Grid File Research Articles

Precise point positioning (PPP) based on the machine learning-based ionospheric tomography

Undifferenced and Uncombined Precise Point Positioning (UPPP) currently stands as a prominent research area, where the integration of high-precision ionospheric products holds the potential to substantially enhance accuracy and convergence performance in UPPP. Presently, the majority of external ionospheric constraints for UPPP rely on Global Ionospheric Maps (GIM). However, the accuracy and resolution of GIM fall short, imposing significant limitations on the positioning performance of UPPP. Consequently, this paper introduces the application of Computerized Ionospheric Tomography based on Machine Learning (CIT-ML) to enhance UPPP performance (PPP-CIT-ML). In this approach, we convert the three-dimensional electron density of CIT-ML into vertical total electron content (VTEC), and then it is compiled into ionospheric grid files essential for UPPP. Simultaneously, the traditional ionospheric tomography methods based on the improved algebraic reconstruction technique (IART) is also employed for UPPP (PPP-CIT-IART), alongside the ionospheric grid files broadcasted by the Center for Orbit Determination in Europe (CODE) for UPPP (PPP-CODE), where PPP-CIT-IART and PPP-CODE are used as the reference methods to test the performance of PPP-CIT-ML. In Static and Kinematic UPPP, compared to PPP-CODE, PPP-CIT-IART demonstrated average improvements in positioning accuracy and convergence performance by over 10% and 7%, respectively. PPP-CIT-ML showed average improvements in positioning accuracy and convergence performance by over 26% and 28%, respectively. The extrapolated ionospheric electron density (IED) applied to UPPP (ECIT-ML-PPP) and compared with PPP-CODE displayed average improvements in positioning accuracy by over 21% and convergence performance by over 26%. Compared with PPP-CIT-IART, ECIT-ML-PPP displayed average improvements in positioning accuracy and convergence performance by over 6% and 21%, respectively. These findings highlight that ionospheric error correction information obtained through ionospheric tomography significantly enhances the positioning accuracy and convergence performance of UPPP. Moreover, the performance enhancement achieved through machine learning-based ionospheric tomography is more pronounced. This study provides preliminary validation for the feasibility of applying machine learning-based ionospheric tomography results to navigation positioning.

SDPH: a new technique for spatial detection of path holes from huge volume high-resolution raster images in near real-time

Detecting and repairing road defects is crucial for road safety, vehicle maintenance, and enhancing tourism on well-maintained roads. However, monitoring all roads by vehicle incurs high costs. With the widespread use of remote sensing technologies, high-resolution satellite images offer a cost-effective alternative. This study proposes a new technique, SDPH, for automated detection of damaged roads from vast, high-resolution satellite images. In the SDPH technique, satellite images are organized in a pyramid grid file system, allowing deep learning methods to efficiently process them. The images, generated as 256×256\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$256\ imes 256$$\\end{document} dimensions, are stored in a directory with explicit location information. The SDPH technique employs a two-stage object detection models, utilizing classical and modified RCNNv3, YOLOv5, and YOLOv8. Classical RCNNv3, YOLOv5, and YOLOv8 and modified RCNNv3, YOLOv5, and YOLOv8 in the first stage for identifying roads, achieving f1 scores of 0.743, 0.716, 0.710, 0.955, 0.958, and 0.954, respectively. When the YOLOv5, with the highest f1 score, was fed to the second stage; modified RCNNv3, YOLOv5, and YOLOv8 detected road defects, achieving f1 scores of 0.957,0.971 and 0.964 in the second process. When the same CNN model was used for road and road defect detection in the proposed SDPH model, classical RCNNv3, improved RCNNv3, classical YOLOv5, improved YOLOv5, classical YOLOv8, improved RCNNv8 achieved micro f1 scores of 0.752, 0.956, 0.726, 0.969, 0.720 and 0.965, respectively. In addition, these models processed 11, 10, 33, 31, 37, and 36 FPS images by performing both stage operations, respectively. Evaluations on geotiff satellite images from Kayseri Metropolitan Municipality, ranging between 20 and 40 gigabytes, demonstrated the efficiency of the SDPH technique. Notably, the modified YOLOv5 outperformed, detecting paths and defects in 0.032 s with the micro f1 score of 0.969. Fine-tuning on TileCache enhanced f1 scores and reduced computational costs across all models.

