845 resultados para Event-based timing
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A new numerical procedure is proposed to investigate cracking behaviors induced by mismatch between the matrix phase and aggregates due to matrix shrinkage in cement-based composites. This kind of failure processes is simplified in this investigation as a purely spontaneous mechanical problem, therefore, one main difficulty during simulating the phenomenon lies that no explicit external load serves as the drive to propel development of this physical process. As a result, it is different from classical mechanical problems and seems hard to be solved by using directly the classical finite element method (FEM), a typical kind of "load -> medium -> response" procedures. As a solution, the actual mismatch deformation field is decomposed into two virtual fields, both of which can be obtained by the classical FEM. Then the actual response is obtained by adding together the two virtual displacement fields based on the principle of superposition. Then, critical elements are detected successively by the event-by-event technique. The micro-structure of composites is implemented by employing the generalized beam (GB) lattice model. Numerical examples are given to show the effectiveness of the method, and detailed discussions are conducted on influences of material properties.
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This thesis presents theories, analyses, and algorithms for detecting and estimating parameters of geospatial events with today's large, noisy sensor networks. A geospatial event is initiated by a significant change in the state of points in a region in a 3-D space over an interval of time. After the event is initiated it may change the state of points over larger regions and longer periods of time. Networked sensing is a typical approach for geospatial event detection. In contrast to traditional sensor networks comprised of a small number of high quality (and expensive) sensors, trends in personal computing devices and consumer electronics have made it possible to build large, dense networks at a low cost. The changes in sensor capability, network composition, and system constraints call for new models and algorithms suited to the opportunities and challenges of the new generation of sensor networks. This thesis offers a single unifying model and a Bayesian framework for analyzing different types of geospatial events in such noisy sensor networks. It presents algorithms and theories for estimating the speed and accuracy of detecting geospatial events as a function of parameters from both the underlying geospatial system and the sensor network. Furthermore, the thesis addresses network scalability issues by presenting rigorous scalable algorithms for data aggregation for detection. These studies provide insights to the design of networked sensing systems for detecting geospatial events. In addition to providing an overarching framework, this thesis presents theories and experimental results for two very different geospatial problems: detecting earthquakes and hazardous radiation. The general framework is applied to these specific problems, and predictions based on the theories are validated against measurements of systems in the laboratory and in the field.
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Acoustic recorders were used to document black drum (Pogonias cromis) sound production during their spawning season in southwest Florida. Diel patterns of sound production were similar to those of other sciaenid fishes and demonstrated increased sound levels from the late afternoon to early evening—a period that lasted up to 12 hours during peak season. Peak sound production occurred from January through March when water temperatures were between 18° and 22°C. Seasonal trends in sound production matched patterns of black drum reproductive readiness and spawning reported previously for populations in the Gulf of Mexico. Total acoustic energy of nightly chorus events was estimated by integration of the sound pressure amplitude with duration above a threshold based on daytime background levels. Maximum chorus sound level was highly correlated with total acoustic energy and was used to quantitatively represent nightly black drum sound production. This study gives evidence that long-term passive acoustic recordings can provide information on the timing and location of black drum reproductive behavior that is similar to that provided by traditional, more costly methods. The methods and results have broad application for the study of many other fish species, including commercially and recreationally valuable reef fishes that produce sound in association with reproductive behav
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Stomach samples from three rockfish species, yellowtail (Sebastes f lavidus), widow (S. entomelas), and canary (S. pinniger) rockfish, seasonally collected off the Pacific Northwest in 1998 and 1999, provided quantitative information on the food habits of these species during and after the 1997–98 El Niño event. Although euphausiids were the most common major prey of all three predators, gelatinous zooplankton and fishes were the most commonly consumed prey items during some seasonal quarters. The influence of the El Niño event was evident in the diets. Anomalous prey items, including the southern euphausiid species Nyctiphanes simplex and juveniles of Pacific whiting (Merluccius productus) frequently appeared in the diets in the spring and summer of 1998. The results of stomach contents analyses, based on 905 stomach samples from 49 trawl hauls during seven commercial fishing trips and from 56 stations during research surveys, were consistent with the timing of occurrence and the magnitude of change in biomass of some zooplankton species reported from zooplankton studies in the northern California Current during the 1997–98 El Niño. Our findings indicate that the observed variations of prey groups in some rockfish diets may be a function of prey variability related to climate and environment changes.
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Background: The rising temperature of the world’s oceans has become a major threat to coral reefs globally as the severity and frequency of mass coral bleaching and mortality events increase. In 2005, high ocean temperatures in the tropical Atlantic and Caribbean resulted in the most severe bleaching event ever recorded in the basin. Methodology/Principal Findings: Satellite-based tools provided warnings for coral reef managers and scientists, guiding both the timing and location of researchers’ field observations as anomalously warm conditions developed and spread across the greater Caribbean region from June to October 2005. Field surveys of bleaching and mortality exceeded prior efforts in detail and extent, and provided a new standard for documenting the effects of bleaching and for testing nowcast and forecast products. Collaborators from 22 countries undertook the most comprehensive documentation of basin-scale bleaching to date and found that over 80% of corals bleached and over 40% died at many sites. The most severe bleaching coincided with waters nearest a western Atlantic warm pool that was centered off the northern end of the Lesser Antilles. Conclusions/Significance: Thermal stress during the 2005 event exceeded any observed from the Caribbean in the prior 20 years, and regionally-averaged temperatures were the warmest in over 150 years. Comparison of satellite data against field surveys demonstrated a significant predictive relationship between accumulated heat stress (measured using NOAA Coral Reef Watch’s Degree Heating Weeks) and bleaching intensity. This severe, widespread bleaching and mortality will undoubtedly have long-term consequences for reef ecosystems and suggests a troubled future for tropical marine ecosystems under a warming climate
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Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.
