Publications by Dimitris Kavroudakis
Open-source technologies for maximizing the creation, deployment, and use of digital resources an... more Open-source technologies for maximizing the creation, deployment, and use of digital resources and information / Shalin Hai-Jew, editor.
The complexity of modern scientific research requires advanced approaches to handle and analyse r... more The complexity of modern scientific research requires advanced approaches to handle and analyse rich and dynamic data. Organizations such as hospitals, hold a great number of health datasets which may consist of many individual records. Artificial Intelligence methodologies incorporate approaches for knowledge retrieval and pattern discovery, which have been proven to be useful for data analysis in various disciplines. Decision trees methods belong to knowledge discovery methodologies and use computational algorithms for the extraction of patterns from data. This work describes the development of an autonomous Decision Support System (" Dth 1.0 ") for the real-time analysis of health data with the use of decision trees. The proposed system uses a patient's dataset based on the patients' symptoms and other relevant information and prepares reports about the importance of the characteristics that determine the number of patients of a specific disease. This work presents the basic concept of decision trees, describes the design of a tree-based system and uses a virtual database to illustrate the classification of patients in a hypothetical intra-hospital case study.
Spatial microsimulation is a methodology aiming to simulate entities such as households , individ... more Spatial microsimulation is a methodology aiming to simulate entities such as households , individuals or businesses in the finest possible scale. This process requires the use of individual based microdatasets. The package presented in this work facilitates the production of small area population microdata by combining various datasets such as census data and individual based datasets. This package includes a parallel implementation of random selection with optimization to select a group of individual records that match a macro description. This methodological approach has been used in a number of topics ranging from measuring inequalities in educational attainment (Kavroudakis, Ballas, and Birkin 2012) to estimating poverty at small area levels (Tanton, McNamara, Harding, and Morrison 2007). The development of the method over recent years is driving computational complexity to the edge as it uses modern computational approaches for the combination of data. The R package sms presented in this work uses parallel processing approaches for the efficient production of small area population microdata, which can be subsequently used for geographical analysis. Finally, a complete case study of fitting geographical data with the R package is presented and discussed. Individual based models are among the most popular tool sets for understanding and analyzing trends or patterns of a population (for a description of population models, see Caswell 2001). Microsimulation models can also be seen as a form of population projection model (Imhoff and Post 1998). Microsimulation methodologies may be used to create small area population microdata by combining datasets and then using the results for geographical analysis (for a description of the method see Ballas, Rossiter, Bethan, Clarke, and Dorling 2005). The microsimulation method has been used in the past by economists with successful results to generate data for individuals and then check the effects of public policies at the smaller ag
Spatial microsimulation is a methodology aiming to simulate entities such as house-
holds, indivi... more Spatial microsimulation is a methodology aiming to simulate entities such as house-
holds, individuals or businesses in the finest possible scale. This process requires the use
of individual based microdatasets. The package presented in this work facilitates the pro-
duction of small area population microdata by combining various datasets such as census
data and individual based datasets. This package includes a parallel implementation of
random selection with optimization to select a group of individual records that match a
macro description. This methodological approach has been used in a number of topics
ranging from measuring inequalities in educational attainment (Kavroudakis, Ballas, and
Birkin 2012) to estimating poverty at small area levels (Tanton, McNamara, Harding,
and Morrison 2007). The development of the method over recent years is driving com-
putational complexity to the edge as it uses modern computational approaches for the
combination of data. The R package sms presented in this work uses parallel processing
approaches for the efficient production of small area population microdata, which can
be subsequently used for geographical analysis. Finally, a complete case study of fitting
geographical data with the R package is presented and discussed.
Kavroudakis, D., Ballas, D. & Birkin, M., (2013). SimEducation: A Dynamic Spatial Microsimulation Model for Understanding Educational Inequalities. In R. Tanton & K. Edwards, eds. Spatial Microsimulation:Understanding Population Trends and Processes. Springer Netherlands, pp. 209–222
Spatial microsimulation models can be used to produce small area output for a deeper understandin... more Spatial microsimulation models can be used to produce small area output for a deeper understanding of inequality. Dynamic spatial microsimulation models can be used to model transitions such as leaving home, entering school, university, the labour market, etc. This chapter presents a dynamic spatial microsimulation approach to the analysis of educational inequalities. The method simulates individual units (potential students) over a period of time. This chapter describes a model that utilises the BHPS dataset to build a dynamic spatial microsimulation model for the analysis of social and spatial inequalities in educational attainment. Educational attainment is particularly suitable for the development and application of a dynamic spatial microsimulation model given the influence that education has on a person’s life outcomes. The dynamic spatial microsimulation model described in this chapter has been used in a case study to analyse social and spatial inequalities in higher education entry and attainment.