Turbulence simulations with BOUT++ by using SOLPS grids for SOLPS/BOUT++ coupling

AbstractThe coupling of transport code SOLPS with the turbulence code BOUT++ was reported in Reference [D. R. Zhang et al., Phys. Plasmas 26, 012508 (2019)], while the grids of SOLPS and BOUT++ are not completely consistent with each other, especially in the divertor region. In the present work, a method of replacing the grids of BOUT++ with the grids of SOLPS is proposed to make the simulation region fully consistent with each other for the SOLPS/BOUT++ coupling. A SOLPS grid file is generated with an MHD equilibrium and used in BOUT++ code to simulate the profiles of plasma density, ion temperature, and electron temperature with the six‐field two‐fluid model. The profiles of the main plasma parameters simulated with the SOLPS grids are similar with the profiles simulated with the BOUT++ grids at the midplane, while the profiles are deformed compared with the profiles simulated with the BOUT++ grids at the outer divertor target because of the differences of the distributions of SOLPS grids and BOUT++ grids in the divertor region. The radial particle transport coefficient and heat transport coefficients are also calculated by using the BOUT++ code with the two grids, and the comparisons of the radial particle transport coefficient and heat transport coefficients simulated with the two grids at the midplane and outer divertor target plate are discussed.

Zonal statistics datasets of climate indicators for Brazilian municipalities

Abstract Climate trends and weather indicators are used in several research fields due to their importance in statistical modeling, frequently used as covariates. Usually, climate indicators are available as grid files with different spatial and time resolutions. The availability of a time series of climate indicators compatible with administrative boundaries is scattered in Brazil, not fully available for several years, and produced with diverse methodologies. In this paper, we propose time series of climate indicators for the Brazilian municipalities produced using zonal statistics derived from the ERA5-Land reanalysis indicators. As a result, we present datasets with zonal statistics of climate indicators with daily data, covering the period from 1950 to 2022.

ESTIMATION OF MANGROVE FRACTIONAL COVER FROM MULTISPECTRAL AND HYPERSPECTRAL DATA USING MIXTURE TUNED MATCHED FILTERING

Abstract. Mangroves provide various ecosystem services and contribute to climate change adaptation being one of the blue carbon ecosystems. The extents of mangroves are mapped and monitored using commonly available multispectral images, such as Landsat and Sentinel-2, to detect and assess gains and losses. However, this presence or absence per pixel based on crisp classification or index thresholding offers limited information on the dynamics of mangrove growth or decline. In this paper, we evaluated the use of Mixture Tuned Matched Filtering (MTMF) in estimating mangrove fractional cover (MFC) from multispectral (Landsat-8) and hyperspectral (PRISMA) satellite images. We also examined the utility of the mangrove vegetation index (MVI) and enhanced MVI (EMVI) for this purpose. The images were first denoised using Minimum Noise Fraction (MNF). MTMF was then separately applied to the sets of MNF bands, excluding noise bands, to generate Matched Filtering (MF) Score and Infeasibility layers. The endmember (mangrove) spectrum was extracted from a pixel identified using pixel purity index (PPI) and examination of high-resolution Google Earth base image, from which detailed mangrove extents were also delineated. A 30-m vector grid file was created and populated with MFC, MF Score, and Infeasibility values using zonal analysis. Correlation analysis, exploratory regression, and ordinary least squares (OLS) regression were performed. MF Score is moderately and positively correlated with MFC. In contrast, Infeasibility, MVI, and EMVI are uncorrelated or very weakly correlated with MFC. MFC can be estimated using an OLS model with MF Score and Infeasibility as explanatory variables. The performance of the PRISMA-based model (R2Adj=0.30, AIC=98643.20) was found to be better than the Landsat-8-based model (R2Adj=0.36, AIC=97428.89).

