Connectivity Calculation Method of the Simulation Entities Based on Geographical Information Grid

2013 ◽  
Vol 427-429 ◽  
pp. 2738-2742
Author(s):  
Feng Li ◽  
Gang Wan ◽  
Zong Pei Zhang ◽  
Jin Min Liao
Keyword(s):  
Spatial Distribution ◽  
Geospatial Data ◽  
Geographical Information ◽  
Grid Technology ◽  
3 Dimensional ◽  
Grid Simulation ◽  
Computation Efficiency ◽  
The Earth ◽  
Information Grid ◽  
Dimensional Simulation

Geographical information grid can not only manage geospatial data, but also can manage the spatial distribution of 3-dimensional simulation entities. Using geographical information grid technology could divided the earth into different resolution of global series of geographic grid, registering the grid according to the geographical coordinates and technique index of simulation entities, building space position relations between entities, , improving the computation efficiency of connectivity test of simulation entity based on geographic grid simulation entity beforehand.

scholarly journals Spatial Distribution of Breast Cancer in Sudan 2010-2016

2019 ◽  
Author(s):  
Marwa Maweya Abdelbagi Elbasheer ◽  
Ayah Galal Abdelrahman Alkhidir ◽  
Siham Mohammed Awad Mohammed ◽  
Areej Abuelgasim Hassan Abbas ◽  
Aisha Osman Mohamed ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Spatial Distribution ◽  
Spatial Analysis ◽  
High Risk ◽  
Geographical Information ◽  
Risk Level ◽  
Histopathological Diagnosis ◽  
Cross Sectional ◽  
Distribution Maps ◽  
Risk Areas

AbstractBackgroundBreast cancer is the most prevalent cancer among females worldwide including Sudan. The aim of this study was to determine the spatial distribution of breast cancer in Sudan.Materials and methodsA facility based cross-sectional study was implemented in eighteen histopathology laboratories distributed in the three localities of Khartoum State on a sample of 4630 Breast Cancer cases diagnosed during the period 2010-2016. A master database was developed through Epi Info™ 7.1.5.2 for computerizing the data collected: the facility name, type (public or private), and its geo- location (latitude and longitude). Personal data on patients were extracted from their respective medical records (name, age, marital status, ethnic group, State, locality, administrative unit, permanent address and phone number, histopathology diagnosis). The data was summarized through SPSS to generate frequency tables for estimating prevalence and the geographical information system (ArcGIS 10.3) was used to generate the epidemiological distribution maps. ArcGIS 10.3 spatial analysis features were used to develop risk maps based on the kriging method.ResultsBreast cancer prevalence was 3.9 cases per 100,000 female populations. Of the 4423 cases of breast cancer, invasive breast carcinoma of no special type (NST) was the most frequent (79.5%, 3517/4423) histopathological diagnosis. The spatial analysis indicated as high risk areas for breast cancer in Sudan the States of Nile River, Northern, Red Sea, White Nile, Northern and Southern Kordofan.ConclusionsThe attempt to develop a predictive map of breast cancer in Sudan revealed three levels of risk areas (risk, intermediate and high risk areas); regardless the risk level, appropriate preventive and curative health interventions with full support from decision makers are urgently needed.

scholarly journals Optical Imaging of the Small Intestine Immune Compartments Across Scales

2021 ◽  
Author(s):  
Arielle Planchette ◽  
Cédric Schmidt ◽  
Olivier Burri ◽  
Mercedes Gomez de Agüero ◽  
Aleksandra Radenovic ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Small Intestine ◽  
High Resolution ◽  
Imaging Modality ◽  
Regions Of Interest ◽  
Label Free ◽  
3 Dimensional ◽  
Wide Range ◽  
Mouse Small Intestine ◽  
Made In

Abstract The limitations of 2D microscopy constrain our ability to observe and understand tissue-wide networks that are, by nature, 3-dimensional. Optical projection tomography enables the acquisition of large volumes (ranging from micrometres to centimetres) in various tissues, with label-free capacities for the observation of auto-fluorescent signals as well fluorescent-labelled targets of interest in multiple channels. We present a multi-modal workflow for the characterization of both structural and quantitative parameters of the mouse small intestine. As proof of principle, we evidence its applicability for imaging the mouse intestinal immune compartment and surrounding mucosal structures. We quantify the volumetric size and spatial distribution of Isolated Lymphoid Follicles (ILFs) and quantify density of villi throughout centimetre long segments of intestine. Furthermore, we exhibit the age- and microbiota-dependence for ILF development, and leverage a technique that we call reverse-OPT for identifying and homing in on regions of interest. Several quantification capabilities are displayed, including villous density in the autofluorescent channel and the size and spatial distribution of the signal of interest at millimetre-scale volumes. The concatenation of 3D image acquisition with the reverse-OPT sample preparation and a 2D high-resolution imaging modality adds value to interpretations made in 3D. This cross-modality referencing technique is found to provide accurate localisation of ROIs and to add value to interpretations made in 3D. Importantly, OPT may be used to identify sparsely-distributed regions of interest in large volumes whilst retaining compatibility with high-resolution microscopy modalities, including confocal microscopy. We believe this pipeline to be approachable for a wide-range of specialties, and to provide a new method for characterisation of the mouse intestinal immune compartment.

