scholarly journals Analysis of Pole Position from 1846 to 1970

1972 ◽  
Vol 48 ◽  
pp. 19-32 ◽  
Author(s):  
E. M. Gaposchkin
Keyword(s):  
Data Analysis ◽  
Historical Data ◽  
Pole Position ◽  
Point Of View ◽  
Two Component ◽  
Component Motion ◽  
Component Models

One- and two-component models for the Chandler motion are investigated with the use of historical data. Evidence for a two-component motion is more convincing from both the data-analysis and the geophysical point of view.

Medical Diagnosis from a Clinician’s Point of View

1978 ◽  
Vol 17 (01) ◽  
pp. 28-35
Author(s):  
F. T. De Dombal
Keyword(s):  
Decision Making ◽  
Data Analysis ◽  
Computer Science ◽  
Medical Diagnosis ◽  
Information Science ◽  
Point Of View ◽  
Joint Research ◽  
The World

This paper discusses medical diagnosis from the clinicians point of view. The aim of the paper is to identify areas where computer science and information science may be of help to the practising clinician. Collection of data, analysis, and decision-making are discussed in turn. Finally, some specific recommendations are made for further joint research on the basis of experience around the world to date.

Teaching Computer Based Historical Data Analysis

1994 ◽  
Vol 6 (1) ◽  
pp. 52-58 ◽  
Author(s):  
Charles Anderson ◽  
Robert J. Morris
Keyword(s):  
Data Analysis ◽  
Social History ◽  
Historical Data ◽  
Good Practice ◽  
Computer Assisted ◽  
Historical Data Analysis ◽  
University Of Edinburgh ◽  
Computer Based ◽  
The University

A case study ofa third year course in the Department of Economic and Social History in the University of Edinburgh isusedto considerandhighlightaspects of good practice in the teaching of computer-assisted historical data analysis.

scholarly journals How Digital Inclusion Increase Opportunities for Young People: Case of NEETs from Bulgaria, Romania and Turkey

2021 ◽  
Vol 13 (14) ◽  
pp. 7894
Author(s):  
Gabriela Neagu ◽  
Muhammet Berigel ◽  
Vladislava Lendzhova
Keyword(s):  
Data Analysis ◽  
Rural Areas ◽  
Secondary Data ◽  
Point Of View ◽  
Multidimensional Analysis ◽  
Theoretical Point ◽  
Digital Inclusion ◽  
Virtual Mobility ◽  
Alternative Research ◽  
High Share

This paper examines the perspectives of rural NEETs in the information society. Our analysis focuses on the situation of three European countries—Bulgaria, Romania, and Turkey—characterized by a high share of rural areas and a population of NEETs. From a methodological point of view, we use alternative research methods (secondary data analysis) with statistical methods (simple linear regression). From a theoretical point of view, we will opt for a multidimensional analysis perspective: the theory of digital divide, digital inclusion, virtual mobility, etc. Through data analysis, we expect to obtain a more complete and detailed picture of the ICT situation in rural areas (level of digital skills, level of digital inclusion) to demonstrate the importance of ICT in optimizing virtual mobility for the living conditions of the population, especially the NEET population.

scholarly journals Hotspot analysis: a first prototype Python plugin enabling exploratory spatial data analysis into QGIS

2016 ◽  
Author(s):  
Daniele Oxoli ◽  
Mayra A Zurbarán ◽  
Stanly Shaji ◽  
Arun K Muthusamy
Keyword(s):  
Data Analysis ◽  
Spatial Data ◽  
Point Of View ◽  
Geospatial Data ◽  
Spatial Data Analysis ◽  
Exploratory Spatial Data Analysis ◽  
Software Environment ◽  
Hotspot Analysis ◽  
Computational Procedures ◽  
Gis Software

The growing popularity of Free and Open Source (FOSS) GIS software is without doubts due to the possibility to build and customize geospatial applications to meet specific requirements for any users. From this point of view, QGIS is one of the most flexible as well as fashionable GIS software environment which enables users to develop powerful geospatial applications using Python. Exploiting this feature, we present here a first prototype plugin for QGIS dedicated to Hotspot analysis, one of the techniques included in the Exploratory Spatial Data Analysis (ESDA). These statistics aim to perform analysis of geospatial data when spatial autocorrelation is not neglectable and they are available inside different Python libraries, but still not integrated within the QGIS core functionalities. The main plugin features, including installation requirements and computational procedures, are described together with an example of the possible applications of the Hotspot analysis.

Data Analysis and Interpretation in Metabolomics

2013 ◽  
pp. 1494-1521
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

Data Analysis and Interpretation in Metabolomics

2011 ◽  
pp. 29-56
Author(s):  
Jose M. Garcia-Manteiga
Keyword(s):  
Mass Spectrometry ◽  
Nuclear Magnetic Resonance ◽  
Data Analysis ◽  
Systems Biology ◽  
Magnetic Resonance ◽  
Biological System ◽  
Analytical Techniques ◽  
Point Of View ◽  
The Other ◽  
Top Down

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

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