GridFormat: header-only C++-library for grid file I/O

GridFormat: header-only C++-library for grid file I/O

Generalization of digital elevation models for military passability maps development

Abstract. This paper presents the methodology of the digital elevation model (DEM) generalization which aims to reduce the generation time of the military passability maps. The generalization is based on the local standard deviations of slopes on the analyzed area. It assumes that in areas, where the diversification of relief is low, the elevation points should be reduced, which may significantly increase the efficiency of the process of the military passability maps development. The generalization was performed on the LIDAR (Light Detection and Ranging) elevation data, which can be obtained with no charges from the Polish Head Office of Geodesy and Cartography. The data are in 1 m resolution and in an ASCII grid file, which contains all coordinates (X, Y and H) of elevation points. The conducted research shows that the modification of parameters used in the generalization process (shape and size of primary fields, number of classes and standard deviation threshold) influences the degree of generalization of obtained results. What is more, the generalized DEMs allowed to reduce the processing time of the passability maps by about 3.5 times compared to the non-generalized model. The parameters used for generalization can be adjusted by the user to individual needs which makes the tool universal.

Геолого-плотностные модели глубинного строения в районе локальных гравитационных аномалий севера Волго-Уральской антеклизы

Detailed geological and geophysical studies discovered intensive local gravimetric anomalies (Frolovskaya, Chetdinskaya, Lokchimskaya, Kynmemtila and others) in the south of the Komi Republic, which were promising for the discovery of bodies of the basic (ultrabasic ?) composition in the production of geological and geophysical works [8, 9].
 Within them, a database of XYZ (recorded and extrapolated) in arbitrary units of the gravity field and their rectangular coordinates was created in the Microsoft EXCEL program, with more than 1600 values, and formed grid files, based on them, formed the basis for calculations in the Golden Software SURFER program for constructing models of the deep structure. As a result of the interpretation of the gravity field, geological and geophysical models of the deep structure

Three-Dimensional Image of Crustal Density Model: A Case Study in South Kamchatka

Abstract —The methodology for building a 3D density model of the Earth’s crust and upper mantle for a crustal block in the South Kamchatka Peninsula is presented. The model is derived from the interpretation of the Bouguer anomaly values and data obtained by deep seismic soundings and electrical prospecting methods. 3D image creation can be viewed as a several phase procedure. At the first step, the area of interest is investigated through a network of intersecting profiles utilized for subsequent modeling depth density sections using the parameter scanning procedure. The a priori data include materials of geophysical surveys and geological, and petrophysical studies as well as results of depth estimation at singular points by the Euler deconvolution method. The next step involves formation of a 3D density matrix from the cross-section models. Coordinates in the cross-section planes are defined in the square grid nodes and converted to plane rectangular coordinates (the SK-42 reference system). A file of the cross-sectional database of density values is thus produced. For area shaving a sparse network of cross-sections, an additional database is derived from grid files of densities mapped horizon-wise. This ultimately results in the creation of the unified databases. A 3D network of cubic unit cells for three-dimensional (voxel) representation of density of the geologic medium is calculated. The model of density of unit cube with edge measuring 4 km was constructed for entire investigated block of the Earth’s crust. The model was detailed by decreasing successively the unit cube edges to 2.0, 1.0, and 0.5 km. The 3D modeling results are presented as block diagrams and density isosurface maps in horizontal slices at different depths. The block diagrams show isosurfaces with densities typical of deep subsurface boundaries and structures. The isosurfaces for densities of 2.75 and 2.90 g/cm3 reflect the morphology of the roof of the crystalline basement, and the lower–upper crust boundary, respectively, while the isosurfaces of 3.20 and 3.33 g/cm3 represent feasible shape of the crust–upper mantle contact. The lower-density zone ubiquitously observed in the investigated crustal block is caused by rock destruction along the deep fault. It is identified in the model with 1 km cubic unit cell side and encompasses the feeding systems of volcanoes, namely: Sopka Asacha (Asacha Volcano), Mutnovskaya Sopka (Mutnovsky Volcano), Gorelaya Sopka (Gorely Volcano), and Vilyuchinskaya Sopka (Vilyuchansky Volcano).The model with a 0.50 km cubic unit cell side shows a 2.85 g/cm3 isosurface, which delineates a column-shaped high-density region. A higher density revealed in the block is assumed to be associated with basite intrusions. 3D density models based on cross-section modeling provide additional information for geodynamic reconstructions, allowing a rough estimation of the geometry of concealed geologic features and their volumes, and can be utilized in 3D modeling to build initial models.

