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8th International Congress on Environmental Modelling and Software - Environmental Modelling and Software for Supporting a Sustainable Future, iEMSs 2016

作者： Gibert, Karina Sànchez-Marrè, Miquel Izquierdo, Joaquín Rodríguez-Roda, Ignasi Hamilton, Serena Athanasiadis, Ioannis Ciampi, Antonio Holmes, Geoff Kuentz-Simonet, Vanessa Rambonilaza, Tina Statistics and Operations Research Department Universitat Politecnica de Catalunya Barcelona Catalonia Spain Computational Sciences Department Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Knowledge Engineering and Machine Learning Group Universitat Politecnica de Catalunya - Barcelona Catalonia Spain Grupo Multidisciplinar de Modelación de Fluidos Universidad Politécnica de Valencia Spain Catalan Institute for Water Research Girona Catalonia Spain Australian National University Canberra Australia Information Technologies Group Wageningen University Netherlands McGill University Montreal Canada Waikato University New Zealand IRSTEA Institut National de Recherché en Sciences et Technologies Pour L'environnement et L'agriculture Bordeaux France

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Stream C sessions 8

Stream C sessions

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8th International Congress on Environmental Modelling and Software - Environmental Modelling and Software for Supporting a Sustainable Future, iEMSs 2016

作者： Sànchez-Marrè, Miquel Gibert, Karina Erechtchoukova, Marina Computational Sciences Department Universitat Politècnica de Catalunya-BarcelonaTech Campus Nord Ed. Omega. Jordi Girona 1-3 Barcelona Catalonia08034 Spain Statistics and Operations Research Department Universitat Politecnica de Catalunya - Barcelona Tech Campus Nord Ed C5. Jordi Girona 1-3 Barcelona08034 Spain Knowledge Engineering and Machine Learning Group Universitat Politecnica de Catalunya - Barcelona Tech Campus Nord Ed Omega. Jordi Girona 1-3 Barcelona08034 Spain School of Information Technology Faculty of Liberal Arts and Professional Studies York University 4700 Keele Street TorontoONM3J 1P3 Canada

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ATLP: A color-based model of uncertainty to evaluate the risk of decisions based on prototypes

ATLP: A color-based model of uncertainty to evaluate the ris...

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作者： Gibert, Karina Conti, Dante Knowledge Engineering and Machine Learning group Department Statistics and Operation Research Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Spain Department of Operations Research Universidad de Los Andes Mérida Venezuela Instituto de Matemática Estadistica e Computacao Cientifica Departamento de Matemática Aplicada U. Estadual de Campinas Sao Paulo Brazil

Clustering techniques find homogeneous and distinguishable prototypes. Careful interpretation of these prototypes is crucial to assist the experts to better organize this know-how and to really improve their decision-making processes. The Traffic Lights Panel was introduced in 2009 as a postprocessing tool to provide understanding of clustering prototypes. In this work, annotated Traffic Lights Panel (aTLP) is presented as an enrichment of the TLP to manage the intrinsic uncertainty related with prototypes themselves. The aTLP handles uncertainty through a quantification of the prototypes' purity based on the variation coefficients (VC) and an associated color-based uncertainty model, with two dimensions-tone and saturation-representing nominal trend and purity of the prototype. An application to a waste-water treatment plant in Slovenia, in a discrete and continuous approach, suggests that aTLP seems a useful and friendly tool able to reduce the gap between data mining and effective decision support, towards informed-decisions. © 2015 - IOS Press and the authors.

关键词： Decision making

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Estimation of machine settings for spinning of yarns-new algorithms for comparing complex structures

Estimation of machine settings for spinning of yarns-new alg...

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22nd International Conference on Case-Based Reasoning Research and Development, ICCBR 2014

作者： Sevilla-Villanueva, Beatriz Sànchez-Marrè, Miquel Fischer, Thomas V. Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Jordi Girona 1-3 Barcelona Catalonia08034 Spain DITF Denkendorf Center for Management Research Koerschtalstr. 26 Denkendorf73770 Germany

ISBN: (纸本)9783319112084

The textile industry in Europe is facing a new challenge in order to stay competitive into the textile market. They need to be flexible, cost efficient and produce with high quality. The setting of the machinery parameters is therefore an important aspect that combines implicit knowledge of workers and engineers with explicit knowledge. This makes it an ideal domain for CBR. It is used for an automatic parameter setting but the data cannot be reduced to a flat representation, as yarns and fabrics are multicomponent artefacts. Therefore we propose a combination of 4 algorithms to evaluate the similarity of the yarns. The application was successfully applied for spinning and it can be applied in the following steps of the textile processes like weaving. © Springer International Publishing Switzerland 2014.