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Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.
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Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd. Summary A field programmable gate array (FPGA) based model predictive controller for two phases of spacecraft rendezvous is presented. Linear time-varying prediction models are used to accommodate elliptical orbits, and a variable prediction horizon is used to facilitate finite time completion of the longer range manoeuvres, whilst a fixed and receding prediction horizon is used for fine-grained tracking at close range. The resulting constrained optimisation problems are solved using a primal-dual interior point algorithm. The majority of the computational demand is in solving a system of simultaneous linear equations at each iteration of this algorithm. To accelerate these operations, a custom circuit is implemented, using a combination of Mathworks HDL Coder and Xilinx System Generator for DSP, and used as a peripheral to a MicroBlaze soft-core processor on the FPGA, on which the remainder of the system is implemented. Certain logic that can be hard-coded for fixed sized problems is implemented to be configurable online, in order to accommodate the varying problem sizes associated with the variable prediction horizon. The system is demonstrated in closed-loop by linking the FPGA with a simulation of the spacecraft dynamics running in Simulink on a PC, using Ethernet. Timing comparisons indicate that the custom implementation is substantially faster than pure embedded software-based interior point methods running on the same MicroBlaze and could be competitive with a pure custom hardware implementation.
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In this review, the potential of mode-locked lasers based on advanced quantum-dot ( QD) active media to generate short optical pulses is analysed. A comprehensive review of experimental and theoretical work on related aspects is provided, including monolithic-cavity mode-locked QD lasers and external-cavity mode-locked QD lasers, as well as mode-locked solid-state and fibre lasers based on QD semiconductor saturable absorber mirrors. Performance comparisons are made for state-of-the-art experiments. Various methods for improving important characteristics of mode-locked pulses such as pulse duration, repetition rate, pulse power, and timing jitter through optimization of device design parameters or mode-locking methods are addressed. In addition, gain switching and self-pulsation of QD lasers are also briefly reviewed, concluding with the summary and prospects.
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本文着重研究了工作流中各活动间的定量时序关系,提出了一种分析工作流中时间约束的方法。该方法针对基于ECA规则的工作流,通过建立及分析工作流的约束图,对工作流中活动间定量时序约束的一致性进行了分析,从而保证了工作流的正常运行。
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The times spent by an electron in a scattering event or tunnelling through a potential barrier are investigated using a method based on the absorption probabilities. The reflection and transmission times derived from this method are equal to the local Larmor times if the transmission and reflection probability amplitudes are complex analytic functions of the complex potential. The numerical results show that they coincide with the phase times except as the incident electron energy approaches zero or when the transmission probability is too small. If the imaginary potential covers the whole space the tunnelling times are again equal to the phase times. The results show that the tunnelling times based on absorption probabilities are the best of the various candidates.
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We propose a simple approach to generate a high quality 10 GHz 1.9 ps optical pulse train using a semiconductor optical amplifier and silica-based highly nonlinear fiber. An optical pulse generator based on our proposed scheme is easy to set up with commercially available optical components. A 10 GHz, 1.9 ps optical pulse train is obtained with timing jitter as low as 60 fs over the frequency range 10 Hz-1 MHz. With a wavelength tunable CW laser, a wide wavelength tunable span can be achieved over the entire C band. The proposed optical pulse generator also can operate at different repetition rates from 3 to 10 GHz.
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A conductive carbon ceramic composite electrode (CCE) comprised of cc-type 1:12 phosphomolybdic acid (PMo12) and carbon powder in an organically modified silicate matrix was fabricated using a sol-gel method and characterized by scanning electron microscopy, cyclic voltammetry, and Osteryoung square-wave voltammetry. Osteryoung square-wave voltammograms of the modified electrode immersed in different acidic aqueous solutions present the dependence of current and redox potential on pH. The PMo12-doped CCE shows more reversible reaction kinetics, good stability and reproducibility, especially the renewal repeatability by simple polishing in the event of surface fouling or dopant leaching. Moreover, the modified electrode shows good catalytic activity for the electrochemical reduction of bromate.
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A new type of silicomolybdate-methylsilicate-graphite composite material was prepared by the sol-gel technique and used for the fabrication of an amperometric nitrite sensor. The silicomolybdic anion acts as a catalyst, the graphite powder ensures conductivity by percolation, the silicate provides a rigid porous backbone and the methyl groups endow hydrophobicity and thus limit the wetting section of the modified electrode. Cyclic voltammetry, square-wave voltammetry and chronoamperometry were employed to characterize the sensor. The amperometric nitrite sensor exhibited a series of good properties: high sensitivity (1.771 mu A mmol(-1) dm(3)), a short response time (7 s), remarkable long-term stability and especially reproducibility of surface renewal in the event of electrode surface fouling.