PorousMultiphaseFoam v2107: An open-source tool for modeling saturated/unsaturated water flows and solute transfers at watershed scale

The first releases of porousMultiphaseFoam proposed an open-source software suite to solve the equations for multiphase flow (generalized Darcy’s law) in porous media or groundwater flows (Richards' equation) by taking advantage of OpenFOAM, a finite volume platform with automatic discretization on three-dimensional unstructured grids and good parallel efficiency. Recently, the porousMultiphaseFoam toolbox has been confronted with complex cases of fast water flows and solute transfers in realistic hydrological configurations with variable forcing conditions (heterogeneous infiltration and local tracer injection). Several developments have been carried out to make it possible to simulate those cases, which extend the toolbox with: (i) a set of solvers dedicated to groundwater flows, including coupled water flow and solute transport and simplified 2D approaches, (ii) improved numerical techniques for problems with strong non-linearities, (iii) libraries/executables for pre-processing of input data (geographical information and time-variable forcing terms) and (iv) passive or coupled scalar transport (tracer) with groundwater solvers that support any number of species. New solvers are validated on several (un-)saturated configurations by a direct comparison with a well validated finite element code. Program summaryProgram title: porousMultiphaseFoam v2107CPC Library link to program files:https://doi.org/10.17632/hphn58ksfy.1Developer's repository link:https://github.com/phorgue/porousMultiphaseFoam.gitLicensing provisions: GNU GPLv3Programming language: C++ / OpenFOAMJournal reference of previous version: Computer Physics Communications 187 (2015) 217-226Does the new version supersede the previous version?: YesReasons for the new version: Multiple new features of the toolbox dedicated to groundwater flows (with pre-processing tools)Summary of revisions:–Solvers:–groundwaterFoam/stationaryGroundwaterFoam: new unsaturated flow (transient/stationary) solvers in porous media (Richards' equation) using Picard or Newton's method for linearization.–groundwater2DFoam/stationaryGroundwater2DFoam: new 2D (transient/stationary) solver for saturated flow in porous media.–porousScalarTransportFoam/porousScalarTransport2DFoam: new passive multi-scalar transport solvers on pre-computed flow fields (3D unsaturated or 2D saturated fields).–groundwaterTransportFoam/groundwaterTransport2DFoam: new solvers coupling flow modeling (2D saturated or 3D unsaturated) with multi-scalar tracers transports.–Improved numerical techniques–Timestep management: time-stepping is now based on the temporal truncation of the time scheme used (backward Euler 1st and 2nd order, Crank-Nicolson).–Linearization techniques: problems of unsaturated flow with strong non-linearities can now be solved using an algorithm based on Newton's method.–Libraries:–numericalMethods: the EulerD3dt3Scheme class allows computation of the 3rd-order time derivative to estimate the truncation error and the JacobianMatrix class computes the Jacobian using finite differencing (expensive method used only for debugging).–toolsGIS: new dynamic library for managing GIS (Geographical Information System) files and event files. Events are variable and localized source terms for fluid or scalar transport.–Ippisch: an improved two-phase model for relative permeability and capillary pressure.–porousBoundaryConditions: several new boundary conditions have been added to handle heterogeneous pressure head boundary conditions and variable fluid or tracer injections (using event files).–Utilities:–setBoundaryHeadPressure: pressure head initializer for boundary conditions using uniform value of GIS files.–setFieldsFromDEM/setFieldsFromXY: heterogeneous initializer for internal fields, similar to the classical OpenFOAM setFields, but using ordered (DEM) or unordered (XY) grid files.–darcyFoam: simple utility to calculate a single-phase flow in porous media.Nature of problem: The porousMultiphaseFoam toolbox was initially released with generic two-phase solvers for flow in porous media. Developments were carried out to model more specifically hydrogeological flows by including a groundwaterFoam solver for Richards' equation. However, many features required to simulate realistic configurations, such as event management for variable and heterogeneous forcing terms (infiltration / scalar source term) or suitable numerical techniques for complex configurations (high rate injection for unsaturated flow for example), were still missing. Moreover, the 2D approach with integration of vertical properties (for flow and tracer) was not present even though this is an indispensable tool for groundwater flow modeling due to its ease of implementation and its low computation cost.Solution method: Improved numerical techniques have been developed to solve realistic flows by handling strong non-linearities with Newton's method, and a wide range of time scales with time-stepping based on time truncation errors. Various solvers for groundwater flows have been developed to handle cases under different assumptions, including the aforementioned 2D approaches. Variants of these solvers were also developed to simultaneously solve the passive transport of any number of scalars (tracers) by the flow. A dynamic library has been developed to pre-process input data: event information for variable conditions, GIS file for spatial information.Additional comments including restrictions and unusual features: porousMultiphaseFoam v2107 requires an installation of OpenFOAM-v9. Dedicated branches are available on the developer's repository for compatibility with other versions of OpenFOAM. The following versions are compatible with the current version of porousMultiphaseFoam: v7, v8, v1906, v2006 and v2106. Older branches may be found in the repository link but do not contain all features.