scholarly journals Spatial Analysis of Seasonal Precipitation Using Various Interpolation Methods in the Euphrates Basin, Turkey

2021 ◽  
Author(s):  
Okan Mert Katipoğlu
Keyword(s):  
Spatial Distribution ◽  
Geographical Information Systems ◽  
Polynomial Interpolation ◽  
Estimation Method ◽  
Summer Precipitation ◽  
Winter Precipitation ◽  
Geographical Information ◽  
Seasonal Precipitation ◽  
Interpolation Methods

Abstract It is vital to accurately map the spatial distribution of precipitation, which is widely used in many fields such as hydrology, climatology, meteorology, ecology, and agriculture. In this study, it was aimed to reveal the spatial distribution of seasonal long-term average precipitation in the Euphrates Basin by using various interpolation methods. For this reason, Simple Kriging (SK), Ordinary Kriging (OK), Universal Kriging (UK), Ordinary CoKriging (OCK), Empirical Bayesian Kriging (EBK), Radial Basis Functions (Completely Regularized Spline (CRS), Thin Plate Spline (TPS), Multiquadratic, Inverse Multiquadratic (IM), Spline with Tensor (ST)), Local Polynomial Interpolation (LPI), Global Polynomial Interpolation (GPI), Inverse Distance Weighting (IDW) methods have been applied in the Geographical Information Systems (GIS) environment. Long-term seasonal precipitation averages between 1966 and 2017 are presented as input for the prediction of precipitation maps. The accuracy of the precipitation prediction maps created was based on root mean square error (RMSE) values obtained from the cross-validation tests. The method of precipitation by interpolation yielding the lowest RMSE was selected as the most appropriate method. As a result of the study, OCK in spring and winter precipitation, LPI in summer precipitation, and OK in autumn precipitation were determined as the most appropriate estimation method.

scholarly journals Gamma Distribution and its Application of Spatially Monitoring Meteorological Drought in Barind, Bangladesh

2013 ◽  
Vol 5 (2) ◽  
pp. 287-293 ◽  
Author(s):  
ATMJ Alam ◽  
MS Rahman ◽  
AHM Saadat ◽  
MM Huq
Keyword(s):  
Spatial Distribution ◽  
Gamma Distribution ◽  
Monsoon Season ◽  
Standardized Precipitation Index ◽  
Geographical Information ◽  
Critical Threshold ◽  
Drought Severity ◽  
Multiple Time ◽  
Drought Vulnerability ◽  
Weighting Method

The Barind tract of Bangladesh suffers from frequent drought due to erratic rainfall distribution. In the present study details analysis of rainfall data has been carried out for the years 1971-2010. The Standardized Precipitation Index (SPI) which is followed by gamma distribution is used to evaluate drought vulnerability based on frequency and severity of drought events at multiple time steps (3, 5 and 12 months). Drought severity maps are generated in a GIS (Geographical Information System) environment using inverse distance weighting method. Critical (threshold) rainfall values are derived for each station at multiple-time steps in varying drought categories to determine least amount of rainfall required to avoid from drought initiation. The study found that drought vulnerability portrays a very diverse but consistent picture with varying time steps. Analysis and interpretation of the map shows a similar spatial distribution of drought in pre-monsoon season but in monsoon season rainfall deficits shifts its position time to time and occurred in certain discrete pockets. In 12 months period the spatial distribution of drought was almost similar with monsoon season. In pre-monsoon season drought severity was higher in north eastern part of the study area compare to other parts. The study also evident that critical threshold values of rainfall to avoid drought condition was higher in the northern part of high Barind than southern part.DOI: http://dx.doi.org/10.3329/jesnr.v5i2.14832 J. Environ. Sci. & Natural Resources, 5(2): 287-293 2012

Sign in / Sign up

Export Citation Format

Share Document