Numerical simulation of condensation of bubbles under microgravity conditions by moving mesh method in the double-staggered grid

A numerical 2D method for simulation of two-phase flows including phase change under microgravity conditions is presented in this paper, with a level set method being coupled with the moving mesh method in the double-staggered grid systems. When the grid lines bend very much in a curvilinear grid, great errors may be generated by using the collocated grid or the staggered grid. So the double-staggered grid was adopted in this paper. The level set method is used to track the liquid-vapor interface. The numerical analysis is fulfilled by solving the Navier-Stokes equations using the SIMPLER method, and the surface tension force is modeled by a continuum surface force approximation. A comparison of the numerical results obtained with different numerical strategies shows that the double-staggered grid moving-mesh method presented in this paper is more accurate than that used previously in the collocated grid system. Based on the method presented in this paper, the condensation of a single bubble in the cold water under different level of gravity is simulated. The results show that the condensation process under the normal gravity condition is different from the condensation process under microgravity conditions. The whole condensation time is much longer under the normal gravity than under the microgravity conditions.

Compression of Chinese document images based on morphologic analysis and pattern matching

We propose a highly efficient content-lossless compression scheme for Chinese document images. The scheme combines morphologic analysis with pattern matching to cluster patterns. In order to achieve the error maps with minimal error numbers, the morphologic analysis is applied to decomposing and recomposing the Chinese character patterns. In the pattern matching, the criteria are adapted to the characteristics of Chinese characters. Since small-size components sometimes can be inserted into the blank spaces of large-size components, we can achieve small-size pattern library images. Arithmetic coding is applied to the final compression. Our method achieves much better compression performance than most alternative methods, and assures content-lossless reconstruction. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

Acceleration of initially moving electrons by a copropagation intense laser pulse

Acceleration of an initially moving electron by a copropagation ultra-short ultra-intense laser pulse in vacuum is studied. It is shown that when appropriate laser pulse parameters and focusing conditions are imposed, the acceleration of electron by ascending front of laser pulse can be much stronger compared to the deceleration by descending part. Consequently, the electron can obtain significantly high net energy gain. We also report the results of the new scheme that enables a second-step acceleration of electron using laser pulses of peak intensity in the range of 10(19)-10(20) W mu m(2)/cm(2). In the first step the electron acceleration from rest is limited to energies of a few MeV, while in the second step the electron acceleration can be considerably enhanced to about 100 MeV energy.

Compression of Chinese document images based on morphologic analysis and pattern matching

We propose a highly efficient content-lossless compression scheme for Chinese document images. The scheme combines morphologic analysis with pattern matching to cluster patterns. In order to achieve the error maps with minimal error numbers, the morphologic analysis is applied to decomposing and recomposing the Chinese character patterns. In the pattern matching, the criteria are adapted to the characteristics of Chinese characters. Since small-size components sometimes can be inserted into the blank spaces of large-size components, we can achieve small-size pattern library images. Arithmetic coding is applied to the final compression. Our method achieves much better compression performance than most alternative methods, and assures content-lossless reconstruction. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

Phase interpretation for polarization-dependent near-field images of high-density gratings

It has been described that the near-field images of a high-density grating at the half self-imaging distance could be different for TE and TM polarization states. We propose that the phases of the diffraction orders play an important role in such polarization dependence. The view is verified through the coincidence of the numerical result of finite-difference time-domain method and the reconstructed results from the rigorous coupled-wave analysis. Field distributions of TE and TM polarizations are given numerically for a grating with period d = 2.3 lambda, which are verified through experiments with the scanning near-field optical microscopy technique. The concept of phase interpretation not only explains the polarization dependence at the half self-imaging distance of gratings with a physical view, but also, it could be widely used to describe the near-field diffraction of a variety of periodic diffractive optical elements whose feature size comparable to the wavelength. (C) 2008 Elsevier B.V. All rights reserved.

