Detection of outliers in pollutant emissions from the Soto de Ribera coal-fired power plant using functional data analysis: a case study in northern Spain

The present research uses two different functional data analysis methods called functional high-density region (HDR) boxplot and functional bagplot. Both methodologies were applied for the outlier detection in the time pollutant emissions curves that were built using as inputs the discrete information available from an air quality monitoring data record station. Although the record of pollutant emissions is made in a discrete way, these methodologies consider pollutant emissions over time as curves, with outliers obtained by a comparison of curves instead of vectors. Then the concept of outlier passes from been a point to a curve that employed the functional depth as the indicator of curve distances. In this study, the referred methodologies are applied to the detection of outliers in pollutant emissions from the Soto de Ribera coal-fired plant which is in the nearby of the city of Oviedo, located in the Principality of Asturias, Spain. Finally, the advantages of the functional method are reported.

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Detection of outliers in water quality monitoring samples using functional data analysis in San Esteban estuary (Northern Spain)

The Science of The Total Environment ◽

10.1016/j.scitotenv.2012.08.083 ◽

2012 ◽

Vol 439 ◽

pp. 54-61 ◽

Cited By ~ 19

Author(s):

C. Díaz Muñiz ◽

P.J. García Nieto ◽

J.R. Alonso Fernández ◽

J. Martínez Torres ◽

J. Taboada

Keyword(s):

Water Quality ◽

Data Analysis ◽

Functional Data Analysis ◽

Functional Data ◽

Water Quality Monitoring ◽

Quality Monitoring ◽

Northern Spain ◽

Detection Of Outliers

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Methodology of Schema Integration for New Database Applications

Human Computer Interaction Development & Management ◽

10.4018/978-1-931777-13-1.ch011 ◽

2002 ◽

pp. 194-218

Author(s):

Joseph Fong ◽

Kamalakar Karlapalem ◽

Qing Li ◽

Irene Kwan

Keyword(s):

Data Analysis ◽

Functional Data Analysis ◽

Functional Data ◽

Schema Integration ◽

Top Down ◽

Database Applications ◽

Bottom Up ◽

Integration Techniques ◽

New Applications

A practitioner’s approach to integrate databases and evolve them so as to support new database applications is presented. The approach consists of a joint bottom-up and top-down methodology; the bottom-up approach is taken to integrate existing database using standard schema integration techniques (B-Schema), the top-down approach is used to develop a database schema for the new applications (T-Schema). The T-Schema uses a joint functional-data analysis. The B-schema is evolved by comparing it with the generated T-schema. This facilitates an evolutionary approach to integrate existing databases to support new applications as and when needed. The mutual completeness check of the T-Schema against B-Schema derive the schema modification steps to be performed on B-Schema to meet the requirements of the new database applications. A case study is presented to illustrate the methodology.

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