Relevant bibliographies by topics / Complex real-world problems

Academic literature on the topic 'Complex real-world problems'

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Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Complex real-world problems"

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Turco, Alessandro, and Carlos Kavka. "MFGA: a GA for complex real-world optimisation problems." International Journal of Innovative Computing and Applications 3, no. 1 (2011): 31. http://dx.doi.org/10.1504/ijica.2011.037949.

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Pelikán, Emil. "FORECASTING OF PROCESSES IN COMPLEX SYSTEMS FOR REAL-WORLD PROBLEMS : TUTORIAL." Neural Network World 24, no. 6 (2014): 567–89. http://dx.doi.org/10.14311/nnw.2014.24.032.

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Li, Z. G. "Using Electron Diffraction Technique to Solve Real World Problems." Microscopy and Microanalysis 7, S2 (August 2001): 554–55. http://dx.doi.org/10.1017/s1431927600028841.

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Electron diffraction can be a very useful technique in solving real world structure-related problems. However, electron diffraction is much less widely used in industry compared to x-ray diffraction for several reasons. So far, application of electron diffraction has been limited to large-sized companies either to characterize newly synthesized materials in a research division or to directly support business activities in an analytical laboratory. New materials produced on a commercial scale are more and more complex with micro-, even nano-meter sized structures. Development of these materials on a commercial scale, for example, high temperature superconducting compounds, fullerenes, and giant magneoresistance devices [1-7], has increased demand for electron diffraction techniques considerably. Here, I would like to review how electron microscopists in industry solve their real world problems using electron diffraction techniques [8].Unit cell determination. Unit cell parameters and atom coordinates of a crystal can be routinely determined by single crystal x-ray technique if the crystal is large enough (about 0.1 mm in size).
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Sintov, Nicole, Debarun Kar, Thanh Nguyen, Fei Fang, Kevin Hoffman, Arnaud Lyet, and Milind Tambe. "Keeping it Real: Using Real-World Problems to Teach AI to Diverse Audiences." AI Magazine 38, no. 2 (July 1, 2017): 35–47. http://dx.doi.org/10.1609/aimag.v38i2.2733.

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In recent years, AI-based applications have increasingly been used in real-world domains. For example, game theory-based decision aids have been successfully deployed in various security settings to protect ports, airports, and wildlife. This article describes our unique problem-to-project educational approach that used games rooted in real-world issues to teach AI concepts to diverse audiences. Specifically, our educational program began by presenting real-world security issues, and progressively introduced complex AI concepts using lectures, interactive exercises, and ultimately hands-on games to promote learning. We describe our experience in applying this approach to several audiences, including students of an urban public high school, university undergraduates, and security domain experts who protect wildlife. We evaluated our approach based on results from the games and participant surveys.
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Niess, Margaret L., Pejmon Sadri, and Kwangho Lee. "Mathematical Explorations: Variables and Spreadsheets Connect with Real-World Problems." Mathematics Teaching in the Middle School 13, no. 7 (March 2008): 423–31. http://dx.doi.org/10.5951/mtms.13.7.0423.

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Spreadsheet software is generally available in schools and is in wide-spread use in business. The use of spreadsheets can help students make mathematical connections with problems in the world around them. Many real-life quantitative problems require algebra for decision making. Examples include the impact of rising gas prices on family budgets; the amount of gasoline left in the tank of a car and the distance to the nearest gas station; and the level of monthly income versus money needed to pay for food, rent, utilities, and clothing. Although these issues do not require complex mathematics, they do require knowledge of basic algebra involving variables and equations.
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Sutherland, Betsy M. "UV effects in “the real world”: problems of UV dosimetry in complex organisms." Journal of Photochemistry and Photobiology B: Biology 40, no. 1 (August 1997): 8–13. http://dx.doi.org/10.1016/s1011-1344(97)82942-9.

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Gürses, Dildar, Nantiwat Pholdee, Sujin Bureerat, Sadiq M. Sait, and Ali Rıza Yıldız. "A novel hybrid water wave optimization algorithm for solving complex constrained engineering problems." Materials Testing 63, no. 6 (June 1, 2021): 560–64. http://dx.doi.org/10.1515/mt-2020-0093.

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Abstract In this work, a new hybrid optimization algorithm (HWW-NM), which combines the Nelder-Mead local search algorithm with the water wave algorithm, is introduced to solve real-world engineering optimization problems. This paper is one of the first studies in which both the water wave algorithm and the HWW-NM are applied to processing parameters optimization for manufacturing processes. HWW-NM performance is measured using the cantilever beam problem. Additionally, a problem for milling manufacturing optimization is posed and solved to evaluate HWW-NM performance in real-world applications. The results reveal that HWW-NM is an attractive optimization approach for optimizing real-life problems.
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He, Cheng, Ye Tian, Handing Wang, and Yaochu Jin. "A repository of real-world datasets for data-driven evolutionary multiobjective optimization." Complex & Intelligent Systems 6, no. 1 (November 11, 2019): 189–97. http://dx.doi.org/10.1007/s40747-019-00126-2.