Quick Compression and Transmission of Meteorological Big Data in Complicated Visualization Systems

The sizes of individual data files have steadily increased along with rising demand for customized services, leading to issues such as low efficiency of web‐based geographical information system (WebGIS)‐based data compression, transmission, and rendering for rich Internet applications (RIAs) in complicated visualization systems. In this article, a WebGIS‐based technical solution for the efficient transmission and visualization of meteorological big data is proposed. Based on open‐source technology such as HTML5 and Mapbox GL, the proposed scheme considers distributed data compression and transmission on the server side as well as distributed requests and page rendering on the browser side. A high‐low 8‐bit compression method is developed for compressing a 100 megabyte (MB) file into a megabyte‐scale file, with a compression ratio of approximately 90%, and the recovered data are accurate to two decimal places. Another part of the scheme combines pyramid tile cutting, concurrent domain name request processing, and texture rendering. Experimental results indicate that with this scheme, grid files of up to 100 MB can be transferred and displayed in milliseconds, and multiterminal service applications can be supported by building a grid data visualization mode for big data and technology centers, which may serve as a reference for other industries.

Mapping potential geographical distribution of Acria meyricki (Lepidoptera: Depressariidae), an emerging oil palm defoliator in India

Ecological niche modelling study was attempted to identify climate suitable locations for Acria meyricki Shashank and Ramamurthy spread in India as area under oil palm cultivation is expanding. Geographical coordinates of 31 pest presence sites, world climate grid files, nineteen bioclimatic variables, MaxEnt software, DIVA-GIS were used for the construction of ecological niche model of A. meyricki. The model indicated potential geographical locations (districts) in six states viz., Andhra Pradesh, Gujarat, Karnataka, Maharashtra, Odisha, Tamil Nadu for the spread of pest in India. The predictions of potential distribution of the pest arrived at in this study should help in developing strategies for monitoring and managing this defoliator of oil palm.

Updating of digital topographic maps in the new national spatial coordinate system: case Fergana valley in Uzbekistan

Abstract. The classical geodetic coordinate system (CS42) in Uzbekistan uses the Krasovsky ellipsoid. The implementation of new information technologies, such as the Global Navigation Satellite System, became the basis for the development of a new national open geocentric coordinate system. This paper describes the development of a distortion grid for transforming horizontal spatial data from the local geodetic datum CS42 to a geocentric datum WGS84 for 1:100000 scale maps of the Fergana Valley in Uzbekistan. A first version of the distortion grid file has been created for transforming between CS42 and WGS84 for the whole territory of the country. The significant influence of the longitudinal drift of the region has been confirmed. The grid was used to transform topographic maps at a scale of 1:100000 for the Fergana Valley. Changing the map datum has shifted the grid of coordinate systems by 70 m in the East and 7 m in the North.

MAT.TRIGRS (V1.0): A new open-source tool for predicting spatiotemporal distribution of rainfall-induced landslides

In this work, a new TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) model based on Matlab® is proposed, named MAT.TRIGRS (V1.0), which can be applied to research of spatiotemporal distribution of rainfall-induced landslides. It is characterized by simple data processing, straightforward setting of script parameters, high computation efficiency and convenient operation. A test on the effectiveness of this tool is conducted using the data of the 2019 rainfall-induced landslide in the Shuicheng area, Guizhou Province, China. The data of drilling, terrain, hydrological and mechanical properties of the study area are prepared and converted into TIF grid files. Based on the MAT.TRIGRS model, variations of water head depth and slope instability with time are calculated. The results show that compared with TRIGRS version 2, MAT.TRIGRS is more convenient and friendly in data processing and operation. The comparative experiments prove that the computation efficiency of the new tool increases by 40%. It can be used to predict spatial-temporal distribution of rainfall-induced landslides and contribute to the design and implementation of the landslide early warning system (LEWS).

