10,013 research outputs found

    An experimental validation of the fatigue damaging events extracted using the wavelet bump extraction (WBE) algorithm

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    This paper describes an experimental validation of the fatigue damaging events that were identified and extracted using a wavelet-based fatigue data editing technique. This technique, known as the Wavelet Bump Extraction (WBE) algorithm, is specifically designed to summarise a long record of fatigue variable amplitude (VA) loading whilst preserving the original load cycle sequence. Using WBE the fatigue damaging events were identified and extracted in order to produce a mission signal. In order to validate the effectiveness of WBE in practical applications a VA road load time history that was measured on a road vehicle suspension arm was taken as a case study. Uniaxial fatigue tests were performed using the original signal, the WBE mission signal and the individual WBE extracted segments. A mirror polished specimen of SAE 1042 steel was tested using a servo-hydraulic machine. The fatigue lives measured for these VA loadings were then compared to the fatigue lives calculated from a VA strain loading fatigue damage model. The results show a good fatigue life correlation at the coefficient of 0.98 between the prediction and experiment. For the road load time history considered, the WBE mission signal was found to be only 40% the time duration of the original time history while maintaining 60% of the fatigue damage according to analytical calculation and 87% according to experimental testing

    Bump extraction algorithm for variable amplitude fatigue loading

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    This paper presents the development of a fatigue mission synthesis algorithm, called Wavelet Bump Extraction (WBE), for summarising long records of fatigue road load data. This algorithm is used to extract fatigue damaging events or bumps in the record that cause the majority of the fatigue damage, whilst preserving the load cycle sequences. Bumps are identified from characteristic frequency bands in the load spectrum using the 12th order Daubechies wavelet. The bumps are combined to produce a mission signal which has equivalent signal statistics and fatigue damage to the original signal. The WBE accuracy has been evaluated by observing the cycle sequence effects of the bump loadings. The WBE was compared with the time domain fatigue data editing method, so that the effectiveness of WBE can be verified. Using WBE, a substantial compression of the load-time history could be achieved for the purpose of accelerated fatigue tests in the automotive industry

    Power-Law Distributions in a Two-sided Market and Net Neutrality

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    "Net neutrality" often refers to the policy dictating that an Internet service provider (ISP) cannot charge content providers (CPs) for delivering their content to consumers. Many past quantitative models designed to determine whether net neutrality is a good idea have been rather equivocal in their conclusions. Here we propose a very simple two-sided market model, in which the types of the consumers and the CPs are {\em power-law distributed} --- a kind of distribution known to often arise precisely in connection with Internet-related phenomena. We derive mostly analytical, closed-form results for several regimes: (a) Net neutrality, (b) social optimum, (c) maximum revenue by the ISP, or (d) maximum ISP revenue under quality differentiation. One unexpected conclusion is that (a) and (b) will differ significantly, unless average CP productivity is very high

    Effects of cold water immersion on muscle oxygenation during repeated bouts of fatiguing exercise : a randomized controlled study

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    2015-2016 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    FSL-BM: Fuzzy Supervised Learning with Binary Meta-Feature for Classification

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    This paper introduces a novel real-time Fuzzy Supervised Learning with Binary Meta-Feature (FSL-BM) for big data classification task. The study of real-time algorithms addresses several major concerns, which are namely: accuracy, memory consumption, and ability to stretch assumptions and time complexity. Attaining a fast computational model providing fuzzy logic and supervised learning is one of the main challenges in the machine learning. In this research paper, we present FSL-BM algorithm as an efficient solution of supervised learning with fuzzy logic processing using binary meta-feature representation using Hamming Distance and Hash function to relax assumptions. While many studies focused on reducing time complexity and increasing accuracy during the last decade, the novel contribution of this proposed solution comes through integration of Hamming Distance, Hash function, binary meta-features, binary classification to provide real time supervised method. Hash Tables (HT) component gives a fast access to existing indices; and therefore, the generation of new indices in a constant time complexity, which supersedes existing fuzzy supervised algorithms with better or comparable results. To summarize, the main contribution of this technique for real-time Fuzzy Supervised Learning is to represent hypothesis through binary input as meta-feature space and creating the Fuzzy Supervised Hash table to train and validate model.Comment: FICC201

    Ablation of neuropilin 1 from glioma-associated microglia and macrophages slows tumor progression

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    Gliomas are the most commonly diagnosed primary tumors of the central nervous system (CNS). Median times of survival are dismal regardless of the treatment approach, underlying the need to develop more effective therapies. Modulation of the immune system is a promising strategy as innate and adaptive immunity play important roles in cancer progression. Glioma associated microglia and macrophages (GAMs) can comprise over 30% of the cells in glioma biopsies. Gliomas secrete cytokines that suppress the anti-tumorigenic properties of GAMs, causing them to secrete factors that support the tumor's spread and growth. Neuropilin 1 (Nrp1) is a transmembrane receptor that in mice both amplifies pro-angiogenic signaling in the tumor microenvironment and affects behavior of innate immune cells. Using a Cre-lox system, we generated mice that lack expression of Nrp1 in GAMs. We demonstrate, using an in vivo orthotopic glioma model, that tumors in mice with Nrp1-deficient GAMs exhibit less vascularity, grow at a slower pace, and are populated by increased numbers of anti-tumorigenic GAMs. Moreover, glioma survival times in mice with Nrp1-deficient GAMs were significantly longer. Treating wild-type mice with a small molecule inhibitor of Nrp1's b1 domain, EG00229, which we show here is selective for Nrp1 over Nrp2, yielded an identical outcome. Nrp1-deficient or EG00229-treated wild-type microglia exhibited a shift towards anti-tumorigenicity as evident by altered inflammatory marker profiles in vivo and decreased SMAD2/3 activation when conditioned in the presence of glioma-derived factors. These results provide support for the proposal that pharmacological inhibition of Nrp1 constitutes a potential strategy for suppressing glioma progression

    Separation between coherent and turbulent fluctuations. What can we learn from the Empirical Mode Decomposition?

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    The performances of a new data processing technique, namely the Empirical Mode Decomposition, are evaluated on a fully developed turbulent velocity signal perturbed by a numerical forcing which mimics a long-period flapping. First, we introduce a "resemblance" criterion to discriminate between the polluted and the unpolluted modes extracted from the perturbed velocity signal by means of the Empirical Mode Decomposition algorithm. A rejection procedure, playing, somehow, the role of a high-pass filter, is then designed in order to infer the original velocity signal from the perturbed one. The quality of this recovering procedure is extensively evaluated in the case of a "mono-component" perturbation (sine wave) by varying both the amplitude and the frequency of the perturbation. An excellent agreement between the recovered and the reference velocity signals is found, even though some discrepancies are observed when the perturbation frequency overlaps the frequency range corresponding to the energy-containing eddies as emphasized by both the energy spectrum and the structure functions. Finally, our recovering procedure is successfully performed on a time-dependent perturbation (linear chirp) covering a broad range of frequencies.Comment: 23 pages, 13 figures, submitted to Experiments in Fluid
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