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Abstract Many real-world optimization applications have more than one objective, which are modeled as multiobjective optimization problems. Generally, those complex objective functions are approximated by expensive simulations rather than cheap analytic functions, which have been formulated as data-driven multiobjective optimization problems. The high computational costs of those problems pose great challenges to existing evolutionary multiobjective optimization algorithms. Unfortunately, there have not been any benchmark problems reflecting those challenges yet. Therefore, we carefully select seven benchmark multiobjective optimization problems from real-world applications, aiming to promote the research on data-driven evolutionary multiobjective optimization by suggesting a set of benchmark problems extracted from various real-world optimization applications.
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VASANT, P. "A NOVEL HYBRID GENETIC ALGORITHMS AND PATTERN SEARCH TECHNIQUES FOR INDUSTRIAL PRODUCTION PLANNING." International Journal of Modeling, Simulation, and Scientific Computing 03, no. 04 (November 18, 2012): 1250020. http://dx.doi.org/10.1142/s1793962312500201.

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Soft computing has attracted many research scientists, decision makers and practicing researchers in recent years as powerful computational intelligent techniques, for solving unlimited number of complex real-world problems particularly related to research area of optimization. Under the uncertain and turbulence environment, classical and traditional approaches are unable to obtain a complete solution with satisfaction for the real-world problems on optimization. Therefore, new global optimization methods are required to handle these issues seriously. One such method is hybrid Genetic algorithms and Pattern search, a generic, flexible, robust, and versatile framework for solving complex problems of global optimization and search in real-world applications.
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Stojanovic, Boban, Milos Ivanovic, Ana Kaplarevic-Malisic, Visnja Simic, Milovan Milivojevic, Djordje Nedic, Marina Svicevic, Nikola Milivojevic, and Srboljub Mijailovic. "Multi-modeling and multi-scale modeling as tools for solving complex real-world problems." Journal of Serbian Society for Computational Mechanics 10, no. 1 (2016): 34–49. http://dx.doi.org/10.5937/jsscm1601034s.

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Dissertations / Theses on the topic "Complex real-world problems"

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Cameron, Mark A., and Mark Cameron@csiro au. "A Problem Model for Decision Support Systems." The Australian National University. Faculty of Engineering and Information Technology, 2000. http://thesis.anu.edu.au./public/adt-ANU20020717.144031.

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This body of research focuses on supporting problem-stakeholders, decision-makers and problem-solvers faced with an ill-defined and complex real world problem. An ill-defined problem has a characteristic trait of continual refinement. That is, the definition of the problem changes throughout the problem investigation and resolution process. The central theme of this research is that a support system should provide problem stakeholders with a problem definition model for constructing and manipulating a representation of the definition of the problem as they understand it. The approach adopted herein is to first develop a problem definition model for ill-defined problems— the 6-Component problem definition model. With this model, it is then possible to move on to identifying the types of changes or modifications to the problem definition that problem stakeholders, decision makers and problem solvers may wish to explore. Importantly, there must be a connection between the surface representation of the problem and the underlying implementation of the support system. This research argues that by focusing the support system around the problem definition, it is possible to reduce the mismatch between the problem objectives and the representation of the problem that the support system offers. This research uses the Unified Modelling Language to record and explore the requirements that problem stakeholders, faced with an evolving problem definition, place on a support system. The 6-Component problem definition model is then embedded within a design for an evolutionary support system. This embedding, supported by collaboration diagrams, shows how a system using the 6-Component problem definition model will support stakeholders in their exploration, evaluation and resolution of an ill-defined and complex real-world problem. A case study provides validation of the effectiveness of the 6-Component problem definition model proposed and developed in this work. The case study uses the 6-Component problem definition model as a basis for implementing the Integration Workbench, an evolutionary support system for land-use planning. Stakeholders explore, communicate, evaluate and resolve the Tasmanian Regional Forest Agreement problem with assistance from the Integration Workbench.
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Stronge, Aideen J. "Age-related differences in strategies : investigating problem solving in a complex real-world task." Thesis, Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/30863.

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Moratori, Patrick. "Match-up strategies and fuzzy robust scheduling for a complex dynamic real world job shop scheduling problem." Thesis, University of Nottingham, 2013. http://eprints.nottingham.ac.uk/13054/.

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This thesis investigate a complex real world job shop scheduling / rescheduling problem, in which the presence of uncertainties and the occurrence of disruptions are tackled to produce efficient and reliable solutions. New orders arrive every day in the shop floor and they have to be integrated in the existent schedule. Match-up algorithms are introduced to collect the idle time on machines and accommodate these newly arriving orders. Their aim is to obtain new schedules with good performance which are at the same time highly stable, meaning that they resemble as closely as possible the initial schedule. Subsequently, a novel approach that combines these algorithms with a fuzzy robust scheduling system is proposed. The goal is to associate an effective repairing mechanism with the production of initial robust schedules that are able to facilitate the accommodation of future disruptions. Statistical analyses reveal that match-up algorithms are effective repairing strategies for managing complex disruptions, in which high quality stable schedules are delivered. Moreover, their combination with fuzzy robust scheduling has a positive effect on responding to these disruptions leading to even more reliable solutions in a real world dynamic and uncertain shop floor.
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Books on the topic "Complex real-world problems"

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Bammer, Gabriele. Disciplining Interdisciplinarity: Integration and Implementation Sciences for Researching Complex Real-World Problems. Canberra: ANU Press, 2013.

