2,084 research outputs found

    Choice of the substitution currency in Russia: How to explain the dollar's dominance?

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    The analysis of external economic relations of Russia reveals a paradox: while Europe is the main trade and direct investment partner of Russia, this is far from being the case concerning its currency’s role in Russia's financial activities. The dollar is much preferred by economic agents for financial operations. This paper proposes a disaggregated approach to this issue by separating the ‘means of exchange’ and ‘store of value’ components of the use of substitution currencies. The influence of three main factors (inertial component, real trade relations and exchange rate fluctuations) on the relative demand for the euro by Russian economic agents is tested for the period 1999-2004. Finally we suggest a theoretical interpretation of the results based on the conventions theory approach.dollarisation; euroisation; transition; Russia; currency substitution; asset substitution; network externalities; hysteresis; conventions

    Cased Based Reasoning in Business Process Management Design

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    Tueschen, P., & dos Santos, V. D. (2021). Cased Based Reasoning in Business Process Management Design. In R. Silhavy (Ed.), Artificial Intelligence in Intelligent Systems - Proceedings of 10th Computer Science On-line Conference, 2021 (Vol. 2, pp. 722-741). (Lecture Notes in Networks and Systems; Vol. 229). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-77445-5_65Case-based reasoning (CBR), another form of artificial intelligence, stores and retrieves past cases that can be adapted to find a solution to a current problem. The new solution can then be retained and made available to solve other future problems. Business Process Management analyzes and optimizes business processes to make them more effective and efficient for an organization’s strategy to ultimately increasing shareholder value. CBR can help to support BPM, making better decisions with existing knowledge when solving process problems. This study investigates effectively store, retrieve, and adapt Business Process Management Notation (BPMN) solutions that best fit the underlying BPM problem using CBR as a tool. Therefore, a theoretical model was proposed, containing each CBR live cycle phase with different possible tools applied to BPMN diagrams, which was validated by expert interviews. This study concludes that a whole CBR life cycle can be applied to BPMN diagram problems with the need for human intervention. The objective was not to solve the whole problem but to contribute to a possible solution by using CBR through a theoretical model.authorsversionpublishe

    Cased Based Reasoning in Business Process Management Design

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    Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementArtificial intelligence became increasingly useful since the 1990s, trying to imitate the human brain with its thinking, reasoning, and learning using the key concepts of machine learning, deep learning, and artificial neural networks. Case-based reasoning (CBR), another form of artificial intelligence, stores and retrieves past cases that can be adapted to find a solution to a current problem. The new solution can then be retained and made available to solve other future problems. Business Process Management (BPM) analyzes and optimizes business processes to make them more effective and efficient for an organization’s strategy to ultimately increasing shareholder value. CBR can help to support BPM, making better decisions with existing knowledge when solving process problems. This study investigates effectively store, retrieve, and adapt Business Process Management Notation (BPMN) solutions that best fit the underlying BPM problem using case-based reasoning as a tool. Therefore, a theoretical model was proposed, containing each CBR live cycle phase with different possible tools applied to BPMN diagrams, which was validated by expert interviews. This study concludes that a whole CBR life cycle can be applied to BPMN diagram problems with the need for human intervention. This work did not have the objective to solve the whole problem but to contribute to a possible solution by using CBR through a theoretical model

    Online Build-Order Optimization for Real-Time Strategy Agents Using Multi-Objective Evolutionary Algorithms

