Searched for: subject%3A%22ensemble%22
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Stevense, Wesley (author)
We perform a numerical optimisation of the hardware parameters of an atomic-ensemble-based single repeater setup. The setup operates on a real-life fiber network connecting the cities Delft and Eindhoven. Besides this network, the setup encompasses photon pair sources, quantum memories, single photon detectors, and 50:50 beam splitters. The...
master thesis 2024
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Kim, Sungjin (author)
Although automated segmentation of 3D medical images produce near-ideal results, they encounter limitations and occasional errors, necessitating manual intervention for error correction. Recent studies introduce an active learning pipeline as an efficient solution for this, requiring user corrections only on some of the most uncertain parts of...
bachelor thesis 2023
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du Buf, Koen (author)
Integrated circuits are vital in the modern world. Testing these circuits is often a months long process involving measurements at multiple times during long stress tests. In this work, final measurements from such tests are predicted based on early measurements, potentially reducing the time needed for such tests and giving preliminary results....
master thesis 2023
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van Wieringen, Lisanne (author)
A combinatorial proof of Wigner’s Semicircle Law for the Gaussian Unitary Ensemble (GUE) is presented in this report. The distribution of eigenvalues of different samples of general Wigner matrices is shown to converge to the semicircle distribution, with the aid of histograms created in Python. The type of convergence that is shown is that of...
bachelor thesis 2023
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de Leeuw, Wouter (author)
VPR describes a task where an agent (e.g., a robot) attempts to recognize its current location by comparing the incoming visual data from its sensor(s) (query images), usually a camera, to geotagged reference images. Both query and reference images are described using a feature extractor, and the query descriptor is matched to its closest...
master thesis 2023
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Freyer, Caroline (author)
Outlier detection in time series has important applications in a wide variety of fields, such as patient health, weather forecasting, and cyber security. Unfortunately, outlier detection in time series data poses many challenges, making it difficult to establish an accurate and efficient detection method. In this thesis, we propose the Random...
master thesis 2022
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Castelijn, Moos (author)
Groundwater is an essential ingredient in farming, knowledge about how this is expected to change over time can help farmers improve yields and save water. Predictions about the groundwater level can be made using a mathematical model. This model takes into account the precipitation and evaporation, the flux towards a deeper aquifer and flux to...
bachelor thesis 2022
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O'Hara, Kian (author)
In light of our depleting fossil fuel reserves and the relatively `cheap' extraction of oil and in spite of the highly nonlinear nature of reservoirs, waterflooding has become big business. In recent times, the use of numerical reservoir simulation has not only become possible but has increasingly been used in the petroleum industry in the...
master thesis 2021
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Smit, Jordi (author)
Offline reinforcement learning, or learning from a fixed data set, is an attractive alternative to online reinforcement learning. Offline reinforcement learning promises to address the cost and safety implications of taking numerous random or bad actions online, which is a crucial aspect of traditional reinforcement learning that makes it...
master thesis 2021
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Mol, Maaike (author)
The need for accurate estimation of hydrodynamic and water quality model variables arises from the UNITED project, which aims to create high-resolutional forecasting systems for monitoring the cultivation of seaweed and flat oysters and operating of the Belgian pilot of UNITED in the coastal area of the North Sea. Accurate observations of...
master thesis 2021
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Bilstra, Cas (author)
Machine learning models are increasing in popularity and are nowadays used in a wide range of critical applications in fields such as Automotive, Aviation and Medical. Among machine learning models, tree ensemble models are a popular choice due to their competitive performance and high degree of explainability. Like most machine learning models...
master thesis 2021
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van der Horst, Tim (author)
Software testing is an integral part of the development of embedded systems. Among other reasons, tests are frequently used to ensure that a system meets all the specifications, which is especially important when designing systems for the medical industry. Software changes that have a detrimental impact on a real-time system's performance can...
master thesis 2021
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Jirovská, Hana (author)
There has been a lot of research focused on the next generation of the internet, the so-called quantum networks. This analysis has been so far limited to mostly symmetrical architectures, but any near-term realisations of quantum networks using existing fibre topologies will contain asymmetry. In this thesis, we investigate how midpoint...
bachelor thesis 2021
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Bons, Wouther (author)
Currently, trained machine learning models are readily available, but their training data might not be (for example due to privacy reasons). This thesis investigates how pre-trained models can be combined for performance on all their source domains, without access to data. This problem is formulated as a Multiple-Source Domain Adaptation (MSA)...
master thesis 2021
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Mulder, Lotte (author)
Early detection of Alzheimer's Disease (AD), i.e. before symptom onset, would provide the opportunity for development and testing of interventions at earlier stages, when the disease process may still be altered or interrupted. Computer algorithms combining machine learning with non-invasive imaging and other biomarkers for AD have been...
master thesis 2021
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Borst, Nick (author)
Estimating the RUL (Remaining Useful Life) of machinery is a useful tool for maintenance and performance operations. This results in lower costs, improved safety and operational improvements.<br/>This paper proposes two adaptations to the CNN-LSTM network provided by Li et al. \cite{Li2019APrediction}, as well as exploring reproducibility,...
master thesis 2020
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Colaco, Grevil (author)
Nitrogen oxides (NOx) are significant sources of air pollution. Nitrogen oxides like Nitric oxide (NO) and Nitrogen dioxide (NO2) are mainly responsible for the acid rain and smog. Nitrous oxide (N2O), also known as the laughing gas, is the major greenhouse gas that is responsible for the ozone layer's damage in the...
master thesis 2020
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Mesfum, Johannes (author)
The flight planning process is an extensive and long process to direct and maintain a high level of operations within the airspace. As air traffic demand grows year after year, it's worthwhile to optimise the European air traffic system further. One way of optimising the system, is by creating optimal flight schedules that solve for demand...
master thesis 2020
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Rabbie, Julian (author)
The quantum internet will allow for communication via qubits, enabling for improved clock synchronization, blind quantum computing and quantum key distribution. Key components of such a quantum network are quantum repeaters, which help to overcome the exponential loss of photons in optical fibers. In this thesis we focus on one type of quantum...
master thesis 2020
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Bartczak, Konrad (author)
Displacement control is of utmost importance in deep excavation design and is usually based on numerical modelling, e.g. Finite Element Method (FEM). Numerical methods tend to be more conservative when analysing soil behaviour during deep excavation, whereas for practical and economic reasons this is not favoured. The inverse analysis allows for...
master thesis 2020
Searched for: subject%3A%22ensemble%22
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