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Rastogi, P. N. Policy analysis and problem-solving for social systems: Toward understanding, monitoring, and managing complex real world problems. New Delhi: Sage Publications, 1992.

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Applied Computational Thinking with Python: Design algorithmic solutions for complex and challenging real-world problems. Packt Publishing, 2020.

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Golan, Amos. Inference in the Real World. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.003.0005.

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In this chapter I provide a mix of detailed cross-disciplinary examples to illustrate the method in real-world settings. The examples in this chapter illustrate modeling and inference in a relatively simple set of problems. After exploring single-parameter applications under very limited information, I consider multi-parameter problems, beginning with the inference of a two-parameter size distribution of firms. This demonstrates a main characteristic of social science problems where the available information is most often insufficient to provide a very exact inference. Then a simple ecological example is formulated. It provides an interesting theoretical application of analyzing complex ecological networks based on very limited macro-level information. The chapter concludes with a simple formulation of efficient network and information aggregation. A few shorter examples are provided as well.
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Levin, Ines, and Betsy Sinclair. Causal Inference with Complex Survey Designs. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.4.

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This article discusses methods that combine survey weighting and propensity score matching to estimate population average treatment effects. Beginning with an overview of causal inference techniques that incorporate data from complex surveys and the usefulness of survey weights, it then considers approaches for incorporating survey weights into three matching algorithms, along with their respective methodologies: nearest-neighbor matching, subclassification matching, and propensity score weighting. It also presents the results of a Monte Carlo simulation study that illustrates the benefits of incorporating survey weights into propensity score matching procedures, as well as the problems that arise when survey weights are ignored. Finally, it explores the differences between population-based inferences and sample-based inferences using real-world data from the 2012 panel of The American Panel Survey (TAPS). The article highlights the impact of social media usage on political participation, when such impact is not actually apparent in the target population.
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Apostolopoulos, Yorghos, Michael K. Lemke, and Kristen Hassmiller Lich, eds. Complex Systems and Population Health. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190880743.001.0001.

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Currently, population health science is an integral part of academic curricula around the world. For over a century, the principles of the reductionist paradigm have guided population health curricula, training, research, and action. Researchers continue to draw upon these principles when theorizing, conceptualizing, designing studies, analyzing, and devising interventions to tackle complex population health problems. However, unresolved impasses in delineating and managing pressing population health challenges have catalyzed calls for the integration of complex systems science–grounded theoretical, methodological, and analytical approaches into population health science. Mounting evidence denotes that a complex systems paradigm can bring about dramatic, multipronged changes for education and training and lead to innovative research, interventions, and policies. Despite the large and untapped promise of complex systems, the haphazard knowledge base from which academics, researchers, students, policymakers, and practitioners can draw has slowed their integration into the population health sciences. This volume fulfills this growing need by providing the knowledge base necessary to introduce a holistic complex systems paradigm in population health science. As such, it is the first comprehensive book in population health science that meaningfully integrates complex systems theory, methodology, modeling, computational simulation, and real-world applications, while incorporating current population health theoretical, methodological, and analytical perspectives. It is intended as a programmatic primer across a broad spectrum of population health stakeholders—from university professors and graduate students to researchers, policymakers, and practitioners. This book also aims to provoke long-overdue discourse on the need for updated new curricula in the population health sciences.
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Krohn, Wolfgang. Interdisciplinary Cases and Disciplinary Knowledge. Edited by Robert Frodeman. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780198733522.013.5.

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“Interdisciplinary Cases and Disciplinary Knowledge: Epistemic Challenges of Interdisciplinary Research” provides a conceptual framework of interdisciplinarity in the context of contemporary philosophy of science and social epistemology. It describes a widespread tension between the interdisciplinary commitment to complex real-world problems and the disciplinary strategies to build simplified models. While real-world problems call for highly specific and context-sensitive solutions, disciplinary problems serve as exemplars of more a general type. The epistemological challenge of interdisciplinarity is to relate knowledge about complex and singular cases with knowledge about generalized concepts and causalities. This relationship calls for a combination between the “humanistic” ideal of understanding the individual case, and the “scientific” search for common features of different cases. In practice interdisciplinary projects find ways to bridge causal explanation and the concern for the case. An epistemological attempt is made to conceptually integrate the search for universally applicable knowledge and idiographic richness.
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Golan, Amos. Advanced Inference in the Real World. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199349524.003.0006.