Differential amplitude modulation of auditory evoked cortical potentials associated with brain state in the freely moving rhesus monkey

We simultaneously recorded auditory evoked potentials (AEP) from the temporal cortex (TCx), the dorsolateral prefrontal cortex (dPFCx) and the parietal cortex (PCx) in the freely moving rhesus monkey to investigate state-dependent changes of the AEP. AEPs obtained during passive wakefulness, active wakefulness (AW), slow wave sleep and rapid-eye-movement sleep (REM) were compared. Results showed that AEP from all three cerebral areas were modulated by brain states. However, the amplitude of AEP from dPFCx and PCx significantly appeared greater attenuation than that from the TCx during AW and REM. These results indicate that the modulation of brain state on AEP from all three cerebral areas investigated is not uniform, which suggests that different cerebral areas have differential functional contributions during sleep-wake cycle. (C) 2002 Elsevier Science Ireland Ltd.. All rights reserved.

A microelectrode drive for long term recording of neurons in freely moving and chaired monkeys

An electrode drive is described for recordings of neurons in freely moving and chaired monkeys during the performance of behavioural tasks. The electrode drives are implanted for periods of up to 6 months, and can advance up to 42 electrodes using 14 independent drive mechanisms. The drive samples 288 points within a 12 mm x 12 min region, with 15 min of electrode travel. Major advantages are that recordings are made in freely moving monkeys, and these recordings can be compared with those in chaired experiments; waveforms of single neurons are stable, enabling prolonged recordings of the same neurons across periods of days; recordings can be made throughout the brain, including the dorsolateral prefrontal cortex and hippocampus; the drive accommodates both sharp microelectrodes and fine wire assemblies such as tetrodes. (C) 2003 Elsevier Science B.V; All rights reserved.

Spatially directed movement and neuronal activity in freely moving monkey

The abilities to plan a series of movements and to navigate within the environment require the functions of the frontal and ventromedial temporal lobes, respectively. Neuropsychological studies posit the existence of egocentric (prefrontal) and allocentri

Neurophysiological recordings in freely moving monkeys

Recordings of neuronal activity in freely moving rats are common in experiments where electrical signals are transmitted using cables. Such techniques are not common in monkeys because their prehensile abilities are thought to preclude such techniques. Ho

Maze model to study spatial learning and memory in freely moving monkeys

Many types of mazes have been used in cognitive brain research and data obtained from those experiments, especially those from rodents' studies, support the idea that the hippocampus is related to spatial learning and memory. But the results from non-huma

Using the moving window incorporated neural network to forecast the population behavior of Nostocales spp. in the River Darling, Australia

The paper demonstrates the nonstationarity of algal population behaviors by analyzing the historical populations of Nostocales spp. in the River Darling, Australia. Freshwater ecosystems are more likely to be nonstationary, instead of stationary. Nonstationarity implies that only the near past behaviors could forecast the near future for the system. However, nonstionarity was not considered seriously in previous research efforts for modeling and predicting algal population behaviors. Therefore the moving window technique was incorporated with radial basis function neural network (RBFNN) approach to deal with nonstationarity when modeling and forecasting the population behaviors of Nostocales spp. in the River Darling. The results showed that the RBFNN model could predict the timing and magnitude of algal blooms of Nostocales spp. with high accuracy. Moreover, a combined model based on individual RBFNN models was implemented, which showed superiority over the individual RBFNN models. Hence, the combined model was recommended for the modeling and forecasting of the phytoplankton populations, especially for the forecasting.

A shortest path algorithm for moving objects in spatial network databases

One of the most important kinds of queries in Spatial Network Databases (SNDB) to support location-based services (LBS) is the shortest path query. Given an object in a network, e.g. a location of a car on a road network, and a set of objects of interests, e.g. hotels,gas station, and car, the shortest path query returns the shortest path from the query object to interested objects. The studies of shortest path query have two kinds of ways, online processing and preprocessing. The studies of preprocessing suppose that the interest objects are static. This paper proposes a shortest path algorithm with a set of index structures to support the situation of moving objects. This algorithm can transform a dynamic problem to a static problem. In this paper we focus on road networks. However, our algorithms do not use any domain specific information, and therefore can be applied to any network. This algorithm’s complexity is O(klog2 i), and traditional Dijkstra’s complexity is O((i + k)2).

a shortest path algorithm for moving objects in spatial network databases

中国计算机学会