705 research outputs found

    Graduate Catalog of Studies, 2023-2024

    Get PDF

    Explainable Artificial Intelligence Methods in FinTech Applications

    Get PDF
    The increasing amount of available data and access to high-performance computing allows companies to use complex Machine Learning (ML) models for their decision-making process, so-called ”black-box” models. These ”black-box” models typically show higher predictive accuracy than linear models on complex data sets. However, this improved predictive accuracy can only be achieved by deteriorating the explanatory power. ”Open the black box” and make the model predictions explainable is summarised under the research area of Explainable Artificial Intelligence (XAI). Using black-box models also raises practical and ethical issues, especially in critical industries such as finance. For this reason, the explainability of models is increasingly becoming a focus for regulators. Applying XAI methods to ML models makes their predictions explainable and hence, enables the application of ML models in the financial industries. The application of ML models increases predictive accuracy and supports the different stakeholders in the financial industries in their decision-making processes. This thesis consists of five chapters: a general introduction, a chapter on conclusions and future research, and three separate chapters covering the underlying papers. Chapter 1 proposes an XAI method that can be used in credit risk management, in particular, in measuring the risks associated with borrowing through peer-to-peer lending platforms. The model applies correlation networks to Shapley values and thus the model predictions are grouped according to the similarity of the underlying explanations. Chapter 2 develops an alternative XAI method based on the Lorenz Zonoid approach. The new method is statistically normalised and can therefore be used as a standard for the application of Artificial Intelligence (AI) in credit risk management. The novel ”Shapley-Lorenz”-approach can facilitate the validation of model results and supports the decision whether a model is sufficiently explained. In Chapter 3, an XAI method is applied to assess the impact of financial and non-financial factors on a firm’s ex-ante cost of capital, a measure that reflects investors’ perceptions of a firm’s risk appetite. A combination of two explanatory tools: the Shapley values and the Lorenz model selection approach, enabled the identification of the most important features and the reduction of the independent features. This allowed a substantial simplification of the model without a statistically significant decrease in predictive accuracy.The increasing amount of available data and access to high-performance computing allows companies to use complex Machine Learning (ML) models for their decision-making process, so-called ”black-box” models. These ”black-box” models typically show higher predictive accuracy than linear models on complex data sets. However, this improved predictive accuracy can only be achieved by deteriorating the explanatory power. ”Open the black box” and make the model predictions explainable is summarised under the research area of Explainable Artificial Intelligence (XAI). Using black-box models also raises practical and ethical issues, especially in critical industries such as finance. For this reason, the explainability of models is increasingly becoming a focus for regulators. Applying XAI methods to ML models makes their predictions explainable and hence, enables the application of ML models in the financial industries. The application of ML models increases predictive accuracy and supports the different stakeholders in the financial industries in their decision-making processes. This thesis consists of five chapters: a general introduction, a chapter on conclusions and future research, and three separate chapters covering the underlying papers. Chapter 1 proposes an XAI method that can be used in credit risk management, in particular, in measuring the risks associated with borrowing through peer-to-peer lending platforms. The model applies correlation networks to Shapley values and thus the model predictions are grouped according to the similarity of the underlying explanations. Chapter 2 develops an alternative XAI method based on the Lorenz Zonoid approach. The new method is statistically normalised and can therefore be used as a standard for the application of Artificial Intelligence (AI) in credit risk management. The novel ”Shapley-Lorenz”-approach can facilitate the validation of model results and supports the decision whether a model is sufficiently explained. In Chapter 3, an XAI method is applied to assess the impact of financial and non-financial factors on a firm’s ex-ante cost of capital, a measure that reflects investors’ perceptions of a firm’s risk appetite. A combination of two explanatory tools: the Shapley values and the Lorenz model selection approach, enabled the identification of the most important features and the reduction of the independent features. This allowed a substantial simplification of the model without a statistically significant decrease in predictive accuracy

    Graduate Catalog of Studies, 2023-2024

    Get PDF

    Climate Change and Critical Agrarian Studies

    Full text link
    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    Digital Innovations for a Circular Plastic Economy in Africa

