis device

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    There is a significant high fall risk population, where individuals are susceptible to frequent falls and obtaining significant injury, where quick medical response and fall information are critical to providing efficient aid. This article presents an evaluation of compressive sensing techniques in an accelerometer-based intelligent fall detection system modelled on a wearable Shimmer biomedical embedded computing device with Matlab. The presented fall detection system utilises a database of fall and activities of daily living signals evaluated with discrete wavelet transforms and principal component analysis to obtain binary tree classifiers for fall evaluation. 14 test subjects undertook various fall and activities of daily living experiments with a Shimmer device to generate data for principal component analysis-based fall classifiers and evaluate the proposed fall analysis system. The presented system obtains highly accurate fall detection results, demonstrating significant advantages in comparison with the thresholding method presented. Additionally, the presented approach offers advantageous fall diagnostic information. Furthermore, transmitted data accounts for over 80% battery current usage of the Shimmer device, hence it is critical the acceleration data is reduced to increase transmission efficiency and in-turn improve battery usage performance. Various Matching pursuit-based compressive sensing techniques have been utilised to significantly reduce acceleration information required for transmission.Scopu
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