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In this chapter I continue the voyage into info-metrics in action, with an emphasis on more advanced info-metric inference in real-world environments. I develop a sequence of increasingly complex applications. In the first example, the maximum entropy method is extended for inferring interval information, with an application to weather data. The next example introduces additional conditional information into the constraints. It is a laboratory example, complemented with simulated data matched to observed population frequencies. The last example is the most complex, using surprisal analysis and Bayes’s rule to infer conditional probabilities from brain tumor data. In each problem the quantities whose entropy is maximized are identified and motivated. These examples demonstrate the power and generality of the info-metrics framework by showing that it allows inference in a variety of realistic settings.
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Stern, Marc J. Introduction: Why would you want to read a book about social science theory? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198793182.003.0001.

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This chapter provides a clear introduction to the book, explaining the value of social science theories in developing strategies for solving complex environmental problems. It articulates why technical fixes alone, even brilliant ones based on excellent science, are rarely sufficient to influence meaningful change. Without navigating the complexities of human behaviors and relationships, their implementation is rarely effective. Social scientists have developed a massive amount of knowledge about these complexities, resulting in well-tested theories. This book is about turning those theories into strategies. This chapter explains the layout of the book and provides tips for how to make best use of it. Readers are encouraged to approach the book with an adaptive mindset, which should better enable readers to consider multiple theories within the context of any specific real world problem they might face.
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Comp, T. Allan. From Environmental Liability to Community Asset. Edited by Paula Hamilton and James B. Gardner. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199766024.013.11.

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This chapter explores linking economic redevelopment with a recognition of regional legacy. It provided an opportunity to apply public history to real-world needs and to do something with history on a larger scale and led to the work discussed here. “AMD&ART” is now both the name of a park in Vintondale, Pennsylvania, and the name of an idea, a commitment to interdisciplinary work in the service of community aspirations to address environmental challenges. As an idea, AMD&ART is a lasting antidote to the complex problems of coal country that is, and in fact must be, cultural and environmental; only a place-based multidisciplinary solution that starts with good history has the power to transform environmental liabilities into community assets that engage a broad spectrum of support.
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Book chapters on the topic "Complex real-world problems"

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Bartolini, Andrea, Michele Lombardi, Michela Milano, and Luca Benini. "Neuron Constraints to Model Complex Real-World Problems." In Principles and Practice of Constraint Programming – CP 2011, 115–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23786-7_11.

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Domik, Gitta, and Gerhard Fischer. "Coping with Complex Real-World Problems: Strategies for Developing the Competency of Transdisciplinary Collaboration." In Key Competencies in the Knowledge Society, 90–101. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15378-5_9.

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Dagliana, Giulia, Sara Albolino, Zewdie Mulissa, Jonathan Davy, and Andrew Todd. "From Theory to Real-World Integration: Implementation Science and Beyond." In Textbook of Patient Safety and Clinical Risk Management, 143–57. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59403-9_12.

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AbstractThe increasing complexity and dynamicity of our society (and world of work) have meant that healthcare systems have and continue to change and consequently the state of healthcare systems continues to assume different characteristics. The causes of mortality are an excellent example of this rapid transformation: non-communicable diseases have become the leading cause of death, according to World Health Organization (WHO) data, but at the same time there are new problems emerging such as infectious diseases, like Ebola or some forms of influenza, which occur unexpectedly or without advanced warning. Many of these new diseases diffuse rapidly through the different parts of the globe due to the increasingly interconnected nature of the world. Another example of the healthcare transformation is the innovation associated with the introduction and development of advanced communication and technology systems (such as minimally invasive surgery and robotics, transplantation, automated antiblastic preparation) at all levels of care. Consequently, the social and technical dimensions of healthcare are becoming more and more complex and provide a significant challenge for all the stakeholders in the system to make sense of and ensure high quality healthcare. These stakeholders include but are not limited to patients and their families, caregivers, clinicians, managers, policymakers, regulators, and politicians. It is an inescapable truth that Humans are always going to be part of the healthcare systems, and it is these human, who by their very nature introduce variability and complexity to the system (we do not necessarily view this as a negative and this chapter will illustrate). A microlevel a central relationship in focus is that between the clinician and the patient, two human beings, making the health system a very peculiar organization compared to similarly high-risk organizations such as aviation or nuclear energy. This double human being system [1] requires significant effort (good design) in managing unpredictability through the development of personal and organization skills, such as the ability to react positively and rapidly to unexpected events and to adopt a resilient strategy for survival and advancement. In contrast to other similar industries, in terms of level of risk and system safety, healthcare settings are still plagued by numerous errors and negative events involving humans (and other elements) at various levels within the system. The emotional involvement is very high due to the exposure to social relationships daily and results in significant challenges to address both technical and non-technical issues simultaneously.
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Chen, Yuhan, Youyu Lu, Tianyi Gu, Zhirui Bian, Likai Wang, and Ziyu Tong. "From Separation to Incorporation - A Full-Circle Application of Computational Approaches to Performance-Based Architectural Design." In Proceedings of the 2021 DigitalFUTURES, 189–98. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5983-6_18.

