Searched for: subject%3A%22reinforcements%22
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Falcetelli, F. (author), Cristiani, D.L.M. (author), Yue, N. (author), Sbarufatti, Claudio (author), Sante, Raffaella Di (author), Zarouchas, D. (author)
Distributed Optical Fiber Sensors (DOFS) show several inherent benefits with respect to conventional strain-sensing technologies and represent a key technology for Structural Health Monitoring (SHM). Despite the solid motivation behind DOFS-based SHM systems, their implementation for real-time structural assessment is still unsatisfactory...
conference paper 2023
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Sarkar, A. (author), Al-Ars, Z. (author), Bertels, K.L.M. (author)
In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility function of a classical exploratory stochastic Knowledge Seeking Agent, KL-KSA, is generalized to distance measures from quantum information theory on density matrices. Quantum process...
conference paper 2023
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Staal, Jeroen (author), Smit, Edgar (author), Caglar, Baris (author), Michaud, Véronique (author)
Radical induced cationic frontal polymerisation (RICFP) is considered a promising low energy method for processing of fibre reinforced polymers (FRPs). Optimisation of the local heat balance between reinforcement, epoxy resin and the surrounding mould is required to pave the way for its adaptation to an industrial processing method for high...
journal article 2023
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Su, Jiahang (author), Li, Shuai (author), Wolff, Lennard (author), van Zwam, Wim (author), Niessen, W.J. (author), van der Lugt, Aad (author), van Walsum, T. (author)
Extracting the cerebral anterior vessel tree of patients with an intracranial large vessel occlusion (LVO) is relevant to investigate potential biomarkers that can contribute to treatment decision making. The purpose of our work is to develop a method that can achieve this from routinely acquired computed tomography angiography (CTA) and...
journal article 2023
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Du, Guodong (author), Zou, Yuan (author), Zhang, Xudong (author), Li, Z. (author), Liu, Qi (author)
The autonomous vehicle is widely applied in various ground operations, in which motion planning and tracking control are becoming the key technologies to achieve autonomous driving. In order to further improve the performance of motion planning and tracking control, an efficient hierarchical framework containing motion planning and tracking...
journal article 2023
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Rojas, D. (author), Quintana Gallo, P. (author), Pürgstaller, A. (author), Bianchi, S. (author), Ciurlanti, J. (author), Pampanin, S. (author), Bergmeister, K. (author)
This article presents a numerical study on the influence of the anchorage shear hysteresis on the seismic response of nonstructural components (NSC) connected to multi-storey reinforced concrete (RC) buildings, and of the anchorage itself. To cover a variety of different types of shear hysteresis shapes, this contribution considered the...
journal article 2023
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Tang, Shi Yuan (author), Irissappane, Athirai A. (author), Oliehoek, F.A. (author), Zhang, Jie (author)
Typically, a Reinforcement Learning (RL) algorithm focuses in learning a single deployable policy as the end product. Depending on the initialization methods and seed randomization, learning a single policy could possibly leads to convergence to different local optima across different runs, especially when the algorithm is sensitive to hyper...
journal article 2023
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Lee, Minu (author), Mata-Falcón, Jaime (author), Popescu, M.A. (author), Kaufmann, Walter (author)
Thin-walled textile-reinforced concrete beams have recently emerged as a promising approach for material-efficient design. However, the increased complexity of the formwork is a major challenge in implementing such elements for broader use in the construction industry. This study presents a novel type of stay-in-place flexible formworks with...
journal article 2023
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Shengren, H. (author), Vergara Barrios, P.P. (author), Salazar Duque, Edgar Mauricio (author), Palensky, P. (author)
The massive integration of renewable-based distributed energy resources (DERs) inherently increases the energy system’s complexity, especially when it comes to defining its operational schedule. Deep reinforcement learning (DRL) algorithms arise as a promising solution due to their data-driven and model-free features. However, current DRL...
journal article 2023
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Song, Q. (author), Tan, Rui (author), Wang, J. (author)
Driver Behavior Modeling (DBM) aims to predict and model human driving behaviors, which is typically incorporated into the Advanced Driver Assistance System to enhance transportation safety and improve driving experience. Inverse reinforcement learning (IRL) is a prevailing DBM technique with the goal of modeling the driving policy by...
conference paper 2023
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Zheng, Jingjing (author), Li, Kai (author), Mhaisen, N. (author), Ni, Wei (author), Tovar, Eduardo (author), Guizani, Mohsen (author)
Federated learning (FL) is increasingly considered to circumvent the disclosure of private data in mobile edge computing (MEC) systems. Training with large data can enhance FL learning accuracy, which is associated with non-negligible energy use. Scheduled edge devices with small data save energy but decrease FL learning accuracy due to a...
conference paper 2023
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Slegers, Ron (author)
An experimental research into the use of basalt as reinforcement in concrete to reduce the ECI value of a concrete quay wall apron. In this research experiments with basalt minibars and basalt reinforced polymer rebars are performed to compare directly to steel fibres and steel rebars. With the test results 4 designs are produced resulting in...
master thesis 2022
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Neustroev, G. (author)
Sequential decision-making under uncertainty is an important branch of artificial intelligence research with a plethora of real-life applications. In this thesis, we generalize two fundamental properties of the decision-making process. First, we show that the theory on planning methods for finite spaces can be extended to infinite but countable...
doctoral thesis 2022
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Zhang, S. (author)
Alkali-activated Materials (AAMs), including those classified as geopolymer, are obtained through the reaction between a solid precursor and an alkaline solution. Compared with ordinary Portland cement (OPC) binders, these materials maintain comparable mechanical properties but have the advantage of reducing greenhouse gas emissions and...
doctoral thesis 2022
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Li, Zhuoheng (author)
Programmers usually write test cases to test onboard software. However, this procedure is time-consuming and needs sufficient prior knowledge. As a result, small satellite developers may not be able to test the software thoroughly. <br/> <br/>A promising direction to solve this problem is reinforcement learning (RL) based testing. It searches...
master thesis 2022
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Voogd, Kevin (author)
Autonomous driving is attracting growing attention because of the potential advantages it poses on safety, leisure, energy efficiency, reduced emissions, and traffic reduction. Current research is focusing on areas related to artificial intelligence to solve complex planning and decision-making tasks, object detection, or simultaneous...
master thesis 2022
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Lambregts, Dorien (author)
The production and consumption of electricity need to be balanced at all times. Due to the ever-growing shift towards renewable energy generation, this poses an increasingly difficult challenge. Currently, supply is regulated to maintain balance. However, there is potential to improve reliability and save costs by shifting the balancing to the...
master thesis 2022
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Seres, Peter (author)
With the recent increase in the complexity of aerospace systems and autonomous operations, there is a need for an increased level of adaptability and model-free controller synthesis. Such operations require the controller to maintain safety and performance without human intervention in non-static environments with partial observability and...
master thesis 2022
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van Rietbergen, Tomas (author)
Reliable indoor navigation in the presence of dynamic obstacles is an essential capability for mobile robot deployment. Previous work on robot navigation focuses on expanding the network structure and hardware setup leading to more complex and costly systems. The accompanying physical demonstrations are often limited to slow-moving agents and...
master thesis 2022
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Casals Sadlier, Juliette (author)
The implementation of a model-free, off-policy, actor-critic deep reinforcement learning algorithm consistent of two separate agents to a six-degree-of freedom spacecraft docking maneuver to develop a control policy is carried out in the research presented in this article. Reinforcement learning has the ability to learn without instruction, this...
master thesis 2022
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