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Verhagen, Alexandra (author)Accurate capacity planning is essential to ensure uninterrupted services and network stability through peak hours for the transport core network of KPN. This involves a trade-off between minimizing the risks of capacity shortages and costs of capacity expansions. High network loads are occurring more frequently and their magnitude is increasing....master thesis 2024
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Spitzbarth, B. (author)Nature has inspired countless researchers in their quest to understand the phenomena we observe and utilise their findings to develop new technologies. This becomes especially apparent in systems chemistry, which heavily draws inspiration from natural systems in its pursuit for the understanding and development of chemical reaction networks ...doctoral thesis 2024
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Hettema, Bart (author)Neuromorphic computing can be used to efficiently implement spiking neural networks.<br/>Such spiking neural networks can be used in edge AI applications, where low power consumption is paramount.<br/>The use of analog components allows for extremely low power implementations.<br/>This thesis contributes the designs of an analog spike generator,...master thesis 2024
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Kiste, Amund (author)Solving Partial Differential Equations (PDEs) in engineering such as Navier-Stokes is incredibly computationally expensive and complex. Without analytical solutions, numerical solutions can take ages to simulate at great expense. In order to reduce this cost, neural networks may be used to compute approximations of the solution for use during...bachelor thesis 2024
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Taklimi, Sam (author)The objective of this project is to train a model that transforms a tree with its foliage into only its branch structure. This is achieved by employing machine-learning techniques, specifically Generative Adverserial Networks (GANs). By utilizing the proposed method, a predictive model is built that automatically minimizes its own error function...bachelor thesis 2024
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Lacombe, Pablo (author)This paper presents a comprehensive exploration of a novel method combining Principal Component Analysis (PCA) and Neural Networks (NN) to efficiently solve Partial Differential Equations (PDEs), a fundamental challenge in modeling a wide range of real-world phenomena. Our research extends the work of Bhattacharya et al. by focusing on PCA for...bachelor thesis 2024
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Hueber, Paul (author)Designing processors for implantable closed-loop neuromodulation systems presents a formidable challenge owing to the constrained operational environment, which requires low latency and high energy efficacy. Previous benchmarks have provided limited insights into power consumption and latency. However, this study introduces algorithmic metrics...master thesis 2024
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Hashemi, L. (author)The demand for sustainable and clean energy sources has become increasingly vital in addressing the challenges of climate change and energy security. Hydrogen, with its high energy density and potential for carbon-free energy conversion, has emerged as a promising candidate for future energy systems. Efficient storage and retrieval of hydrogen...doctoral thesis 2024
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Qin, Xusen (author)Neural networks have made significant progress in domains like image recognition and natural language processing. However, they encounter the challenge of catastrophic forgetting in continual learning tasks, where they sequentially learn from distinct datasets. Learning a new task can lead to forgetting important information from previous tasks,...master thesis 2024
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Papenhuijzen, Daan (author)The importance of climate change is getting increasingly more attention from all stakeholders in urban development. This results in the energy network operator being increasingly involved in the partnerships needed to realize new urban area development projects. Current projects have been experiencing delays due to the electricity grid not being...master thesis 2024
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Sebus, Siert (author)The Deep Neural Network (DNN) has become a widely popular machine learning architecture thanks to its ability to learn complex behaviors from data. Standard learning strategies for DNNs however rely on the availability of large, labeled datasets. Self-Supervised Learning (SSL) is a style of learning that allows models to also use unlabeled data...master thesis 2024
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Achterberg, M.A. (author)The COVID-19 pandemic has had a disruptive impact on healthcare systems and everyday life of the majority of the people around the globe. Despite many years of research on network epidemiology, many key aspects of disease transmission and in particular the response of people to the spread of a disease, remain poorly understood. On the basis of...doctoral thesis 2024
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Fu, Peng (author)Keyword spotting (KWS) is an essential component of voice recognition services on smart devices. Its always-on characteristic requires high accuracy and real-time response. Also, low power consumption is another key demand for KWS devices. In previous research, neural networks have become popular for KWS tasks for their accuracy compared to...master thesis 2024
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Versteeg, Rogier (author), Pool, D.M. (author), Mulder, Max (author)This article discusses a long short-term memory (LSTM) recurrent neural network that uses raw time-domain data obtained in compensatory tracking tasks as input features for classifying (the adaptation of) human manual control with single- and double-integrator controlled element dynamics. Data from two different experiments were used to train...journal article 2024
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Schweidtmann, A.M. (author), Zhang, Dongda (author), von Stosch, Moritz (author)The term hybrid modeling refers to the combination of parametric models (typically derived from knowledge about the system) and nonparametric models (typically deduced from data). Despite more than 20 years of research, over 150 scientific publications (Agharafeie et al., 2023), and some recent industrial applications on this topic, the...review 2024
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Murti, Fahri Wisnu (author), Ali, Samad (author), Iosifidis, G. (author), Latva-aho, Matti (author)Virtualized Radio Access Networks (vRANs) are fully configurable and can be implemented at a low cost over commodity platforms to enable network management flexibility. In this paper, a novel vRAN reconfiguration problem is formulated to jointly reconfigure the functional splits of the base stations (BSs), locations of the virtualized central...journal article 2024
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Wang, Ran (author), Wang, Tongbing (author), