scholarly journals REGIONAL CLASSIFICATION OF POPULATION DYNAMICS CHARACTERISTICS BY MOBILE SPATIAL STATISTICS AND APPLICATION TO EARTHQUAKE COUNTERMEASURES

2019 ◽  
Vol 84 (765) ◽  
pp. 2345-2355
Author(s):  
Koki YAMADA ◽  
Kazumi KURATA ◽  
Nobuo FUKUWA
Keyword(s):  
Population Dynamics ◽  
Spatial Statistics

Dakota Using GIS and Spatial Statistics Borer Population Dynamics and Movements

2011 ◽  
pp. 207-232
Author(s):  
J Hutchinson ◽  
James Campbell ◽  
Michael Toews ◽  
Thomas Vought ◽  
Sonny Ramaswamy
Keyword(s):  
Population Dynamics ◽  
Spatial Statistics

Activated sludge population dynamics

1994 ◽  
Vol 30 (11) ◽  
pp. 159-169 ◽  
Author(s):  
Jiri Wanner
Keyword(s):  
Population Dynamics ◽  
Activated Sludge ◽  
Organic Pollution ◽  
Paper Briefly ◽  
Microbial Composition ◽  
Selection Mechanisms ◽  
Sludge Settling

The paper briefly surveys topics covered by the IAWQ Specialist Group on Activated Sludge Population Dynamics. The activated sludge population dynamics has been formulated as a branch of water science and technology concerned with phenomena governing the relationships between activated sludge microorganisms and their functions. The characterization of organic pollution fractions in wastewaters according to their rate of biodegradation has been discussed and the role of wastewater as an inoculum stressed. The characterization of activated sludge biomass has been evaluated from two viewpoints: grouping according to metabolic abilities and identification and classification of activated sludge microorganisms. The basic selection mechanisms influencing the microbial composition of activated sludge have been described. The problems with activated sludge settling and thickening properties have been mentioned as a typical example of applied population dynamics research.

EFFICIENT CLASSIFICATION OF SCANNED MEDIA USING SPATIAL STATISTICS

2010 ◽  
Vol 24 (06) ◽  
pp. 917-946
Author(s):  
GOZDE UNAL ◽  
GAURAV SHARMA ◽  
REINER ESCHBACH
Keyword(s):  
Spatial Statistics ◽  
High Reliability ◽  
Image Data ◽  
Training Data ◽  
Automated Classification ◽  
Data Set ◽  
Statistical Measures ◽  
Scanned Image ◽  
Scanned Images

Photography, lithography, xerography, and inkjet printing are the dominant technologies for color printing. Images produced on these "different media" are often scanned either for the purpose of copying or creating an electronic representation. For an improved color calibration during scanning, a media identification from the scanned image data is desirable. In this paper, we propose an efficient algorithm for automated classification of input media into four major classes corresponding to photographic, lithographic, xerographic and inkjet. Our technique exploits the strong correlation between the type of input media and the spatial statistics of corresponding images, which are observed in the scanned images. We adopt ideas from spatial statistics literature, and design two spatial statistical measures of dispersion and periodicity, which are computed over spatial point patterns generated from blocks of the scanned image, and whose distributions provide the features for making a decision. We utilize extensive training data and determined well separated decision regions to classify the input media. We validate and tested our classification technique results over an independent extensive data set. The results demonstrate that the proposed method is able to distinguish between the different media with high reliability.

scholarly journals Analysis of settlings of Lutoviska commune since 2nd half of 18th century using GIS

2016 ◽  
pp. 198-207
Author(s):  
Ihor Kozak ◽  
Hanna Kozak
Keyword(s):  
Population Dynamics ◽  
Standard Deviation ◽  
Spatial Autocorrelation ◽  
Key Words ◽  
Spatial Statistics ◽  
Historical Data ◽  
18Th Century ◽  
Future Research ◽  
Standard Deviational Ellipse

The study was conducted within the actual area of Lutoviska commune in Bieszczady district, Podkarpackie voivodeship in Eastern Poland. The dynamics of settlements in Lutoviska commune from the 2nd half of the 18th century was discussed. Maps and historical data were analyzed in the ArcGIS 10.3 program. In the study there were presented possibilities of applying the ArcGIS for Desktop 10.3 program. We analyzed the Lutoviska commune in terms of the changes of settlements and used maps for the analysis of changes in its structure. The first of these was the historical map, namely the tactical map of “WIG” in scale 1:100 000 from 1936. Next we analyzed maps from 1965 and 2014, which were prepared applying the “WMS” server. The changes in the number of villages and households were presented. Population dynamics for Greek-Catholics, “Latynnykys” and Jews for the year 1785 and Ukrainians in comparison with the number of Poles and Jews for the year 1939 were shown. Ethnic and religious composition from the 2nd half of the 18th century was evaluated. Based on the study of spatial placement of settlements with the use of Spatial Statistics (Spatial Autocorrelation Global Moran’s test, Standard Deviational Ellipse and Mean Centre) the character of settlements distribution in Lutoviska commune was presented. There was confirmed a similar configuration of Standard Deviation Ellipse and Mean Center for Greek-Catholics-Ukrainians in 1785 and Ukrainians in 1939 in Lutoviska commune. The scale and results of such changes are interesting for future research, mainly in terms of the change of traditional village system infrastructure and culture. Key words: dynamics, village, GIS, Lutoviska commune.

Can functional classification of tropical trees predict population dynamics after disturbance?

2008 ◽  
Vol 19 (2) ◽  
pp. 209-220 ◽  
Author(s):  
M. Delcamp ◽  
S. Gourlet‐Fleury ◽  
O. Flores ◽  
E. Gamier
Keyword(s):  
Population Dynamics ◽  
Tropical Trees ◽  
Functional Classification

A review and classification of the existing models of cyanobacteria

2006 ◽  
Vol 30 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Basak Guven ◽  
Alan Howard
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Population Dynamics ◽  
Mathematical Models ◽  
Network Models ◽  
Transport Mechanisms ◽  
Neural Network Models ◽  
The World ◽  
Artificial Neural Network Models

Bloom-forming and toxin-producing cyanobacteria remain a persistent nuisance across the world. Modelling of cyanobacteria in freshwaters is an important tool for understanding their population dynamics and predicting bloom occurrence in lakes and rivers. In this paper existing key models of cyanobacteria are reviewed, evaluated and classified. Two major groups emerge: deterministic mathematical and artificial neural network models. Mathematical models can be further subcategorized into those models concerned with impounded water bodies and those concerned with rivers. Most existing models focus on a single aspect such as the growth of transport mechanisms, but there are a few models which couple both.

Sign in / Sign up

Export Citation Format

Share Document