Grid-based Technique Research Articles

Grid-Based Moment Tensor Inversion Technique by Using 3-D Green’s Functions Database: A Demonstration of the 23 October 2004 Taipei Earthquake

Grid-Based Moment Tensor Inversion Technique by Using 3-D Green’s Functions Database: A Demonstration of the 23 October 2004 Taipei Earthquake

3-D Grid-Based Localization Technique in Mobile Sensor Networks

Considering the environmental protection, forest fire becomes a more and more serious problem and requires more concerns. This paper provides an efficient method for fire monitoring and detection in forests using wireless sensor network technology. The proposed technique estimates the location of a sensor node based on the current set of hop-count values, which are collected through the anchor nodes’ broadcast. Our algorithm incorporates two salient features; grid-based output and event-triggering mechanism, to improve the accuracy while reducing the power consumption. Through the computer simulation, the output region obtained from our algorithm can always cover the target node. In addition, the algorithm was implemented and tested with a set of Crossbow sensors. Experimental results demonstrated the high feasibility and worked well in real environment.

Focus+Context Route Zooming and Information Overlay in 3D Urban Environments

In this paper we present a novel focus+context zooming technique, which allows users to zoom into a route and its associated landmarks in a 3D urban environment from a 45-degree bird's-eye view. Through the creative utilization of the empty space in an urban environment, our technique can informatively reveal the focus region and minimize distortions to the context buildings. We first create more empty space in the 2D map by broadening the road with an adapted seam carving algorithm. A grid-based zooming technique is then used to enlarge the landmarks to reclaim the created empty space and thus reduce distortions to the other parts. Finally, an occlusion-free route visualization scheme adaptively scales the buildings occluding the route to make the route always visible to users. Our method can be conveniently integrated into Google Earth and Virtual Earth to provide seamless route zooming and help users better explore a city and plan their tours. It can also be used in other applications such as information overlay to a virtual city.

Development of an Optimization Technique for a Potential Surface of Spatial Urban Growth Using Deterministic Modeling Methodology

This study developed the weighted scenario method (WSM) using the analytic hierarchical process (AHP) method that can optimize the weighting value for multiple criteria to make a grid-based potential surface. The potential surface has been used to simulate urban expansion using distributed cellular automata models and to generate land-use planning as basic data. This study formulated the WSM-AHP method mathematically and applied it to the test region, Suwon City, which is located in the south of Seoul, Korea, with time series land-use maps of 1986 and 1996. The WSM-AHP method generates a potential map for each pair of weighting value for all criteria, one of which is weighted with a high weighting value. The others use a low weighting value, considering that the summation for all criteria weighting values should be “1.” The potential change rate to the step of the weighted scenario for the weighting value of criteria is standardized like the AHP intensity matrix in this study. From the standard potential change rate, the WSM-AHP intensity matrix is completed, and then the optimal weighting value is calculated from the maximum eigenvector of the WSM-AHP matrix, according to the new WSM-AHP method developed in this study. The applied results of the new method showed that the optimal weighting value from WSM-AHP is more reasonable than the general AHP specialists’ evaluation for the weighting value. This study also analyzed the sensitivity of the WSM-AHP method according to a variation of nonlinear exponents for accessibility criteria, which are used to make urbanization potential maps with the optimal weighting value for multiple criteria in the grid-based geographic information system technique. This study tried also to develop WSM-AHP2, which is simplified by using a ranking of the potential value for each scenario. The results of this study showed that WSM-AHP and simplified WSM-AHP2 can be used to generate the optimal potential maps for land-use planning in the urban fringe area.

GPU-Based Neighbor-Search Algorithm for Particle Simulations

This paper presents a neighbor-search technique to be used in a GPU-based particle simulation framework. Neighbor searching is usually the most computationally expensive step in particle simulations. The usual approach is to subdivide the simulation space to speed up neighbor search. Here, we present a grid-based neighbor-search technique designed to work on programmable graphics hardware.