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AbstractIn performance-based architectural design, most existing techniques and design approaches to assisting designers are primarily for a single design problem such as building massing, spatial layouts, or facade design. However, architectural design is a synthesis process that considers multiple design problems. Thus, for achieving an overall improvement in building performance, it is critical to incorporate computational techniques and methods into all key design problems. In this regard, this paper presents a full-circle application of different computational design approaches and tools to exploit the potential of building performance in driving architectural design towards more novel and sustainable buildings as well as to explore new research design paradigms for performance-based architectural design in real-world design scenarios. This paper takes a commercial complex building design as an example to demonstrate how building performance can be incorporated into different building design problems and reflect on the limitations of existing tools in supporting the architectural design.
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Granell, Carlos, Andreas Kamilaris, Alexander Kotsev, Frank O. Ostermann, and Sergio Trilles. "Internet of Things." In Manual of Digital Earth, 387–423. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9915-3_11.

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Abstract Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things (IoT) emerged as a holistic proposal to enable an ecosystem of varied, heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing today’s pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efficient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identified synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth.
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Cheek, Dennis W., and Kim A. Cheek. "Business Students Meet the Real World: Creative Problem-Solving via a Complex Role-Playing Simulation." In Educational Technology Beyond Content, 249–59. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37254-5_21.

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Mozer, Michael C., and Debra Miller. "Parsing the stream of time: The value of event-based segmentation in a complex real-world control problem." In Adaptive Processing of Sequences and Data Structures, 370–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0054005.

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Rabiee, Maryam, and A. Min Tjoa. "From Abstraction to Implementation: Can Computational Thinking Improve Complex Real-World Problem Solving? A Computational Thinking-Based Approach to the SDGs." In Information and Communication Technologies for Development, 104–16. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59111-7_10.

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Majumdar, Rupak, Aman Mathur, Marcus Pirron, Laura Stegner, and Damien Zufferey. "Paracosm: A Test Framework for Autonomous Driving Simulations." In Fundamental Approaches to Software Engineering, 172–95. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71500-7_9.

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AbstractSystematic testing of autonomous vehicles operating in complex real-world scenarios is a difficult and expensive problem. We present Paracosm, a framework for writing systematic test scenarios for autonomous driving simulations. Paracosm allows users to programmatically describe complex driving situations with specific features, e.g., road layouts and environmental conditions, as well as reactive temporal behaviors of other cars and pedestrians. A systematic exploration of the state space, both for visual features and for reactive interactions with the environment is made possible. We define a notion of test coverage for parameter configurations based on combinatorial testing and low dispersion sequences. Using fuzzing on parameter configurations, our automatic test generator can maximize coverage of various behaviors and find problematic cases. Through empirical evaluations, we demonstrate the capabilities of Paracosm in programmatically modeling parameterized test environments, and in finding problematic scenarios.
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Roderick, Ian. "An Exploration of Thinking About Complex Global Issues and Then Taking Action." In Systems Research for Real-World Challenges, 102–46. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5996-2.ch004.

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There are many problems and challenges facing the world. They go beyond problems that can be solved. They present as continual challenges that perpetually shift and transform themselves. The word we use for these situations are issues and they are by nature complex and large scale – they are global and long term. However, action does follow thinking and talking, even if that action is internalized. This chapter explores thinking about complex global issues and taking action.
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Conference papers on the topic "Complex real-world problems"

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Tinker, Scott W. "GEOSCIENCES AND ENERGY: COMPLEX PROBLEMS, INTEGRATED SOLUTIONS, REAL WORLD IMPACTS." In GSA Annual Meeting in Denver, Colorado, USA - 2016. Geological Society of America, 2016. http://dx.doi.org/10.1130/abs/2016am-285278.

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Grizioti, Marianthi, and Chronis Kynigos. "Children as players, modders, and creators of simulation games: A design for making sense of complex real-world problems." In IDC '21: Interaction Design and Children. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3459990.3460706.

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Mobley, Dave. "Multi-Agent Systems of Inverse Reinforcement Learners in Complex Games." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/755.

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Real-world problems exhibit a few defining criteria that make them hard for computers to solve. Problems such as driving a car or flying a helicopter have primary goals of reaching a destination as well as doing it safely and timely. These problems must each manage many resources and tasks to achieve their primary goals. The tasks themselves are made up of states that are represented by variables or features. As the feature set grows, the problems become intractable. Computer games are smaller problems but also are representative of real-world problems of this type. In my research, I will look at a particular class of computer game, namely computer role-playing games (RPGs), which are made up of a collection of overarching goals such as improving the player avatar, navigating a virtual world, and keeping the avatar alive. While playing there are also subtasks such as combatting other characters and managing inventory which are not primary, but yet important to overall game play. I will be exploring tiered Reinforcement Learning techniques coupled with training from expert policies using Inverse Reinforcement Learning as a starting point on learning how to play a complex game while attempting to extrapolate ideal goals and rewards.
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Be´nabe`s, Julien, Emilie Poirson, Fouad Bennis, and Yannick Ravaut. "Interactive Modular Optimization Strategy for Layout Problems." In ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/detc2011-47925.