关键词： Textile industry

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Preface

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AI Communications 2015年第1期28卷 1-3页

作者： Gibert, Karina Sierra, Carles Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Spain Department of Statistics and Operation Research Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Spain Institut d'Investigació en Intelligència Artificial Bellaterra Spain

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Towards a framework for the analysis of provenance-aware norms in complex networks

Towards a framework for the analysis of provenance-aware nor...

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1st International Conference on Agreement Technologies, AT 2012

作者： Felipe, Luis Oliva Alvarez-Napagao, Sergio Vázquez-Salceda, Javier Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya Spain

Systemic analysis of dynamics in complex networks has allured interest from different fields. Norms are a mechanism that can be useful to govern or guide the behavior of agents in such scenarios. Such effects of norms can be analyzed in different terms, such as emergence, spread, equilibrium oscillations and stability. In this paper, we present an analysis of the life-cycle of deontic norms in scale-free networks, with special focus on the long-term effects of different agents' personalities and their structural properties. Our approach combines provenance-aware monitoring traces and the analysis of the dynamics emerged in the relations between agents by means of complex network representations.

关键词： Complex networks

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Case-based reasoning applied to textile industry processes

Case-based reasoning applied to textile industry processes

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20th International Conference on Case-Based Reasoning, ICCBR 2012

作者： Sevilla Villanueva, Beatriz Sànchez-Marrè, Miquel Knowledge Engineering Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Spain

ISBN: (纸本)9783642329852

This paper describes an innovative usage of Case-Based Reasoning to reduce the high cost derived from correctly setting the textile machinery within the framework of European MODSIMTex project. Furthermore, this system is capable of dealing with flexible queries, allowing to relax or restrict the searches in the case base. The paper discusses the ideas, design, implementation and an experimental evaluation of the CBR applied to the spinning scenario included in the project framework. © 2012 Springer-Verlag.

关键词： Textile industry

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Towards practical normative agents: A framework and an implementation for norm-aware planning

Towards practical normative agents: A framework and an imple...

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7th International Workshop on Coordination, Organizations, Institutions, and Norms in Agent System VII - IEEE/WIC/ACM International Conference on Intelligent Agent Technology, COIN@WI-IAT 2011

作者： Panagiotidi, Sofia Vázquez-Salceda, Javier Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya - BarcelonaTECH Campus Nord UPC Edifici K2M C/ Jordi Girona 1-3 08034 Barcelona Spain

ISBN: (纸本)9783642355448

Nowadays there is an important increase in the adoption and use ofdistributed computational solutions which are growing both in size (from tensto hundreds or even thousands of components, computational entities or actors)and in complexity (from closed, static, pre-defined interactions to more open,dynamic ones stablished at run-time). In this scenario one way to tame such complexityis to add a social layer on top regulating or shaping the behaviour of theactors in the system. One of those social abstractions that has been explored inliterature is the use of computational models of (social or organisational) *** of these approaches see norms as a way to specify acceptable agent behaviourin some (distributed) context. In literature there is a lot of work on normtheories, models and specifications on how agents might take norms into accountwhen reasoning but few practical implementations. In this paper we present a firststep into the implementation of practical normative agents by describing a frameworkand an implementation of norm-oriented planning. In this framework normscan be either obligations or prohibitions which can be violated, and are accompaniedby repair norms in case they are breached. Unlike most frameworks, ourapproach takes into consideration the operationalisation of norms during the plangeneration phase. Norm operational semantics is expressed as an extension/ontop of STRIPS semantics, acting as a form of temporal restrictions over the trajectories(plans) computed by the planner. In combination with the agent's utilityfunctions over the actions, the norm-aware planner computes the most profitabletrajectory concluding to a state of the world where no pending obligations existand any (obligation/prohibition) violation has been handled. An implementationof the framework in PDDL is described. © Springer-Verlag Berlin Heidelberg 2012.

关键词： Semantics

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Tools for environmental data Mining and intelligent Decision Support

Tools for environmental data Mining and intelligent Decision...

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6th Biennial Meeting of the International Environmental Modelling and Software Society: Managing Resources of a Limited Planet, iEMSs 2012

作者： Gibert, Karina Sànchez-Marrè, Miquel Sevilla, Beatriz Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Department of Statistics and Operation Research Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Software Department Universitat Politrcnica de Catalunya-BarcelonaTech Catalonia Spain

ISBN: (纸本)9788890357428

The joint workshop in Data Mining for Environmental Scientists and Intelligent Environmental Decision Support Systems tries to provide a common discussion forum to communicate environmentalists with data miners and intelligent decision support systems developers. As environmentalists are the consumers of both products, Data Mining (DM) and Intelligent Decision Support Systems (IDSS) are complementary disciplines that must properly link to permit the maximum benefits of data analysis at highest levels. Here, a preliminary analysis of the state of the software tools in environmental DM and IDSS is presented.

关键词： Data mining

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