Kavroudakis, D., (2012) Open source approach to contemporary research: the case of Geo-information technology in ed: Shalin Hai-Jew, Open-Source Technologies for Maximizing the Creation, Deployment, and Use of Digital Resources and Information, IGI Global, Hershey PA, USA
Kavroudakis, D., Gounari, D., Aranitou, V., - (2012) - Point patern analysis of closing retaill shops in Athens (Greek language), Economic Crisis, development and cohesion policies, RSAI-ERSA Greek Section
Kavroudakis, D., Kyriakides, P. - (2011) - DTh 1.0: An Artificial Intelligence health Decision Support System - 17th European Colloquium on Quantitative and Theoretical Geography (ECQTG2011), Athens, Greece, 2-5 September 2011
Kavroudakis, D., Ballas, D. - (2011) - Agent-based modelling for labour force analysis - Annual meeting of European Association of Geographers: EUROGEO, Athens, Greece, 2-5 June 2011
Longley,P., Kavroudakis, D., Mateos, P., Milton, R., Batty, M. - (2009) - Geovisualisation of the 2011 UK Census: Bringing the decennial Census to the Google generation, Association of American Geographers (AAG), 2009-Annual meeting, session: "Neo-geography", 22-27 March 2009, Las Vegas, USA
Kavroudakis, D., Ballas, D., Birkin, M. - (2008) - Using Spatial Microsimulation for the analysis of social and spatial inequalities, Studying, Modeling and Sense making of Planet Earth International Conference, 1-6 June 2008, University of the Aegean, Geography Department, Mytilene Lesvos Greece
Kavroudakis, D., Ballas, D., Birkin, M. - (2007) - Static spatial microsimulation: A comparison study of metaheuristic algorithms, 1st international Conference of International Microsimulation Association, 19-22 August 2007 in Vienna Austria
Kavroudakis, D., Ballas, D., Birkin, M. - (2007) - Spatial microsimulation: Enriching the Census of Population, 15th European Colloquium of Theoretical and Quantitative Geography, 7-11 September 2007 in Montreux Switzerland
Kavroudakis, D., Ballas, D., Birkin, M. - (2006) - Building an object-oriented spatial microsimulation model for public policy analysis, 46th congress of the European Regional Science Association, Volos, Greece(theme: Geographical Information Systems and Spatial Analysis), 30 August-3 September 2006
Kavroudakis, D., Ballas, D., Birkin, M. - (2006) - Spatial microsimulation modelling for public policy analysis, 36th annual conference of Regional Science Association International: British and Irish Section, Jersey, Channel Islands,(theme: Social and Public Policy)16 August - 18 August 2006
Kavroudakis, D., Ballas, D. - (2006) - Microsimulation: Simulating Societies - Department of Work and Pensions, 18 May 2006, Sheffield, UK
Kavroudakis, D. - (2006) - Dynamic Spatial Microsimulation, Mid-Term Conference and AGM of the Royal Geographic Society with IBS, Newcastle, United Kingdom(theme: Geographical Information Systems), March 2006
Kavroudakis, D., Kyriakides, P. - (2011) - DTh 1.0: An Artificial Intelligence health Decision Support System - 17th European Colloquium on Quantitative and Theoretical Geography (ECQTG2011), Athens, Greece, 2-5 September 2011
Kavroudakis, D., Ballas, D., - (2012) - Example use of Microsimulation methodologies in Greece (Greek language), Economic Crisis, development and cohesion policies, RSAI-ERSA Greek Section
Use of Spatial Microsimulation for researching social and spatial inequalities
This paper presents a spatial microsimulation approach to the analysis of social and spatial ineq... more This paper presents a spatial microsimulation approach to the analysis of social and spatial inequalities in higher education attainment. The paper provides a brief review of microsimulation and spatial microsimulation, highlighting the paucity in applications aimed at the analysis of educational policy. It then briefly reviews the educational policy framework in Britain and discusses relevant application areas for spatial microsimulation. It also demonstrates how spatial microsimulation modelling can be used to generate educational policy-relevant outputs and to map and analyse social and spatial inequalities in educational attainment. The paper presents three educational policy scenarios and uses a spatial microsimulation model to assess their spatial and social impact in the region of Yorkshire and the Humber, UK. Finally, in the light of the model outputs and policy analysis scenarios, the paper discusses possible future extensions and policy applications. One of the major findings is the division in the participation of young people to higher education changes by where they live.
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Publications by Dimitris Kavroudakis
holds, individuals or businesses in the finest possible scale. This process requires the use
of individual based microdatasets. The package presented in this work facilitates the pro-
duction of small area population microdata by combining various datasets such as census
data and individual based datasets. This package includes a parallel implementation of
random selection with optimization to select a group of individual records that match a
macro description. This methodological approach has been used in a number of topics
ranging from measuring inequalities in educational attainment (Kavroudakis, Ballas, and
Birkin 2012) to estimating poverty at small area levels (Tanton, McNamara, Harding,
and Morrison 2007). The development of the method over recent years is driving com-
putational complexity to the edge as it uses modern computational approaches for the
combination of data. The R package sms presented in this work uses parallel processing
approaches for the efficient production of small area population microdata, which can
be subsequently used for geographical analysis. Finally, a complete case study of fitting
geographical data with the R package is presented and discussed.