Retrieving the parameters in water quality with multispectral data using neural network is increasingly popular, however,
the training process with large amount samples and calculation with large-volume data are a time-consuming work.
Many emergency pollution events need quick responses for practical use. In this paper, an improved membrane
computing strategy is presented. This strategy is a hybrid one combining the framework and evolution rules of P systems
with active membranes and neural networks, and it involves a dynamic structure including membrane fusion and
division, which helpful to enhance the information communication and beneficial to reduce the computation. Then, a
parallel implementation with the training result is discussed. Experiments with Landsat datasets to obtain suspended
sediment are carried out to demonstrate the practical capabilities of this introduced strategy.
KEYWORDS: Visualization, Data modeling, Visual analytics, Geographic information systems, Human-machine interfaces, 3D modeling, Analytical research, Visual process modeling, Data acquisition, Systems modeling
Storm Surge is one kind of serious natural disasters coming from the sea, for the sudden reduction in atmospheric
pressure and the destruction of the following strong winds, it often imposes huge damage on coastal regions. Many
systems have been developed for the simulation and prediction of storm surges in the last decade. Though they have
powerful simulating and calculating capability, it is far from enough to research on the way to express spatio-temporal
data and provide the interactive visualized analysis efficiently and thoroughly. GIS as an effective tool could visualize
temporal and spatial processes and analyze spatial data. Thus the way to integrate Storm Surge prediction system with
GIS would be helpful to resolve the upper problem. According to the characteristic of Taiwan Strait, a validated
numerical mode for storm surge along Fujian coast was selected. Using the data acquired from observation stations and
applying a new visualizing technique for multi-dimensional data, we developed a fast forecasting and warning system.
Based on a symmetry spiral coordinate system, this visualizing model for multi-dimensional data utilizes the unique
rotation factor and the symmetrical projection feature of spiral line, arrange each dimensional data along spatial and
symmetrical spiral line. The observations obtained along Fujian coastal region in 2006 are verified and simulated by the
visualized analyzing system.
In recent years the authors have engaged in the development of a special technology to optimally modify a structure's physical parameters (mass, damping and stiffness) in time- dependent loading conditions. Specific efforts have been devoted to reduce structural responses under seismic loading. In this regard, there are many other research activities dealing with different devices and control algorithms generally classified in the following categories: passive control, active and hybrid control, adaptive control, semi-active control, etc. All together, this newly emerging field of structural control has generated significant momentum of development. Real-time structural parameter modification (RSPM) is a different approach from the categories mentioned above. A detailed explanation of RSPM is given in the references. In this paper, we discuss a number of fundamental issues facing the development of various structural control technologies. These issues are summarized from our development of RSPM, and are examined based on the view that structural control devices may be considered from only two distinct types: material type and mechanical type. Such a view helps to classify some advantages and disadvantages of different structural protective systems including RSPM.
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