975 resultados para Lee, Spike


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Fil: Vicente, María Eugenia. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

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Fil: Vicente, María Eugenia. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

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Fil: D'Assaro, Adriana. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina.

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Pós-graduação em Letras - IBILCE

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Automated adversarial detection systems can fail when under attack by adversaries. As part of a resilient data stream mining system to reduce the possibility of such failure, adaptive spike detection is attribute ranking and selection without class-labels. The first part of adaptive spike detection requires weighing all attributes for spiky-ness to rank them. The second part involves filtering some attributes with extreme weights to choose the best ones for computing each example’s suspicion score. Within an identity crime detection domain, adaptive spike detection is validated on a few million real credit applications with adversarial activity. The results are F-measure curves on eleven experiments and relative weights discussion on the best experiment. The results reinforce adaptive spike detection’s effectiveness for class-label-free attribute ranking and selection.

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In this paper, hidden Markov models (HMM) is studied for spike sorting. We notice that HMM state sequences have capability to represent spikes precisely and concisely. We build a HMM for spikes, where HMM states respect spike significant shape variations. Four shape variations are introduced: silence, going up, going down and peak. They constitute every spike with an underlying probabilistic dependence that is modelled by HMM. Based on this representation, spikes sorting becomes a classification problem of compact HMM state sequences. In addition, we enhance the method by defining HMM on extracted Cepstrum features, which improves the accuracy of spike sorting. Simulation results demonstrate the effectiveness of the proposed method as well as the efficiency.

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This paper presents an Active Gate Signaling scheme to reduce voltage/current spikes across insulated gate power switches in hard switching power electronic circuits. Voltage and/or current spikes may cause EMI noise. In addition, they increase voltage/current stress on the switch. Traditionally, a higher gate resistance is chosen to reduce voltage/current spikes. Since the switching loss will increase remarkably, an active gate voltage control scheme is developed to improve efficiency of hard switching circuits while the undesirable voltage and/or current spikes are minimized.

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There is a growing body of work that responds to the impact of the rapid uptake of information and communication technology (ICT) on education (Buckingham, 2003; Cheung, 2003; Cuban, 2003; Leung, 2003; Prensky, 2005; Green & Hannon, 2007; Brooks-Gunn & Donahue, 2008; Lyman et al, 2008). Mostly, this work has been positioned in the context of upper-primary or secondary classrooms. More recently, there has been a growing call for research about the impact of ICT on the early years or in early childhood contexts. This text initiates a response to that call. The authors concur that today’s children are a generation who create, learn, work, play and communicate very differently from their parents and teachers (Buckingham, 2003), and that classroom activity needs to reflect this difference.