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Lim, Dayoung (author)
Accurate topic classification is crucial in the scientific community when it comes to finding relevant journals. However, the efficiency and accuracy of topic classification of publications do not seem to be at its best performance, especially with the fast-paced rise in the quantity of research papers. Our research aims to address this problem...
bachelor thesis 2024
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Makrodimitris, S. (author), Pronk, I.B. (author), Abdelaal, T.R.M. (author), Reinders, M.J.T. (author)
Multi-omic analyses are necessary to understand the complex biological processes taking place at the tissue and cell level, but also to make reliable predictions about, for example, disease outcome. Several linear methods exist that create a joint embedding using paired information per sample, but recently there has been a rise in the...
review 2024
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Zimmerling, J.T. (author), Druskin, Vladimir (author), Guddati, Murthy (author), Cherkaev, Elena (author), Remis, R.F. (author)
We present a reduced-order model (ROM) methodology for inverse scattering problems in which the ROMs are data-driven, i.e. they are constructed directly from data gathered by sensors. Moreover, the entries of the ROM contain localised information about the coefficients of the wave equation. We solve the inverse problem by embedding the ROM in...
journal article 2024
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Cavalcante, Túlio de M. (author), Castiel Reis de Souza, A. (author), Hajibeygi, H. (author), Carvalho, Darlan K.E. (author), Lyra, Paulo R.M. (author)
The modeling of fluid flow in heterogeneous, anisotropic and fractured porous media is relevant in many applications, including hydrocarbon and groundwater extraction, dispersion of contaminants, hydrogen or carbon dioxide (CO<sub>2</sub>) storage. Thus, accurate and scalable simulation of fluid flow through these formations continues to be a...
journal article 2024
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van Leeuwen, Sander (author)
Language is an intuitive and effective way for humans to communicate. Large Language Models (LLMs) can interpret and respond well to language. However, their use in deep reinforcement learning is limited as they are sample inefficient. State-of-the-art deep reinforcement learning algorithms are more sample efficient but cannot understand...
master thesis 2023
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Christopoulos, Giorgos (author)
The rapid growth of Floating Offshore Wind (FOW) has spurred intensive research across various aspects of the floating system. A standard practice in mooring system design within the industry is that anchors remain fixed on the seabed. In contrast, plate-type anchors exhibit mobility under loading, a crucial factor considering the thousands of...
master thesis 2023
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Peppelman, Christian (author)
Non-invasive head-worn sensors are an upcoming field of interest. Most commercial sensors and sensors presented in research papers are limited in their capabilities and require frequent user interaction. In this Thesis, we research the possibilities of overcoming some of these limitations and extending the capabilities of these sensors.
master thesis 2023
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VASILEIOU, ANTONIOS (author)
Graph data is widely used in various applications, driving the rapid development of graph-based machine learning methods. However, traditional algorithms tailored for graphs have constraints in capturing intricate node relationships and higher-order patterns. Recent insights from prior research have shed light on comparing different graph neural...
master thesis 2023
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de Gruijl, David (author)
Much like wearable devices today, ingestible devices have emerged as a promising platform for continuous health monitoring, and potentially even intervention. Recent research has demonstrated the feasibility of ingestible devices with a retention mechanism, enabling them to remain in the stomach for weeks. Equipping these devices with sensors...
master thesis 2023
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Lut, Jasper-Jan (author)
Drones that perform complex autonomous movements require a perfect estimate of their current position. However, internal measurement unit (IMU) errors introduce drift in this estimate, leading to significant discrepancies between the predicted and actual location. Various solutions have been proposed to calibrate the IMU, including methods...
master thesis 2023
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Park, Jeongwoo (author)
Moral values influence humans in decision-making. Pluralist moral philosophers argue that human morality can be represented by a finite number of moral values, respecting the differences in moral views. Recent advancements in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms of society....
master thesis 2023
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de Beer, Arne (author)
This paper presents a study focused on developing an efficient signal processing pipeline and identifying suitable machine learning models for real-time gesture recognition using a testbed consisting of an Arduino Nano 33 BLE and three OPT101 photodiodes. Our research aims to address the challenges of limited computational power whilst...
bachelor thesis 2023
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de Winkel, J. (author)
The ecological impact of today’s battery-powered Internet of Things (IoT) is troubling. Technology advancements that reduce the reliance on batteries could blunt the environmental impact of the projected billions of IoT devices. With the emergence of low-cost, small, and high-performance microcontrollers, along with more efficient micro-energy...
doctoral thesis 2023
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Kooyman van Guldener, Gert-Jan (author)
As digitization moves on, more data is produced and the value of this data increases. However, data is still transferred manually between different digital systems. Reason to manually transfer information is lacking interoperability between these systems. Huge costs are related to this lacking interoperability as they cause high data losses....
master thesis 2023
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Kortbeek, V. (author)
The Internet of Things (IoT) is taking the world by storm, from smart lights to smart plant monitoring. This revolution is not only present in consumers’ homes, but companies are also looking for more and more ways to monitor every aspect of their production process. This transition to ubiquitous monitoring is made possible by extremely low...
doctoral thesis 2023
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Cuţitei, Cristian (author)
Analyzing food consumption patterns can provide valuable insights into the development of obesity and eating disorders. The detection and quantification of chewing strokes are essential to facilitate this analysis. One approach to food intake analysis involves evaluating chewing sounds generated during the eating process. These sounds were...
bachelor thesis 2023
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Pronk, Paco (author)
This study introduces a novel system that leverages three photodiodes and ambient light to identify air-written characters on a resource-constrained device. Through experimentation, suitable methods of data preprocessing, machine learning and model compression were selected to recognize the first 10 characters of the Latin alphabet. The final...
bachelor thesis 2023
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Tao, Lucy (author)
Vascularisation is a critical factor in large-scale tissue engineering, as it supports the survival of cells in large tissue constructs. In native tissue, a hierarchical vascular network is present where larger vessels transport nutrients and oxygen throughout the body, and smaller capillaries facilitate blood-tissue exchange. In large-scale...
master thesis 2023
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Agrawal, Isha (author)
Metagenomic Next-Generation Sequencing (mNGS) presents a promising avenue to generate massive volume of sequence reads in a short period of time. This has opened opportunities for disease diagnosis based on individual variations and mutations by considering the microbiome profile of each patient. However, the effective use of this data requires...
master thesis 2023
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Chronas, Konstantinos (author)
Matching schemas is a fundamental task in data integration and semantic web applications. However, generating labeled data for schema matching tasks is challenging, requiring an efficient and effective approach. This thesis addresses this challenge by investigating schema matching techniques and crowdsourcing solutions. We developed a prototype...
master thesis 2023
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