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Layout design optimization has a significant impact in the design and use of many engineering products and systems. Real-world layout problems are usually considered as complex problems because of the geometry of components, the problem density and the great number of designer’s requirements. Solving these optimization problems is a hard and time consuming task. This paper proposes an interactive modular optimization strategy which allows the designer to find optimal solutions in a short period of calculation time. This generic strategy is based on a genetic algorithm, combined with specific optimization modules. These modules improve the global performances of the algorithm. This approach is adapted to multi-objective optimization problems and interactivity between the designer and the optimization process is used to make a final choice among design alternatives. This optimization strategy is tested on a real-world application which deals with the search of an optimal spatial arrangement of a shelter.
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Al-Ani, Dhafar, and Saeid Habibi. "A New Particle Swarm Optimization and Differential Evolution Technique for Constrained Optimization Problems." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63877.

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Real-world problems are often complex and may need to deal with constrained optimization problems (COPs). This has led to a growing interest in optimization techniques that involve more than one objective function to be simultaneously optimized. Accordingly, at the end of the multi-objective optimization process, there will be more than one solution to be considered. This enables a trade-off of high-quality solutions and provides options to the decision-maker to choose a solution based on qualitative preferences. Particle Swarm Optimization (PSO) algorithms are increasingly being used to solve NP-hard and constrained optimization problems that involve multi-objective mathematical representations by finding accurate and robust solutions. PSOs are currently used in many real-world applications, including (but not limited to) medical diagnosis, image processing, speech recognition, chemical reactor, weather forecasting, system identification, reactive power control, stock exchange market, and economic power generation. In this paper, a new version of Multi-objective PSO and Differential Evolution (MOPSO-DE) is proposed to solve constrained optimization problems (COPs). As presented in this paper, the proposed MOPSO-DE scheme incorporates a new leader(s) updating mechanism that is invoked when the system is under the risk of converging to premature solutions, parallel islands mechanism, adaptive mutation, and then integrated to the DE in order to update the particles’ best position in the search-space. A series of experiments are conducted using 12 well-known benchmark test problems collected from the 2006 IEEE Congress on Evolutionary Computation (CEC2006) to verify the feasibility, performance, and effectiveness of the proposed MOPSO-DE algorithm. The simulation results show the proposed MOPSO-DE is highly competitive and is able to obtain the optimal solutions for the all test problems.
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Zhao, Wei-Ye, Suqin He, Chengtao Wen, and Changliu Liu. "Contact-Rich Trajectory Generation in Confined Environments Using Iterative Convex Optimization." In ASME 2020 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/dscc2020-3208.

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Abstract Applying intelligent robot arms in dynamic uncertain environments (i.e., flexible production lines) remains challenging, which requires efficient algorithms for real time trajectory generation. The motion planning problem for robot trajectory generation is highly nonlinear and nonconvex, which usually comes with collision avoidance constraints, robot kinematics and dynamics constraints, and task constraints (e.g., following a Cartesian trajectory defined on a surface and maintain the contact). The nonlinear and nonconvex planning problem is computationally expensive to solve, which limits the application of robot arms in the real world. In this paper, for redundant robot arm planning problems with complex constraints, we present a motion planning method using iterative convex optimization that can efficiently handle the constraints and generate optimal trajectories in real time. The proposed planner guarantees the satisfaction of the contact-rich task constraints and avoids collision in confined environments. Extensive experiments on trajectory generation for weld grinding are performed to demonstrate the effectiveness of the proposed method and its applicability in advanced robotic manufacturing.
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Kock, Ned, Robert Aiken, David Dalton, David Elesh, Anthony Ranere, and Cheryl Sandas. "Team Teaching an Advanced Computer Fluency Course: A Composite Perspective." In 2003 Informing Science + IT Education Conference. Informing Science Institute, 2003. http://dx.doi.org/10.28945/2630.

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This paper discusses the observations of six instructors who team-taught an advanced computer fluency course over a period of three years. The course exposed students to complex information technology applications, such as geographic information and molecular design systems, in specific professional domains. One of the main goals of the course was to give students a glimpse at real-world applications of information technology aimed at solving complex problems. In addition to providing personal observations we summarize some of the problems that were encountered and how we addressed them. Also, the result of analyzing some preliminary data is discussed. The goal is to assist other instructors who might be interested in designing/teaching a similar course.
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W. Dixon, Michael, and Terry W. Koziniec. "Using OPNET to Enhance Student Learning in a Data Communication Course." In 2002 Informing Science + IT Education Conference. Informing Science Institute, 2002. http://dx.doi.org/10.28945/2466.

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It is difficult to teach data communications because it involves complex, dynamic processes which are not visible to students and are hard for them to conceptualise. This paper describes a project to improve the learning of students enrolled in the data communications courses. In this project the traditional mode of teaching data communications was supplemented by a problem solving approach using OPNETO a software environment for modelling, simulating, and analyzing the performance of communications networks. This mode of teaching enabled students to gain experience solving real world data communications problems without requiring the University to invest heavily in communications hardware and software which would quickly become obsolete.
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Bayrak, Alparslan Emrah, Christopher McComb, Jonathan Cagan, and Kenneth Kotovsky. "A Differential Game Approach to Dynamic Competitive Decisions Toward Human-Computer Collaboration." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97619.