A Jump Markov Particle Filter for Localization of Moving Terminals in Multipath Indoor Scenarios

This correspondence describes an efficient Bayesian framework for localization of moving terminals (MTs) in wideband wireless networks. In a previous paper, the authors have presented a grid-based technique, based on a hidden Markov model, that used the power delay profiles of the received signals to track the MT position. This grid-based Bayesian method has proved its efficacy in reducing localization errors in realistic indoor environments with multipath effects and mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions. However, the computational power and the memory storage requirements limit its use in practical wireless networks. To improve the computational efficiency, here we propose a jump-Markov particle-filter approach as an extension of the previous work; the LOS/NLOS sight process is the jumping feature that drives the MT motion dynamics, while the particle filter is used to track the MT position. Performance analyses, carried out for realistic multipath indoor environments, show that, with respect to the previous grid-based algorithm, this novel approach greatly reduces the tracking filter complexity still preserving the same localization accuracy. Simulation results prove also the robustness of the proposed method with respect to the uncertainty of sight statistics information.

A Large Scale Simulation of Ultrasonic Wave Propagation in Concrete Using Parallelized EFIT

A time domain simulation tool for the ultrasonic propagation in concrete is developed using the elastodynamic finite integration technique (EFIT) and the image-based modeling. The EFIT is a grid-based time domain differential technique and easily treats the different boundary conditions in the inhomogeneous material such as concrete. Here, the geometry of concrete is determined by a scanned image of concrete and the processed color bitmap image is fed into the EFIT. Although the ultrasonic wave simulation in such a complex material requires much time to calculate, we here execute the EFIT by a parallel computing technique using a shared memory computer system. In this study, formulations of the EFIT and treatment of the different boundary conditions are briefly described and examples of shear horizontal wave propagations in reinforced concrete are demonstrated. The methodology and performance of parallelization for the EFIT are also discussed.

PocketPicker: analysis of ligand binding-sites with shape descriptors

BackgroundIdentification and evaluation of surface binding-pockets and occluded cavities are initial steps in protein structure-based drug design. Characterizing the active site's shape as well as the distribution of surrounding residues plays an important role for a variety of applications such as automated ligand docking or in situ modeling. Comparing the shape similarity of binding site geometries of related proteins provides further insights into the mechanisms of ligand binding.ResultsWe present PocketPicker, an automated grid-based technique for the prediction of protein binding pockets that specifies the shape of a potential binding-site with regard to its buriedness. The method was applied to a representative set of protein-ligand complexes and their corresponding apo-protein structures to evaluate the quality of binding-site predictions. The performance of the pocket detection routine was compared to results achieved with the existing methods CAST, LIGSITE, LIGSITEcs, PASS and SURFNET. Success rates PocketPicker were comparable to those of LIGSITEcs and outperformed the other tools. We introduce a descriptor that translates the arrangement of grid points delineating a detected binding-site into a correlation vector. We show that this shape descriptor is suited for comparative analyses of similar binding-site geometry by examining induced-fit phenomena in aldose reductase. This new method uses information derived from calculations of the buriedness of potential binding-sites.ConclusionThe pocket prediction routine of PocketPicker is a useful tool for identification of potential protein binding-pockets. It produces a convenient representation of binding-site shapes including an intuitive description of their accessibility. The shape-descriptor for automated classification of binding-site geometries can be used as an additional tool complementing elaborate manual inspections.

A Hybrid Fine-Tuned Multi-Objective Memetic Algorithm

In this paper, we propose a hybrid fine-tuned multi-objective memetic algorithm hybridizing different solution fitness evaluation methods for global exploitation and exploration. To search across all regions in objective space, the algorithm uses a widely diversified set of weights at each generation, and employs a simulated annealing to optimize each utility function. For broader exploration, a grid-based technique is adopted to discover the missing nondominated regions on existing tradeoff surface, and a Pareto-based local perturbation is performed to reproduce incrementing solutions trying to fill up the discontinuous areas. Additional advanced feature is that the procedure is made dynamic and adaptive to the online optimization conditions based on a function of improvement ratio to obtain better stability and convergence of the algorithm. Effectiveness of our approach is shown by applying it to multi-objective 0/1 knapsack problem (MOKP).

In Brief: Grid-Based Modeling Technique Furthers Earthquake Risk Prediction

A UK-based grid computing project merges two earthquake data modeling methods—one macro and one micro.

