Suchergebnisse

Computational Intelligent Data Analysis for Sustainable Development: An Introduction and Overview Ting Yu, Nitesh Chawla, and Simeon SimoffIntegrated Sustainability AnalysisTracing Embodied CO2 in Trade Using High-Resolution Input-Output Tables Daniel Moran and Arne GeschkeAggregation Effects in Carbon Footprint Accounting Using Multi-Region Input-Output Analysis Xin Zhou, Hiroaki Shirakawa, and Manfred LenzenComputational Intelligent Data Analysis for Climate ChangeClimate InformaticsClaire Monteleoni, Gavin A. Schmidt, Francis Alexander, Alexandru Niculescu-Mizil, Karsten Steinhaeuser, Michael Tippett, Arindam Banerjee, M. Benno Blumenthal, Auroop R. Ganguly, Jason E. Smerdon, and Marco TedescoComputational Data Sciences for Actionable Insights on Climate Extremes and Uncertainty Auroop R. Ganguly, Evan Kodra, Snigdhansu Chatterjee, Arindam Banerjee, and Habib N. NajmComputational Intelligent Data Analysis for Biodiversity and Species ConservationMathematical Programming Applications to Land Conservation and Environmental Quality Jacob R. Fooks and Kent D. MesserComputational Intelligent Data Analysis for Smart Grid and Renewable EnergyData Analysis Challenges in the Future Energy Domain Frank Eichinger, Daniel Pathmaperuma, Harald Vogt, and Emmanuel MüllerElectricity Supply without Fossil Fuels John Boland, Peter Pudney, and Jerzy FilarData Analysis for Real-Time Identification of Grid Disruptions Varun Chandola, Olufemi Omitaomu, and Steven J. FernandezStatistical Approaches for Wind Resource Assessment Kalyan Veeramachaneni, Xiang Ye, and Una-May O'ReillyComputational Intelligent Data Analysis for Sociopolitical SustainabilitySpatio-Temporal Correlations in Criminal Offense Records Jameson L. Toole, Nathan Eagle, and Joshua B. PlotkinConstraint and Optimization Techniques for Supporting Policy Making Marco Gavanelli, Fabrizio Riguzzi,

In this case study, a framework to research economic development is presented. The framework was developed to better understand economic development in large U.S. cities. Because regional economies operate under a single macroeconomic climate, the research techniques applied in international comparisons of economic development can be modified to better evaluate the nuances of the economies being studied. The framework outlined in this case study can be used to guide data selection and the aggregation of said data into an economic development index. Correlation coefficients are discussed because of their merit in guiding the choice of which data to include. In addition, systematically excluding data series within an index is shown to allow the researcher to determine if the index is robust to the data it is comprised of. The advantages and disadvantages of using the arithmetic mean in aggregating data are also discussed. After reading this case study, you will be able to apply the framework outlined for your own research purposes.

The rural school is the most critical and unequal qualitative component of the Chilean educational system. The objective of this investigation is to propose a non parametric methodology using the data development analysis (DEA), which is a tool that permits an approach to the economical efficiency for rural schools that took part on the quality improvement and educational equity program (MECE) in the XRegion, South of Chile. An analysis methodology is proposed to identify the small resource schools that reached a superior efficiency level, taking them as a model to improve educational management. Therefore, the application of the DEA theory proves that there is an analysis methodology that provides a context of education politicy, and particularly, to conclude how they get involved into this exemplary challenge of change in the economic development. ; El programa MECE, encuadrado dentro de las políticas sociales del Gobierno de Chile, tiene como propósito: mejorar la calidad de la educación, alcanzar la equidad y generar espacios de participación en todos los sectores involucrados en el proceso educativo. Sin embargo, las escuelas rurales representan uno de los componentes cualitativos más críticos y de mayor inequidad del sistema educacional chileno subvencionado por el Estado. Pues bien, el objetivo de esta investigación es proponer una metodología no paramétrica a través del Análisis Envolvente de Datos (DEA), herramienta que nos posibilita la valoración de la eficiencia técnica en las diferentes escuelas rurales que formaron parte del Programa de Mejoramiento de la Calidad y la Equidad de la Educación (MECE/BASICA/RURAL) en la X Región.