Searched for: subject%3A%22inference%22
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Bisbal Regidor, Àlex (author)
Within the context of the new wave of eVTOL aircraft development, Cyclotech GmbH has been working on the development of cyclorotors, a type of propeller consisting of rotating blades along a common longitudinal axis, where the pitch angle of the blades is actively controlled through what is known as a pitch curve. This thesis proposes a...
master thesis 2024
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Timmer, Sebastiaan (author)
<div>As Neuroscience progresses, there is an increasing amount of research that endorses predictions and reducing of prediction errors as one of the main functions of the brain. active inference is a brain-inspired, mathematical framework that successfully implements this idea both in simulations as well as in robotics. The predictive nature of...
master thesis 2024
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Dawe, Alon (author)
master thesis 2024
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Bekooy, Mark (author)
Type annotations in Python are an integral part of static analysis. They can be used for code documentation, error detection and the development of cleaner architectures. By enhancing code quality, they contribute to the robustness, maintainability and comprehensibility of codebases. Tools like static type checkers use type annotations to detect...
master thesis 2024
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Aalders, Jaime (author)
Addressing the increasingly urgent need for sustainable aviation solutions, this study explores operational innovations as a quicker and more scalable addition to novel zero-emission propulsion systems. Through the use of regression-based causal inference methods, this study aims to understand the relationship between flight fuelburn...
master thesis 2024
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Molhoek, Jord (author)
Many real-world problems fall in the category of sequential decision-making under uncertainty; Markov Decision Processes (MDPs) are a common method for modeling such problems. To solve an MDP, one could start from scratch or one could already have an idea of what good policies look like. Furthermore, there could be uncertainty in this idea. In...
master thesis 2024
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Pezzato, C. (author)
In an ever-evolving society, the demand for autonomous robots equipped with human-level capabilities is becoming increasingly imperative. Various factors, such as an aging population and a shortage of labor for repetitive and physically demanding tasks, have underscored the need for capable autonomous robots to assist us in our daily activities....
doctoral thesis 2024
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Dash, T.K. (author), Driessen, J.N. (author), Krasnov, O.A. (author), Yarovoy, Alexander (author)
The challenge of reconstructing the Doppler spectrum of a precipitation-like event observed by a fast-scanning weather radar is addressed. A novel method is proposed where the echo sequence in time is assumed to be a complex Gaussian process with a known covariance structure. It is a two-step approach where the first step is the estimation of...
conference paper 2024
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Moriaux, Olivier (author), Zamponi, R. (author), Schram, Christophe (author)
The empirical calibration of remote microphone probes (RMP), used to acquire wall-pressure fluctuations, can introduce spurious resonance into the sensor transfer function due to the difference in the pressure field inside the calibrator geometry over multiple calibration steps. Such spurious resonance subsequently propagates into the...
journal article 2024
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Li, G. (author), Li, Zirui (author), Knoop, V.L. (author), van Lint, J.W.C. (author)
Predicting the trajectories of road agents is fundamental for self-driving cars. Trajectory prediction contains many sources of uncertainty in data and modelling. A thorough understanding of this uncertainty is crucial in a safety-critical task like auto-piloting a vehicle. In practice, it is necessary to distinguish between the uncertainty...
journal article 2024
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Dziarnowska, Weronika (author)
Researchers have been interested in studying the connection between emotion and memory for decades but much remains unknown due to the elusive nature of the human brain. Furthering our understanding of the phenomenon is crucial for improving the treatment of neurological disorders associated with emotion dysregulation, as well as for enhancing...
master thesis 2023
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Pellegrino, G. (author)
doctoral thesis 2023
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Edelman, Jory (author)
Magnetic resonance electrical properties tomography is a type of quantitative magnetic resonance imaging that aims to reconstruct the conductivity and permittivity of biological tissue. These electrical properties of the tissue can be used to compute the specific absorption rate, to differentiate tumours from healthy tissue and for hyperthermia...
master thesis 2023
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Moreno León, C. (author)
Radar-tracking of low-observable targets such as drones suffers from low detection performance. In these type of applications, it is desirable to avoid data thresholding in order to preserve the weak target signal in the raw sensor data. This thesis considers the Multiple Object Tracking (MOT) problem in the context of radar Track-before-Detect ...
doctoral thesis 2023
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ZHANG, Frankie (author)
Task and Motion Planning (TAMP) has progressed significantly in solving intricate manipulation tasks in recent years, but the robust execution of these plans remains less touched. Particularly, generalizing to diverse geometric scenarios is still challenging during execution. In this work, we propose a reactive TAMP method to deal with...
master thesis 2023
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BHIDE, NEERAJA (author)
Due to the increase in traffic, road congestion has gone up. Vehicle platooning is a possible way to increase the capacity of a given road, by decreasing the distance between the vehicles in the platoon. At the moment, the control of vehicle platoons is commonly done using PID controllers. The advantage of this is that it requires little...
master thesis 2023
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feng, lang (author)
Type inference plays a pivotal role in modern software development as it aids in understanding code, detecting errors, and facilitating code completion. Two main approaches, static analysis, and machine learning, contribute to this process. Each approach has its own benefits and limitations. This thesis investigates the potential of combining...
master thesis 2023
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Peker, Uri (author)
Probabilistic numerics methods are a novel approach to quantifying the approximation errors in numerical computations as probabilistic uncertainties. A recent method that was developed is the Bayesian Finite Element Method, which aims to determine the discretization errors along a coarse mesh probabilistically. This work analyzes the use of...
master thesis 2023
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Gardos Reid, Reuben (author)
Over 700 trains in the Netherlands are used daily for passenger transportation. Train operations involve tasks like parking, recombination, cleaning, and maintenance, which take place in shunting yards. The train unit shunting problem (TUSP) is a complex planning problem made more difficult by uncertainties such as delays. Most existing...
master thesis 2023
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Borges Carioca Moreno Rodrigues, Inês (author)
Tacrolimus is an immunosuppressive drug given to kidney transplant patients. A low concentration of this drug can lead to kidney rejection, but to our knowledge no research has been done to causally connect the two. This paper investigates the causal effect of tacrolimus concentration on kidney rejection occurrence using predictive analysis and...
master thesis 2023
Searched for: subject%3A%22inference%22
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