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Abstract Partnership between humans and computers has a significant potential to extend the ability of humans to address complex design problems. This paper presents a decision-making process for computers to effectively collaborate with humans in the solution of complex problems under dynamic competition. In the proposed process, the computers learn strategies and objectives from prior experimental data and provide strategy suggestions to human collaborators. The study integrates clustering and sequential learning methods from machine learning with a differential game formulation based on model predictive control to find dynamic Nash equilibrium solutions to zero-sum games. The application of the proposed approach is demonstrated on the real-time strategy game Starcraft II that offers a dynamic competitive problem comparable in complexity to real-world applications. The results show that the proposed approach can successfully identify a variety of opening strategies in the experimental data for the initial phase of the process. The game-theoretic strategies in the later phases provide useful suggestions for low-performing players but are unnecessarily conservative for high-performing players where there is little opportunity for improvement. These results suggest a need for an assessment of the opponent expertise and a human intuition to judge the appropriateness of the game-theoretic suggestions for further improvement.
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Shady, Sally Fouad. "Traditional, Active and Problem-Based Learning Methods Used to Improve an Undergraduate Biomechanics Course." In ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-87478.

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Biomechanics is a core curriculum course taught in many biomedical engineering programs. Biomechanical analysis has become a necessary tool for both industry and research when developing a medical device. Despite its significance both inside and outside of the classroom, most students have demonstrated challenges in effectively mastering biomechanical concepts. Biomechanics requires adaptive skill sets needed to solve a multitude of problems from various disciplines and physiological systems. Many students taking biomechanics have not taken foundational courses that are necessary for in-depth learning and mastery of biomechanics. Consequently, limiting their ability to solve complex problems requiring strong foundations in statics, dynamics, fluid mechanics, and physiology. Active (AL) and problem-based learning (PBL) are techniques that has been widely used in medical education and allow faculty to implement engineering concepts into the context of disease solving real-world medical problems. This study investigates using both traditional and problem-based learning teaching pedagogy to enhance student learning in a senior level undergraduate biomechanics course. Results of this technique have shown an increase in student performance and self-assessments.
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Reports on the topic "Complex real-world problems"

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Perdigão, Rui A. P. Earth System Dynamic Intelligence - ESDI. Meteoceanics, April 2021. http://dx.doi.org/10.46337/esdi.210414.

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Earth System Dynamic Intelligence (ESDI) entails developing and making innovative use of emerging concepts and pathways in mathematical geophysics, Earth System Dynamics, and information technologies to sense, monitor, harness, analyze, model and fundamentally unveil dynamic understanding across the natural, social and technical geosciences, including the associated manifold multiscale multidomain processes, interactions and complexity, along with the associated predictability and uncertainty dynamics. The ESDI Flagship initiative ignites the development, discussion and cross-fertilization of novel theoretical insights, methodological developments and geophysical applications across interdisciplinary mathematical, geophysical and information technological approaches towards a cross-cutting, mathematically sound, physically consistent, socially conscious and operationally effective Earth System Dynamic Intelligence. Going beyond the well established stochastic-dynamic, information-theoretic, artificial intelligence, mechanistic and hybrid techniques, ESDI paves the way to exploratory and disruptive developments along emerging information physical intelligence pathways, and bridges fundamental and operational complex problem solving across frontier natural, social and technical geosciences. Overall, the ESDI Flagship breeds a nascent field and community where methodological ingenuity and natural process understanding come together to shed light onto fundamental theoretical aspects to build innovative methodologies, products and services to tackle real-world challenges facing our planet.
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Dalglish, Chris, and Sarah Tarlow, eds. Modern Scotland: Archaeology, the Modern past and the Modern present. Society of Antiquaries of Scotland, September 2012. http://dx.doi.org/10.9750/scarf.09.2012.163.

