28 research outputs found

    5th International Conference on Advanced Research Methods and Analytics (CARMA 2023)

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    Research methods in economics and social sciences are evolving with the increasing availability of Internet and Big Data sources of information. As these sources, methods, and applications become more interdisciplinary, the 5th International Conference on Advanced Research Methods and Analytics (CARMA) is a forum for researchers and practitioners to exchange ideas and advances on how emerging research methods and sources are applied to different fields of social sciences as well as to discuss current and future challenges.Martínez Torres, MDR.; Toral Marín, S. (2023). 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023). Editorial Universitat Politècnica de València. https://doi.org/10.4995/CARMA2023.2023.1700

    Understanding over-indebtedness in Portugal: descriptive and predictive models.

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    Over-indebtedness is a recurring problem in Portugal. After facing different economic cycles, between financial crises and prosperity periods, Portuguese consumers have been striving to keep their household finances stable and avoid being over-indebted. This project aims to gain insights on over-indebtedness, from different perspectives that range from the social to the economic point of view. It examines over-indebtedness from a psychological and from a data science perspective. In particular, we suggest that the systemic impact of financial crisis in Portugal not only promotes over-indebtedness, but it crafts a specific profile of over-indebted consumers which may be distinguished from other profiles, ranging from the emphasis on lack of self-regulation and careless management of one’s budget to other causal factors such as consumerism, crisis, and unemployment. Given this scenario, this project proposes the use of Machine Learning (ML) for developing descriptive and predictive models, to understand the influencing factors of over-indebtedness on Portuguese consumers and will be used for establishing consumer clusters and guidelines for over-indebtedness regulation and consumer financial empowerment.info:eu-repo/semantics/publishedVersio

    2020 Huskies Showcase Abstracts

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    The 2020 Huskies Showcase abstracts are arranged in the following order: Applied Experience Displays; Artistic Performances; Demonstrations; Gallery Exhibits; Oral Presentations; Poster Presentations

    The University of Iowa 2020-21 General Catalog

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    Trinity College Bulletin, 2020-2021

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    https://digitalrepository.trincoll.edu/bulletin/1670/thumbnail.jp

    Trinity College Bulletin, 2019-2020

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    https://digitalrepository.trincoll.edu/bulletin/1669/thumbnail.jp

    The University of Iowa 2019-20 General Catalog

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    Uso de diferentes algoritmos de otimização para definição de áreas de serviço de esquadras de polícia para Portugal

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Geographic Information Systems and ScienceA segurança é considerada um direito fundamental nos estados democráticos. É uma condição que exige cada vez mais ferramentas avançadas de análise espacial, para apoiar a adequação de recursos e a disposição espacial das forças de segurança. A reorganização das forças de segurança no contexto atual depende da distribuição da população e do seu dinamismo. O processo de agrupar pequenas áreas geográficas para formar as áreas de serviço é designado por districting. Esta dissertação tem como objetivo a otimização espacial das forças de segurança tendo em consideração a distribuição espacial da população residente do distrito administrativo de Setúbal. A análise de dados da população residente foi efetuada com a análise hot spot para estudar a sua distribuição ao nível da freguesia. Implementou-se um algoritmo genético e efetuaram-se testes experimentais com os dados da população residente e dos grupos vulneráveis, para criar áreas de serviço das esquadras de polícia. Compararam-se os resultados obtidos com o Automatic Zoning Procedure – Simulated Annealing (AZP-SA) utilizando os mesmos dados. A população do distrito concentra-se sobretudo na península de Setúbal, existindo uma grande assimetria na sua distribuição geográfica. Os testes experimentais com o algoritmo genético demonstram que as áreas de serviço criadas, apresentam uma soma das diferenças da população com uma grande variação. O AZP-SA obteve um desempenho ligeiramente superior ao algoritmo genético implementado. A implementação do algoritmo permitiu obter soluções de áreas de serviço, no entanto, o desempenho do AZP-SA foi ligeiramente superior. A grande assimetria da população do distrito administrativo de Setúbal dificultou a criação de áreas de serviço mais equitativas.Security is to consider being a fundamental right in democratic societies. It is a condition that requires advanced spatial analysis tools to support security forces in the spatial disposition and adequacy of resources. Nowadays security forces reorganization, depends on the population distribution and dynamic. Districting is the process of grouping small geographic areas in service areas. The main objective of this thesis is the spatial optimization of security forces considering the spatial disposition of the population in Setubal administrative district. Data analysis was done with the hot spot analysis to study the population and their distribution at freguesia level. A genetic algorithm was implemented to create service areas and experimental tests were performed with the population data and vulnerable groups. We compared the results with the Automatic Zoning Procedure - Simulated Annealing (AZP-SA). The population concentrates in Setubal peninsula denoting a great asymmetry on their geographical distribution. Experimental tests with the genetic algorithm show a large variation of a sum of the population differences in service areas. AZP-SA performed better than the genetic algorithm. The solutions for the service areas were obtained with the genetic algorithm. However, the performance of AZP-SA is slightly higher. The difficult to obtain equitable areas is due the great asymmetry of the population

    The University of Iowa 2018-19 General Catalog

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