ICEAGE: Interactive Clustering and Exploration of Large and High-Dimensional Geodata

The unprecedented large size and high dimensionality of existing geographic datasets make the complex patterns that potentially lurk in the data hard to find. Clustering is one of the most important techniques for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial clustering methods focus on the specific characteristics of distributions in 2- or 3-D space, while general-purpose high-dimensional clustering methods have limited power in recognizing spatial patterns that involve neighbors. Second, clustering methods in general are not geared toward allowing the human-computer interaction needed to effectively tease-out complex patterns. In the current paper, an approach is proposed to open up the “black box” of the clustering process for easy understanding, steering, focusing and interpretation, and thus to support an effective exploration of large and high dimensional geographic data. The proposed approach involves building a hierarchical spatial cluster structure within the high-dimensional feature space, and using this combined space for discovering multi-dimensional (combined spatial and non-spatial) patterns with efficient computational clustering methods and highly interactive visualization techniques. More specifically, this includes the integration of: (1) a hierarchical spatial clustering method to generate a 1-D spatial cluster ordering that preserves the hierarchical cluster structure, and (2) a density- and grid-based technique to effectively support the interactive identification of interesting subspaces and subsequent searching for clusters in each subspace. The implementation of the proposed approach is in a fully open and interactive manner supported by various visualization techniques.

Rapid Evaluation of Molecular Shape Similarity Index Using Pairwise Calculation of the Nearest Atomic Distances

Rapid evaluation method for obtaining molecular shape similarity index using pairwise calculation of the nearest atomic distance respected to the template atoms was investigated. This method for calculations of similarity indices remarkably reduced required time compared with hitherto methods (especially 2 or 3 orders of magnitude faster than the previous grid-based evaluation technique) and gave without clear loss of preciseness. The potential of these improvements and possible further enhancements are discussed.

Mapping of protein surface cavities and prediction of enzyme class by a self-organizing neural network.

An automated computer-based method for mapping of protein surface cavities was developed and applied to a set of 176 metalloproteinases containing zinc cations in their active sites. With very few exceptions, the cavity search routine detected the active site among the five largest cavities and produced reasonable active site surfaces. Cavities were described by means of solvent-accessible surface patches. For a given protein, these patches were calculated in three steps: (i) definition of cavity atoms forming surface cavities by a grid-based technique; (ii) generation of solvent accessible surfaces; (iii) assignment of an accessibility value and a generalized atom type to each surface point. Topological correlation vectors were generated from the set of surface points forming the cavities, and projected onto the plane by a self-organizing network. The resulting map of 865 enzyme cavities displays clusters of active sites that are clearly separated from the other cavities. It is demonstrated that both fully automated recognition of active sites, and prediction of enzyme class can be performed for novel protein structures at high accuracy.

Computing the superexchange electronic factor of electron transfer theory using a grid-based numerical method

We report a method for calculating the electronic factor in the superexchange rate equation of electron transfer theory; this method is a basis set independent, grid-based numerical technique that utilizes fast Fourier transforms (FFTs) and a Lanczos recursion in a pseudospectral framework and is used to treat a three-dimensional one-electron model of the electronic factor. We compare eigenvalues calculated from the current method to eigenvalues from the literature for both one-dimensional (1D) and three-dimensional (3D) model problems and find that the current method provides excellent accuracy and efficiency. With respect to the superexchange electronic factor, we use model potentials to calculate the tunneling matrix elements with the present method to illustrate how the method can be used to address current issues in superexchange. In particular, we show how this method is useful in evaluating the effect of the bridge potential on the superexchange electronic factor when using repulsive-core pseudopotentials to represent the bridge. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 1262–1273, 2000

Prodock: Software package for protein modeling and docking

A new software package, Prodock, for protein modeling and flexible docking is presented. The protein system is described in internal coordinates with an arbitrary level of flexiblity for the proteins or ligands. The protein is represented by an all-atom model with the Ecepp/3 or Amber IV force field, depending on whether the ligand is a peptidic molecule or not. Prodock is based on a new residue data dictionary that makes the programming easier and the definition of molecular flexibility more straigthforward. Two versions of the dictionary have been constructed for the Ecepp/3 and Amber IV geometry, respectively. The global optimization of the energy function is carried out with the scaled collective variable Monte Carlo method plus energy minimization. The incorporation of a local minimization during the conformational sampling has been shown to be very important for distinguishing low-energy nonnative conformations from native structures. To make the Monte Carlo minimization method efficient for docking, a new grid-based energy evaluation technique using Bezier splines has been incorporated. This article includes some techniques and simulation tools that significantly improve the efficiency of flexible docking simulations, in particular forward/backward polypeptide chain generation. A comparative study to illustrate the advantage of using quaternions over Euler angles for the rigid-body rotational variables is presented in this paper. Several applications of the program Prodock are also discussed. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 412–427, 1999

Flexible docking simulations: Scaled collective variable Monte Carlo minimization approach using Bezier splines, and comparison with a standard Monte Carlo algorithm