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The main recommendations of the panel report can be summarised under five key headings:  HUMANITY The Panel recommends recognition that research in this field should be geared towards the development of critical understandings of self and society in the modern world. Archaeological research into the modern past should be ambitious in seeking to contribute to understanding of the major social, economic and environmental developments through which the modern world came into being. Modern-world archaeology can add significantly to knowledge of Scotland’s historical relationships with the rest of the British Isles, Europe and the wider world. Archaeology offers a new perspective on what it has meant to be a modern person and a member of modern society, inhabiting a modern world.  MATERIALITY The Panel recommends approaches to research which focus on the materiality of the recent past (i.e. the character of relationships between people and their material world). Archaeology’s contribution to understandings of the modern world lies in its ability to situate, humanise and contextualise broader historical developments. Archaeological research can provide new insights into the modern past by investigating historical trends not as abstract phenomena but as changes to real lives, affecting different localities in different ways. Archaeology can take a long-term perspective on major modern developments, researching their ‘prehistory’ (which often extends back into the Middle Ages) and their material legacy in the present. Archaeology can humanise and contextualise long-term processes and global connections by working outwards from individual life stories, developing biographies of individual artefacts and buildings and evidencing the reciprocity of people, things, places and landscapes. The modern person and modern social relationships were formed in and through material environments and, to understand modern humanity, it is crucial that we understand humanity’s material relationships in the modern world.  PERSPECTIVE The Panel recommends the development, realisation and promotion of work which takes a critical perspective on the present from a deeper understanding of the recent past. Research into the modern past provides a critical perspective on the present, uncovering the origins of our current ways of life and of relating to each other and to the world around us. It is important that this relevance is acknowledged, understood, developed and mobilised to connect past, present and future. The material approach of archaeology can enhance understanding, challenge assumptions and develop new and alternative histories. Modern Scotland: Archaeology, the Modern past and the Modern present vi Archaeology can evidence varied experience of social, environmental and economic change in the past. It can consider questions of local distinctiveness and global homogeneity in complex and nuanced ways. It can reveal the hidden histories of those whose ways of life diverged from the historical mainstream. Archaeology can challenge simplistic, essentialist understandings of the recent Scottish past, providing insights into the historical character and interaction of Scottish, British and other identities and ideologies.  COLLABORATION The Panel recommends the development of integrated and collaborative research practices. Perhaps above all other periods of the past, the modern past is a field of enquiry where there is great potential benefit in collaboration between different specialist sectors within archaeology, between different disciplines, between Scottish-based researchers and researchers elsewhere in the world and between professionals and the public. The Panel advocates the development of new ways of working involving integrated and collaborative investigation of the modern past. Extending beyond previous modes of inter-disciplinary practice, these new approaches should involve active engagement between different interests developing collaborative responses to common questions and problems.  REFLECTION The Panel recommends that a reflexive approach is taken to the archaeology of the modern past, requiring research into the nature of academic, professional and public engagements with the modern past and the development of new reflexive modes of practice. Archaeology investigates the past but it does so from its position in the present. Research should develop a greater understanding of modern-period archaeology as a scholarly pursuit and social practice in the present. Research should provide insights into the ways in which the modern past is presented and represented in particular contexts. Work is required to better evidence popular understandings of and engagements with the modern past and to understand the politics of the recent past, particularly its material aspect. Research should seek to advance knowledge and understanding of the moral and ethical viewpoints held by professionals and members of the public in relation to the archaeology of the recent past. There is a need to critically review public engagement practices in modern-world archaeology and develop new modes of public-professional collaboration and to generate practices through which archaeology can make positive interventions in the world. And there is a need to embed processes of ethical reflection and beneficial action into archaeological practice relating to the modern past.
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Chandrasekhar, C. P. The Long Search for Stability: Financial Cooperation to Address Global Risks in the East Asian Region. Institute for New Economic Thinking Working Paper Series, March 2021. http://dx.doi.org/10.36687/inetwp153.

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Forced by the 1997 Southeast Asian crisis to recognize the external vulnerabilities that openness to volatile capital flows result in and upset over the post-crisis policy responses imposed by the IMF, countries in the sub-region saw the need for a regional financial safety net that can pre-empt or mitigate future crises. At the outset, the aim of the initiative, then led by Japan, was to create a facility or design a mechanism that was independent of the United States and the IMF, since the former was less concerned with vulnerabilities in Asia than it was in Latin America and that the latter’s recommendations proved damaging for countries in the region. But US opposition and inherited geopolitical tensions in the region blocked Japan’s initial proposal to establish an Asian Monetary Fund, a kind of regional IMF. As an alternative, the ASEAN+3 grouping (ASEAN members plus China, Japan and South Korea) opted for more flexible arrangements, at the core of which was a network of multilateral and bilateral central bank swap agreements. While central bank swap agreements have played a role in crisis management, the effort to make them the central instruments of a cooperatively established regional safety net, the Chiang Mai Initiative, failed. During the crises of 2008 and 2020 countries covered by the Initiative chose not to rely on the facility, preferring to turn to multilateral institutions such as the ADB, World Bank and IMF or enter into bilateral agreements within and outside the region for assistance. The fundamental problem was that because of an effort to appease the US and the IMF and the use of the IMF as a foil against the dominance of a regional power like Japan, the regional arrangement was not a real alternative to traditional sources of balance of payments support. In particular, access to significant financial assistance under the arrangement required a country to be supported first by an IMF program and be subject to the IMF’s conditions and surveillance. The failure of the multilateral effort meant that a specifically Asian safety net independent of the US and the IMF had to be one constructed by a regional power involving support for a network of bilateral agreements. Japan was the first regional power to seek to build such a network through it post-1997 Miyazawa Initiative. But its own complex relationship with the US meant that its intervention could not be sustained, more so because of the crisis that engulfed Japan in 1990. But the prospect of regional independence in crisis resolution has revived with the rise of China as a regional and global power. This time both economics and China’s independence from the US seem to improve prospects of successful regional cooperation to address financial vulnerability. A history of tensions between China and its neighbours and the fear of Chinese dominance may yet lead to one more failure. But, as of now, the Belt and Road Initiative, China’s support for a large number of bilateral swap arrangements and its participation in the Regional Comprehensive Economic Partnership seem to suggest that Asian countries may finally come into their own.
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