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Power is increasingly becoming a design constraint for embedded systems. Dynamic Power Management algorithms enable optimal utilization of hardware at runtime. The present work attempts to arrive at an optimal policy to reduce the energy consumption at system level, by selectively placing components into low power states. A new, simple algorithm for power management systems involving multiple requests and services, proposed here, has been obtained from stochastic queuing models. The proposed policy is event driven and based on a Deterministic Markov Nonstationary Policy model (DMNSP). The proposed policy has been tested using a Java-based event driven simulator. The test results show that there is about 23% minimum power saving over the existing schemes with less impact on performance or reliability.

Characterization of the wave reflection and mainly its return time has significant clinical value in detecting cardiovascular and cerebrovascular diseases. Indeed, the return time is an indicator which is used to evaluate the performance of peripheral perfusion and the propagation speed for arterial stiffness measurement. The study is aimed at implementing a novel model based on cepstral analysis for estimation of the arrival time of reflected wave ($t_0)$. The proposed method is specially based on cepstral analysis of the simulated blood velocity wave by using the Matlab software. To achieve this aim, we used a theoretical bidimensional model to simulate blood flow velocity, and we combined this model with clinical data acquired in two healthy subjects using phase contrast magnetic resonance imaging (PCMRI). Values of the arrival time of reflected wave measured are similar to the theoretical values. The suggested model is validated in vivo. We can conclude that the novel approach described in this paper offers a promising efficient and convenient method to determinate noninvasively arrival time of reflected wave.

The 2010 Chile tsunami had different effects along the Chilean coast. Seawater surged hundred meters into many rivers, though field surveys showed that the 2 km wide Biobio River did not experience any flooding. In a similar manner, the coastal zones south of the river had an inundation height of less than 2 m. To ascertain why these areas were not greatly affected by the event, the behavior of tsunami waves propagating over a submarine canyon was investigated by means of numerical simulations over a simplified and idealized bathymetry. The main variables which define the size of the canyon were varied, and three different tsunami wave lengths were tested. The results show that submarine canyons have a strong influence on tsunami propagation and run-up such that there is a spatial variation of wave amplitude along the coast and this behavior is very sensitive to the canyon size. The run-up directly behind the canyon is lower than in the case without the canyon, while there are zones of wave amplification at both sides of the canyon. These idealized results compare well with what happened during the 2010 Chile tsunami, and provide a useful insight into the behavior of tsunamis around other submarine canyons in other regions of the world.

Local wave speed plays an interesting role in investigating cardiovascular diseases and arterial wall stiffness. The aim of this study was to implement a novel method based on cepstral analysis for noninvasive determination of local wave speed in the carotid artery. To show the precision of the proposed method, we specially focused on the effect of age. In addition, we intended to compare the obtained results to those obtained by the foot-to-foot method. Our method consists in measuring the instantaneous blood velocity in the internal carotid by using phase-contrast magnetic resonance imaging in 20 healthy subjects distributed as follows: 10 young subjects aged between 22 and 41 years, and 10 old subjects aged between 50 and 86 years. The cepstral analysis was used to determine the arrival time of the reflection wave and the wave speed in the carotid artery. A statistical test analysis was conducted in order to establish the relation between the wave speed and the age in the sample under investigation. Our main finding was that there was a high significant difference between the two groups forming the studied sample ($p<0.001$). In terms of the internal carotid arterial branch, our experimental results were in total agreement with reference values by the invasive method reported in the literature. Moreover, the wave speed detected using our method correlated with that detected using foot-to-foot analysis ($R=0.84$, $p<0.001$). We can conclude that the new technique described in this paper offers a promising, convenient and efficient method to measure wave speed noninvasively.

Oceanic ridges could act as waveguides transferring tsunami energy to thousands of kilometers away, pumping large energy in to far-field regions as a secondary source. The shallow-water wave velocity $c={(gh)}^{1/2}$ can only predict the arrival time of the early signals accurately but can hardly estimate that of ridge-trapped waves. The present study provides a fast analytic prediction method to estimate the arrival time of the subsequent large trapped waves. The method is based on the energy velocity solution of trapped waves over the uniform parabolic-shaped submerged ridge. Records of two-tide gauge stations, located nearby Sand Island and Nawiliwili for the 2011 Tohoku tsunami are chosen to illustrate the application of this method. The Sand Island record shows typical open-ocean island characteristics that the maximum wave height is followed by rapid amplitude decay. While the Nawiliwili record is strongly affected by topographical trapping effect of the Hawaii Ridge, and several subsequent wave trains carrying large energy arrive within one day duration. Further investigations show that the present analytic method is able to estimate the arrival time for these distinguished subsequent trains.