    Get PDF
    Plastic pollution is one of the biggest challenges of the twenty-first century that requires innovative and varied solutions. Focusing on sub-Saharan Africa, this book brings together interdisciplinary, multi-sectoral and multi-stakeholder perspectives exploring challenges and opportunities for utilising digital innovations to manage and accelerate the transition to a circular plastic economy (CPE). This book is organised into three sections bringing together discussion of environmental conditions, operational dimensions and country case studies of digital transformation towards the circular plastic economy. It explores the environment for digitisation in the circular economy, bringing together perspectives from practitioners in academia, innovation, policy, civil society and government agencies. The book also highlights specific country case studies in relation to the development and implementation of different innovative ideas to drive the circular plastic economy across the three sub-Saharan African regions. Finally, the book interrogates the policy dimensions and practitioner perspectives towards a digitally enabled circular plastic economy. Written for a wide range of readers across academia, policy and practice, including researchers, students, small and medium enterprises (SMEs), digital entrepreneurs, non-governmental organisations (NGOs) and multilateral agencies, policymakers and public officials, this book offers unique insights into complex, multilayered issues relating to the production and management of plastic waste and highlights how digital innovations can drive the transition to the circular plastic economy in Africa. The Open Access version of this book, available at https://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license

    Libro de Abstracts | VIII Jornadas de Investigación y Doctorado: “Ética en la Investigación Científica”

    Get PDF
    El objetivo de estas Jornadas es promover el intercambio científico entre estudiantes de doctorado, fomentando la participación, el debate y la discusión, de aspectos científicos tan importantes como la ética de la investigación. Para poner en valor el papel de los doctores en la sociedad, no podemos pasar por alto las competencias transversales que estos deben adquirir en su formación como doctores. Si bien la ética es algo fundamental en todas las facetas de la vida, en el caso de los investigadores cobra especial relevancia, ya que son generadores de conocimiento sobre el que se asentarán futuros desarrollos y políticas de interés para toda la sociedad. Por lo tanto, con el fin de incrementar la proyección social de las investigaciones llevadas a cabo y la proyección profesional de los doctores, es importante incidir en su formación ética. La base de la investigación académica está construida sobre la confianza. Los investigadores confían en que los resultados informados por otros son veraces. La sociedad confía en que los resultados de la investigación reflejan un intento honesto por parte de los científicos de describir el mundo de forma precisa. Pero esta confianza sólo perdurará si la comunidad científica transmite los valores asociados a la conducta de la ética de investigación. Por este motivo, la Universidad juega un papel muy importante en la formación de los doctores en cuestiones éticas que son inherentes al método científico y a la generación de conocimiento. Dentro de las universidades, las Escuelas Internacionales de Doctorado, con nuestros recursos, aptitudes y espacio de influencia, nos convertimos en actores clave para promover actitudes éticas entre los doctorandos, y estas Jornadas son una oportunidad muy valiosa para tratar este tema. Las ramas de conocimiento que se incluyen para estas Jornadas son las derivadas de los programas de doctorado de la EIDUCAM: -Ciencias de la Salud -Tecnologías de la Computación e Ingeniería Ambiental -Ciencias Sociales -Ciencias del DeporteActividad Física y DeporteAdministración y Dirección de EmpresasAgricultura y VeterinariaArte y HumanidadesCiencias AmbientalesCiencias de la AlimentaciónCiencias de la ComunicaciónCiencias ReligiosasDerechoEducaciónEnfermeríaFarmaciaIdiomasIngeniería, Industria y ConstrucciónMedicinaOdontologíaPodologíaPsicologíaTerapia y RehabilitaciónTurism

    Revisiting the capitalization of public transport accessibility into residential land value: an empirical analysis drawing on Open Science