An algorithm for docking a flexible ligand onto a flexible or rigid receptor, using the scaled-collective-variables Monte Carlo with energy minimization approach, is presented. Energy minimization is shown to be one of the best techniques for distinguishing between native- and nonnative-generated conformations. Incorporation of this technique into a Monte Carlo procedure enables one to distinguish the native conformation directly during the conformational search. It avoids the generation of a large number of ligand conformers for which more sophisticated energy evaluation tools would have had to be applied to identify the nativelike conformations. The efficiency of the Monte Carlo minimization was greatly improved by incorporating a new grid-based energy evaluation technique using Bezier splines for which the energy function, as well as all of its derivatives, can be deduced from the values at the grid points. Comparison between our ECEPP/3-based algorithm and the Monte Carlo algorithm presented elsewhere (Hart, T. N.; Read, R. J. Prot Struct Funct Genet 1992, 13, 206–222) has been made for docking NH2DPheProArgCOOH, the noncovalent analog of NH2DPheProArg chloromethylketone (PPACK), onto the active site of human α-thrombin. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 244–252, 1999

Flexible docking simulations: Scaled collective variable Monte Carlo minimization approach using Bezier splines, and comparison with a standard Monte Carlo algorithm

An algorithm for docking a flexible ligand onto a flexible or rigid receptor, using the scaled-collective-variables Monte Carlo with energy minimization approach, is presented. Energy minimization is shown to be one of the best techniques for distinguishing between native- and nonnative-generated conformations. Incorporation of this technique into a Monte Carlo procedure enables one to distinguish the native conformation directly during the conformational search. It avoids the generation of a large number of ligand conformers for which more sophisticated energy evaluation tools would have had to be applied to identify the nativelike conformations. The efficiency of the Monte Carlo minimization was greatly improved by incorporating a new grid-based energy evaluation technique using Bezier splines for which the energy function, as well as all of its derivatives, can be deduced from the values at the grid points. Comparison between our ECEPP/3-based algorithm and the Monte Carlo algorithm presented elsewhere (Hart, T. N.; Read, R. J. Prot Struct Funct Genet 1992, 13, 206–222) has been made for docking NH2DPheProArgCOOH, the noncovalent analog of NH2DPheProArg chloromethylketone (PPACK), onto the active site of human α-thrombin. ©1999 John Wiley & Sons, Inc. J Comput Chem 20: 244–252, 1999

Grid-free density-functional technique with analytical energy gradients.

We have implemented a completely analytical linear combination of atomic orbitals-X\ensuremath{\alpha} local density-functional method with exact energy gradients. The superiority of the analytical method over the corresponding grid-based technique in terms of speed, smooth energy surfaces, and accurate gradients is demonstrated in calculations for the umbrella inversion mode of ammonia. The equilibrium geometry and inversion barrier height are also shown to compare well to experimental data.

Evaluation of the USDA curve number method for agricultural catchments in the Australian semi-arid tropics

The USDA-SCS curve number method (5 day antecedent rainfall version) was evaluated using rainfall and runoff data from four catchments at the Douglas-Daly Research Farm, 250 km S.W. of Darwin. These catchments were rotational cropped with maize and soybeans using either conventional or no-till technology. Optimized curve numbers (CNs) were calculated for each catchment and crop type for the various 5 day antecedent rainfall conditions (ARC) by using a grid-based statistical technique known as the Marquardt-Levenberg method. Significance levels (SL) of 0.05 or less were regarded as significant throughout. The curve number method (CNM) was able to describe significant levels of variation in observed rainfall and runoff data. By using optimized curve numbers, the CNM significantly explained up to 98% of the variation in data. Results showed that crop type and soil conservation bank spacing as individual factors had minor or no effect on optimized CNs, and hence on the ability of the CNM to predict runoff. Cropping technology and ARC, however, had a very strong influence on optimized CNs. Optimized CNs obtained in this study provide best estimates of CNs for use on commercial cropping catchments in the region.

Application of the grid square technique to mapping of evapotranspiration

A grid-based technique for mapping potential evapotranspiration is described. An attempt is made to extrapolate the constituent parameters of Penman's equation (1962) over a grid, so that the equation can be evaluated for every grid square. Data for a part of Southwest England are used to demonstrate the technique. Aspect and slope, which determine evaporation to a considerable degree, have been included using a formula derived by Okanoue.