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Trommelen, Joost (author)Sea level variations and storm surges are expected to increase as a result of climate change. 570 cities and some 800 million people are by 2050 estimated to be exposed to these phenomena when emissions do not decrease (UCCRN, 2018). It is, however, deeply uncertain if and to what extent emissions will decrease. Additionally, the effects of...master thesis 2022
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van Tol, Thomas (author)The COVID-19 pandemic has changed travel behaviour and mobility in the Netherlands. It is questioned if the mobility system is subject to long-lasting change in the near and distant future. This study aims to observe the development of mobility impacts over time with a quantitative approach.<br/><br/>Current traditional transport models have...master thesis 2022
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Zhou, C. (author)Climate change is incompatible with the assumption of stationarity. This has lead to a sharp increase in the detection and study of nonstationarity in hydro-meteorological processes. Most hydro-meteorological processes are still analyzed by studying time series of observations. From the perspective of statistical characteristics, a stationary...doctoral thesis 2022
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Toonen, Sanny (author)Building upon a conceptual framework of elements that play a role in the management of uncertainties, an empirical study was performed to learn about the uncertainties in the energy transition. For this, interviews were held and an expert panel was organized. <br/><br/>It was found that uncertainty is an unavoidable element of project management...master thesis 2022
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Meggouh, Mamoun (author)Construction projects are filled with uncertainty. Such projects are becoming more complex: Many different interrelated aspects that are subject to change play a role in the delivery of construction work. This makes it interesting to know what exactly is uncertain in these projects, and what can be done to manage uncertainty. The aim of this...master thesis 2022
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Hermans, Bruno (author)Illicit supply chain networks are not well mapped. Regulators do not know how goods flow from supplier to retailer. There is uncertainty about whom is involved, where goods originate from, and what quantities are being shipped. Simulation models are effective tools to find measures against the distribution of illicit goods such as personal...master thesis 2022
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Oren, Yaniv (author)Deep, model based reinforcement learning has shown state of the art, human-exceeding performance in many challenging domains. <br/>Low sample efficiency and limited exploration remain however as leading obstacles in the field. <br/>In this work, we incorporate epistemic uncertainty into planning for better exploration.<br/>We develop a low-cost...master thesis 2022
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Bonavita, Daniele (author)From 2018 to 2020, the city of Breda (NL) faced drought, with significant economic losses and water scarcity problems. The water board within which the city is located began to consider new possible water management practices, due to the unsustainability of the current ones. This study aims to investigate how a change of the current paradigm can...master thesis 2022
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Eil, Willem-Jan (author)There has been a growing interest in improving the operating efficiency of warehouses, which is one of the critical facilities used in the logistics sector. This thesis examines the impact of order characteristics on the performance of different configurations of the outbound logistics of a 3PL warehouse. A contingency approach combined with a...master thesis 2022
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Wang, X. (author), Alonso-Mora, J. (author), Wang, M. (author)Road traffic safety has attracted increasing research attention, in particular in the current transition from human-driven vehicles to autonomous vehicles. Surrogate measures of safety are widely used to assess traffic safety but they typically ignore motion uncertainties and are inflexible in dealing with two-dimensional motion. Meanwhile,...journal article 2022
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Carli, Raffaele (author), Cavone, Graziana (author), Pippia, T.M. (author), De Schutter, B.H.K. (author), Dotoli, Mariagrazia (author)This paper focuses on the control of microgrids where both gas and electricity are provided to the final customer, i.e., multi-carrier microgrids. Hence, these microgrids include thermal and electrical loads, renewable energy sources, energy storage systems, heat pumps, and combined heat and power units. The parameters characterizing the...journal article 2022
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Riillo, Cesare Antonio F. (author), Allamano-Kessler, Renaud (author), Asnafi, Nader (author), Fomin, Vladislav V. (author), van de Kaa, G. (author)Standards may be arrived at through various coordination mechanisms, including cooperation, coopetition, or competition. This article explores how technological uncertainty affects the coordination mechanism for standardization. The article is based on the Community Innovation Survey, a sizeable firm-level survey representative of the...journal article 2022
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Wilde, N. (author), Alonso-Mora, J. (author)In this paper we study the multi-robot task assignment problem with tasks that appear online and need to be serviced within a fixed time window in an uncertain environment. For example, when deployed in dynamic, human-centered environments, the team of robots may not have perfect information about the environment. Parts of the environment may...conference paper 2022
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Boskos, D. (author), Cortes, Jorge (author), Martinez Sandez, S. (author)This paper introduces a spectral parameterization of ambiguity sets to hedge against distributional uncertainty in stochastic optimization problems. We build an ambiguity set of probability densities around a histogram estimator, which is constructed by independent samples from the unknown distribution. The densities in the ambiguity set are...conference paper 2022
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Chaouach, L. (author), Boskos, D. (author), Oomen, T.A.E. (author)Ambiguity sets of probability distributions are a prominent tool to hedge against distributional uncertainty in stochastic optimization. The aim of this paper is to build tight Wasserstein ambiguity sets for data-driven optimization problems. The method exploits independence between the distribution components to introduce structure in the...conference paper 2022
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Chatterjee, Sarthak (author), Gonçalves Melo Pequito, S.D. (author)Discrete-time fractional-order dynamical systems (DT-FODS) have found innumerable applications in the context of modeling spatiotemporal behaviors associated with long-term memory. Applications include neurophysiological signals such as electroencephalogram (EEG) and electrocorticogram (ECoG). Although learning the spatiotemporal parameters of...conference paper 2022
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Lodel, M. (author), Ferreira de Brito, B.F. (author), Serra Gomez, A. (author), Ferranti, L. (author), Babuska, R. (author), Alonso-Mora, J. (author)Search missions require motion planning and navigation methods for information gathering that continuously replan based on new observations of the robot's surroundings. Current methods for information gathering, such as Monte Carlo Tree Search, are capable of reasoning over long horizons, but they are computationally expensive. An alternative...conference paper 2022
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Ghanipoor, Farhad Ghanipoor (author), Murguia, Carlos (author), Mohajerin Esfahani, P. (author), van de Wouw, Nathan (author)In this paper, we present a methodology for actuator and sensor fault estimation in nonlinear systems. The method consists of augmenting the system dynamics with an approximated ultra-local model (a finite chain of integrators) for the fault vector and constructing a Nonlinear Unknown Input Observer (NUIO) for the augmented dynamics. Then, fault...conference paper 2022
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Li, Peng (author), Liu, Di (author), Xia, Xin (author), Baldi, S. (author)The operation of Unmanned Aerial Vehicles (UAVs) is often subject to state-dependent alterations and unstructured uncertainty factors, such as unmodelled dynamics, environmental weather disturbances, aerodynamics gradients, or changes in inertia and mass due to payloads. While a large number of autopilot solutions have been proposed to operate...conference paper 2022
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Mody, Prerak (author), Chaves-de-Plaza, Nicolas F. (author), Hildebrandt, K.A. (author), van Egmond, R. (author), de Ridder, H. (author), Staring, Marius (author)Deep learning models for organ contouring in radiotherapy are poised for clinical usage, but currently, there exist few tools for automated quality assessment (QA) of the predicted contours. Bayesian models and their associated uncertainty, can potentially automate the process of detecting inaccurate predictions. We investigate two Bayesian...journal article 2022