A compressing and saving method for structured grid data based on block construction

The increasing grid data in CFD simulation has brought some new difficulties and challenges, such as high storage cost, low transmission efficiency. In order to overcome these problems, a novel method for compressing and saving the structured grid are proposed. In the present method, the geometric coordinates of the six logical domains of one grid block is saved instead of all grid vertex coordinates to reduce the size of the structured grid file when the grid is compressed. And all grid vertex coordinates are recovered from the compressed data with the use of the transfinite interpolation algorithm when the grid is decompressed. Firstly, single-block grid cases with different edge vertexes are tested to investigate the compression effect. The test results show that a higher compression ratio will be obtained on a larger grid. Secondly, further theoretical analysis is carried out to investigate the effects of parameters on grid compression. The analysis on single-block grid compression shows that the compression ratio is proportionate to the cubic root of the number of total vertexes. The highest compression ratio of single-block grid is obtained when the numbers of vertexes in three logical directions are equal. The analysis on multi-block grid compression shows that a higher compression ratio will be obtained when a larger difference of total vertexes number exists among the grid blocks. Finally, multi-blockgrids of two industrial aircraft configurations are compressed to validate the method. The compression results demonstrate that the present method has an excellent ability on structured grid compression. For a million-vertex structured grid, more than 80 percent disk space can be saved after compression.

Modeling Conditions Appropriate for Wildfire in South East China – A Machine Learning Approach

Wildfire is one of the most common natural hazards in the world. Fire risk estimation for the purposes of risk reduction is an important aspect in disaster studies around the world. The aim of this research was to develop a machine learning workflow process for South East China to monitor fire risks over a large region by learning from a grid file database containing a time series of several of the important environmental parameters largely extracted from remote sensing data products, and highlight areas as fire risk or non-fire risk over a couple of weeks in the future. The study employed fire threshold and the transductive PU learning method to identify reliable non-fire/negative training samples from the grid file database using fire/positive training samples, labeled using the MODIS MCD14ML fire location product. Different models were trained for the three natural vegetation land covers, namely evergreen broadleaf forest, mixed forest, and woody savannas in the study area. On the test dataset, the three models exhibited high sensitivity (>80%) by identifying the majority of fires in the test dataset for all land covers. The use of the reliable negatives identified though the fire threshold and PU learning process resulted in low precision and accuracy. During the model verification process, the model for the mixed forest land cover performed the best with 70% of verification fires falling within the classified fire zone. It was found that the better representation of mixed forest in the training samples made this model perform more reliably as compared to others. Improving the individual models constructed for different land covers and combining them can provide fire classification for a larger region. There is room to improve the spatial precision of fire cell classification. Introducing finer scale features that have higher correlation with fire activity and exhibit high spatial variability seems a viable way forward.

Simulation and Computational Study of CFD on Tube MBR Membrane Assembly

When using tubular MBR to treat sewage, the water production is an important parameter to measure the efficiency of the tubular MBR system. The problem to be solved in this paper is to calculate the water yield of the tubular MBR system, so as to evaluate the sewage treatment efficiency of the MBR system. This research uses the CFD simulation software ANSYS 16.0 to study the water yield of the tubular MBR system. The MBR model of a single membrane filament tube was established using the ICEM CFD preprocessor in ANSYS 16.0, and the structured grid was divided to obtain a grid file. Then, the fluid solver was used to solve the mesh file and through the flow monitoring window to obtain the water output of the tubular MBR system. Finally, the CFD postprocessor in ANSYS 16.0 was used to visualize the calculation results and compare them with the waste-water treatment results of some actual MBR systems. The results show that the water yield calculated by the fluent solver is basically the same as that of the actual MBR system. This research realizes the purpose of calculating the water yield of the tubular MBR system with CFD technology, solves the problem of evaluating the working efficiency of the tubular MBR system with water consumption, and realizes the MBR before deployment The evaluation of the working efficiency of the system has certain reference value for the planning, design, and deployment of MBR.