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    The investigation introduces a novel approach for online build-order optimization in real-time strategy (RTS) games. The goal of our research is to develop an artificial intelligence (AI) RTS planning agent for military critical decision- making education with the ability to perform at an expert human level, as well as to assess a players critical decision- making ability or skill-level. Build-order optimization is modeled as a multi-objective problem (MOP), and solutions are generated utilizing a multi-objective evolutionary algorithm (MOEA) that provides a set of good build-orders to a RTS planning agent. We de ne three research objectives: (1) Design, implement and validate a capability to determine the skill-level of a RTS player. (2) Design, implement and validate a strategic planning tool that produces near expert level build-orders which are an ordered sequence of actions a player can issue to achieve a goal, and (3) Integrate the strategic planning tool into our existing RTS agent framework and an RTS game engine. The skill-level metric we selected provides an original and needed method of evaluating a RTS players skill-level during game play. This metric is a high-level description of how quickly a player executes a strategy versus known players executing the same strategy. Our strategic planning tool combines a game simulator and an MOEA to produce a set of diverse and good build-orders for an RTS agent. Through the integration of case-base reasoning (CBR), planning goals are derived and expert build- orders are injected into a MOEA population. The MOEA then produces a diverse and approximate Pareto front that is integrated into our AI RTS agent framework. Thus, the planning tool provides an innovative online approach for strategic planning in RTS games. Experimentation via the Spring Engine Balanced Annihilation game reveals that the strategic planner is able to discover build-orders that are better than an expert scripted agent and thus achieve faster strategy execution times

    Manufacturing Value Modelling, Flexibility, and Sustainability: from theoretical definition to empirical validation

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    The aim of this PhD thesis is to investigate the relevance of flexibility and sustainability within the smart manufacturing environment and understand if they could be adopted as emerging competitive dimensions and help firms to take decisions and delivering value

    CBR and MBR techniques: review for an application in the emergencies domain

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    The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version

    Governance Through Participation: An Inquiry into the Social Relations of Community-Based Research

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    Community-based research (CBR) is consistently held up as a benchmark for socially just knowledge production. Calls for the intensification of and further institutionalization of CBR indicate the discursive value of community-engaged research, but its material effects are unclear. CBRs claims to egalitarian, emancipatory research relations and outcomes remain largely uninterrogated and the participative practices and collaborative relations under documented and theorized. This study of the social relations of CBR theorizes participatory research as a site of governance. Specifically, I inquire into how the social relations of CBR are governed through affect, participatory practices, colonial processes of subjectification, institutional arrangements, as well as resisted as counter governmental practices. I draw on poststructural, postcolonial and affect theories in dialogue with the critical reflections of twenty-nine academic, community-based professionals, and peer CBR collaborators to bring forth the complexity of governmental practices. I develop a methodology of Dialogic Theoretical Pluralism to produce five distinct strands of theoretical analyses, which trouble the discursive and material practices of collaborative research, while not foreclosing on its possibilities. I argue that conversants desires to do socially transformative research are unmet and reconfigure CBR as a site of scaffolding community collaborators toward social mobility. These desires activate participative practices of access to and appropriation of community knowledges and labour to produce a tertiary, low cost and precarious knowledge work force. Colonial subject-making practices of CBR, which are raced, gendered and classed, secure the benevolence and expertise of academe against community subjects Othered as lacking beneficiaries in need of capacity building. Institutional arrangements coordinate time, authorize who is a legitimate knower, and consign community collaborators and community benefit to the margins. These governmental practices are not total and institutionalized norms of CBR are resisted through unsettling affect, strategic subjectivities, dissent and distance, and revitalized commitments to social and epistemic transformation. Despite these transgressive practices, the reconfiguration of CBR as an individual intervention in a context of eroding support to social programming and social change warrants sustained attention to the ways in which participation colludes with the very neoliberal/colonial projects it aims to contest

    Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

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    [EN] This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings

    Improving the Relevance of Cyber Incident Notification for Mission Assurance

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    Military organizations have embedded Information and Communication Technology (ICT) into their core mission processes as a means to increase operational efficiency, improve decision making quality, and shorten the kill chain. This dependence can place the mission at risk when the loss, corruption, or degradation of the confidentiality, integrity, and/or availability of a critical information resource occurs. Since the accuracy, conciseness, and timeliness of the information used in decision making processes dramatically impacts the quality of command decisions, and hence, the operational mission outcome; the recognition, quantification, and documentation of critical mission-information resource dependencies is essential for the organization to gain a true appreciation of its operational risk. This research identifies existing decision support systems and evaluates their capabilities as a means for capturing, maintaining and communicating mission-to-information resource dependency information in a timely and relevant manner to assure mission operations. This thesis answers the following research question: Which decision support technology is the best candidate for use in a cyber incident notification system to overcome limitations identified in the existing United States Air Force cyber incident notification process
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