scholarly journals TraitBank: Practical semantics for organism attribute data

Semantic Web ◽  
2016 ◽  
Vol 7 (6) ◽  
pp. 577-588 ◽  
Author(s):  
Cynthia S. Parr ◽  
Katja S. Schulz ◽  
Jennifer Hammock ◽  
Nathan Wilson ◽  
Patrick Leary ◽  
...  
Keyword(s):  
Attribute Data

Spatial Analysis of Water Resources Data in Selected Districts of Bihar

2019 ◽  
Vol 6 (03) ◽  
Author(s):  
MANIBHUSHAN MANIBHUSHAN ◽  
AKRAM AHMED
Keyword(s):  
Water Resources ◽  
Spatial Data ◽  
Water Bodies ◽  
Tabular Form ◽  
Tabular Data ◽  
Standing Water ◽  
Attribute Data ◽  
State Study ◽  
Scientific Personnel ◽  
Bihar State

The main aim of this study is to apply geographic information system (GIS) and data mining techniques to get the attribute data in a spatial and tabular form related to district wise availability of standing water bodies in their area and number of Bihar state. An analysis has been done on available spatial data and maps to get non-spatial/ tabular data, which are in a more easily understandable form. Data extracted district-wise related to area and number of standing water bodies according to their size of Bihar state. Study shows that the number and area of standing water bodies in Madhubani, East Champaran and Patna districts are 2185, 1753, 350 and 2355.42, 6752.36 and 8429.68 ham respectively. In this way, number and area of standing water bodies of other districts of Bihar are also extracted from geodatabases and digitized maps. This type of information is more useful than the spatial data because a common person is able to understand these tabular data and they can use this data for their own purposes. These data can be utilized by scientific personnel as well as farmers and that will be used in agriculture for better utilization of water resources to enhance agricultural productivity and income of farmers of Bihar state.

scholarly journals An approach to predict the risk of glaucoma development by integrating different attribute data

SpringerPlus ◽  
2012 ◽  
Vol 1 (1) ◽  
pp. 41 ◽  
Author(s):  
Yuichi Tokuda ◽  
Tomohito Yagi ◽  
Kengo Yoshii ◽  
Yoko Ikeda ◽  
Masahiro Fuwa ◽  
...  
Keyword(s):  
Attribute Data

Predicting Voting Patterns in the General Assembly

1971 ◽  
Vol 65 (2) ◽  
pp. 471-498 ◽  
Author(s):  
Jack E. Vincent
Keyword(s):  
Economic Development ◽  
United Nations ◽  
Voting Behavior ◽  
Predictive Power ◽  
Correlation Technique ◽  
Factor Scores ◽  
Theoretical Level ◽  
Independent Variables ◽  
Attribute Data ◽  
The United Nations

This project attempts to relate a large number of potential predictors to voting data generated at the United Nations. Numerous associations were found when the predictors, 77 in all, were related to 13 different kinds of voting scores. Because of considerable redundancy in both sets of data, national attribute and voting, the results were factor analyzed and the original variables were reduced to 14 sets of factor scores representing the national attribute data, and 4 representing the voting data. Several significant associations emerged from the intercorrelation of these two sets of factor scores, with the independent variables “Economic Development,” “Democracy,” and “U.S. Relations” exhibiting considerable predictive power. When the overall relationships between the two sets of data were assessed by use of the canonical correlation technique, “Economic Development” received the greatest weight on the national attribute side, and “Eastern Voting” on the voting (dependent variable) side. These findings accord well with previous research, in that “Economic Development” seems to predict negativism as revealed by voting. Thus “Economic Development” appears to be fundamentally related to certain schisms at the United Nations, with the representatives from the most developed states appearing the most “negative” as evidenced by questionnaire responses and voting behavior. Such orientations are likely to have a significant impact on the evolution of the organization.At a theoretical level, the present findings may have considerable relevance for both Social Field theory and Attribute theory.

Fast Distributed Outlier Detection in Mixed-Attribute Data Sets

2006 ◽  
Vol 12 (2-3) ◽  
pp. 203-228 ◽  
Author(s):  
Matthew Eric Otey ◽  
Amol Ghoting ◽  
Srinivasan Parthasarathy
Keyword(s):  
Outlier Detection ◽  
Data Sets ◽  
Attribute Data

Fracture Prediction by Integrated Prestack Inversion and Poststack Multi-Attribute Data

2020 ◽  
Author(s):  
H. Lei ◽  
L. Junzhou ◽  
C. S.Q ◽  
D. Ning ◽  
L. W.Y ◽  
...  
Keyword(s):  
Fracture Prediction ◽  
Attribute Data ◽  
Prestack Inversion
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