Processing Continuous k Nearest Neighbor Queries in Obstructed Space with Voronoi Diagrams

With the emergence and growing popularity of and location-based service (LBS) technologies, the continuous k nearest neighbor (CO k NN) query in obstructed space is becoming a very important service. In this article, we study the CO k NN in obstructed space, which retrieves k obstructed nearest neighbors (ONNs) for every point on a query segment q̄ . The state-of-the-art approach, called <monospace>Euclidean based CONN (E-CONN)</monospace>, exploits an R-tree to traverse the dataset P in ascending order of their Euclidean distances to q̄ . Taking a different point of view, in this article, we explore the idea of Voronoi diagram to define the notion of obstructed Voronoi diagram (OVD) . The Voronoi cells with obstacles are divided into visible and invisible regions for quickly answering nearest neighbor queries. To facilitate efficient retrieval of Voronoi cells and processing of continuous nearest neighbor (CONN) queries, we propose a new grid-based index, called Voronoi diagram with Obstacles in Grid (VO-Grid) , which indexes Voronoi cells and associated obstacle information with a grid file. Based on VO-Grid, we propose an efficient algorithm, called <monospace>CONN with VO-Grid Acceleration (CONN-VOA)</monospace>, to accelerate the CONN query processing. Moreover, we extend <monospace>CONN-VOA</monospace> to the CO k NN query, which also explores effective filtering and early termination for reducing redundant access of data objects. A comprehensive performance evaluation using both real and synthetic datasets is conducted to validate the proposed ideas and demonstrate the efficiency of our algorithms. The experimental results show that the <monospace>CONN-VOA</monospace> algorithm substantially outperforms <monospace>E-CONN</monospace> algorithm.

GRID System Based on European EGI Standards for Large-Scale Calculations by the Original Accelerated Method of Quantum Chemistry

Based on the analysis of modern tools for the creation of GRID-type information systems incorporated into the UMD repository, which has become a European EGI “standard” (including new version of Globus Toolkit, ARC, dCache, etc.), the application of GRID systems for computational chemistry problems is briefly considered. The GRID system created by the authors is a combination of two Linux CentOS 7 clusters and based on the UMD-4 software. The relevance and efficiency of the application of batch processing systems (we use Torque 4.2.10) in quantum-chemical calculations are increased in the mass calculations of docking complexes (including drug design problems) and, for these purposes, an improved semiempirical method implemented with more efficient approximations in the LSSDOCL software in Fortran-95 has been proposed. New methods of approximation, including the methods for DFT functionals, have been developed for such calculations to perform their software implementation. The convertors of LSSDOCK calculation results into the XML based CML version 3 format, which is more natural for GRID, have been developed. Based on the CML format and the dCache software tools, the universal tree of a virtual GRID file system distributed between heterogeneous nodes for the storage of LSSDOCK calculation results has been implemented.

Digital Elevation Models of the Bottom in the Operational Oceanography System

A new area of oceanography, operational oceanography, involves a comprehensive assessment and forecast of the variability of the state of the marine environment. This requires systematic study of numerous natural parameters, the creation of integrated measurement systems for the properties of the water column and seafloor, rapid data collection and transmission systems, assimilation of new data in the model, etc. The seafloor has a significant impact on the hydrophysical state of the environment and vice versa; accordingly, information is needed on the state and properties of the bottom in the deployment area of various surveillance tools, including assessment of possible geohazards. The spatial distribution and possible variability of the geomorphological and geological–geophysical parameters of the bottom, which determine the geoacoustic properties, depends on the shape of the relief and its morphometric characteristics. Thus, the digital elevation model (DEM) is an essential component of marine geographic information systems and an essential element of operational oceanography. A DEM entails an organized structure of files containing vector representations of various types of spatial objects, information on their attributes, and topological relationships between them. The DEM displays the seafloor relief as a grid file with a resolution corresponding to a given scale. Methods for the direct spatial mathematical processing of DEMs make it possible to obtain a wide range of bottom surface characteristics, including morphometric. DEMs can have both independent practical application and act as parameters for systematizing, typifying, and zoning the seafloor. The paper outlines some areas of the possible use of DEMs in operational oceanography with a case study of the Arctic shelf.