    Get PDF
    Background: The delivery and effective operation of public transport is fundamental for a for a transition to low-carbon emission transport systems’. However, many cities face budgetary challenges in providing and operating this type of infrastructure. Land value capture (LVC) instruments, aimed at recovering all or part of the land value uplifts triggered by actions other than the landowner, can alleviate some of this pressure. A key element of LVC lies in the increment in land value associated with a particular public action. Urban economic theory supports this idea and considers accessibility to be a core element for determining residential land value. Although the empirical literature assessing the relationship between land value increments and public transport infrastructure is vast, it often assumes homogeneous benefits and, therefore, overlooks relevant elements of accessibility. Advancements in the accessibility concept in the context of Open Science can ease the relaxation of such assumptions. Methods: This thesis draws on the case of Greater Mexico City between 2009 and 2019. It focuses on the effects of the main public transport network (MPTN) which is organised in seven temporal stages according to its expansion phases. The analysis incorporates location based accessibility measures to employment opportunities in order to assess the benefits of public transport infrastructure. It does so by making extensive use of the open-source software OpenTripPlanner for public transport route modelling (≈ 2.1 billion origin-destination routes). Potential capitalizations are assessed according to the hedonic framework. The property value data includes individual administrative mortgage records collected by the Federal Mortgage Society (≈ 800,000). The hedonic function is estimated using a variety of approaches, i.e. linear models, nonlinear models, multilevel models, and spatial multilevel models. These are estimated by the maximum likelihood and Bayesian methods. The study also examines possible spatial aggregation bias using alternative spatial aggregation schemes according to the modifiable areal unit problem (MAUP) literature. Results: The accessibility models across the various temporal stages evidence the spatial heterogeneity shaped by the MPTN in combination with land use and the individual perception of residents. This highlights the need to transition from measures that focus on the characteristics of transport infrastructure to comprehensive accessibility measures which reflect such heterogeneity. The estimated hedonic function suggests a robust, positive, and significant relationship between MPTN accessibility and residential land value in all the modelling frameworks in the presence of a variety of controls. The residential land value increases between 3.6% and 5.7% for one additional standard deviation in MPTN accessibility to employment in the final set of models. The total willingness to pay (TWTP) is considerable, ranging from 0.7 to 1.5 times the equivalent of the capital costs of the bus rapid transit Line-7 of the Metrobús system. A sensitivity analysis shows that the hedonic model estimation is sensitive to the MAUP. In addition, the use of a post code zoning scheme produces the closest results compared to the smallest spatial analytical scheme (0.5 km hexagonal grid). Conclusion: The present thesis advances the discussion on the capitalization of public transport on residential land value by adopting recent contributions from the Open Science framework. Empirically, it fills a knowledge gap given the lack of literature around this topic in this area of study. In terms of policy, the findings support LVC as a mechanism of considerable potential. Regarding fee-based LVC instruments, there are fairness issues in relation to the distribution of charges or exactions to households that could be addressed using location based measures. Furthermore, the approach developed for this analysis serves as valuable guidance for identifying sites with large potential for the implementation of development based instruments, for instance land readjustments or the sale/lease of additional development rights

    Overview of Aboriginal and Torres Strait Islander health status 2022

    Get PDF
    The main purpose of the Overview of Aboriginal and Torres Strait Islander health status (Overview) is to provide a comprehensive summary of the most recent indicators of the health and current health status of Australia’s Aboriginal and Torres Strait Islander people. The Overview has been prepared by HealthInfoNet staff as part of our contribution to supporting those who work in the Aboriginal and Torres Strait Islander health sector. The Overview is a key indicator of the HealthInfoNet’s commitment to authentic and engaged knowledge development and exchange. The initial sections of this Overview provide information about the context of Aboriginal and Torres Strait Islander health, population, and various measures of population health status. The subsequent sections are about specific health conditions and risk/protective factors that contribute to the overall health of Aboriginal and Torres Strait Islander people. These sections comprise an introduction about the condition and evidence of the current status of the condition or risk/protective factor and burden of disease. Information is provided for states and territories, Indigenous Regions and remoteness, and for demographics such as sex and age when it is available and appropriate..

    Circular economy practices and environmental performance: Analysing the role of big data analytics capability and responsible research and innovation

    Get PDF
    This study employs dynamic capability view theory to comprehend the interplay between big data analytics capability (BDAC), responsible research and innovation (RRI) and circular economy practices (CEPs) as an execution strategy for improving environmental performance. The study uses partial least square structural equation modelling to analyse primary survey data collected from 326 manufacturers. The results indicate that BDAC, RRI and CEPs favourably affect environmental performance. Notably, RRI emerges as the most influential factor among the three. Furthermore, the findings suggest that implementing CEPs serves as a partial mediator for the influence of BDAC and RRI on environmental performance. Surprisingly, the study finds that the moderating impact of resource commitment is not statistically significant in any of the three pairwise interactions involving BDAC, RRI and CEPs with respect to environmental performance. The results have various intriguing implications for how manufacturers can enhance their circular economy strategies to achieve better environmental performance, representing a noteworthy contribution to the foundational theory of the dynamic capability view. Finally, these findings also provide valuable insights to managers, enabling a deeper understanding of the determinants that contribute to deploying CEPs and improving environmental performance within a manufacturing setting.publishedVersio

    スマート農業のための信頼できるドキュメンテーションシステム

    Get PDF
    九州工業大学博士学位論文 学位記番号:情工博甲第373号 学位授与年月日:令和4年12月27日1 Introduction|2 Traditional Documentation|3 Blockchain-based Trust Management|4 Adopting Blockchain Method for Cocoa Farming Documentation|5 Implementation of Blockchain Concept into the Real Problem through a Simulation Case of Cocoa Production|6 Conclusion and Future Work九州工業大学令和4年
    corecore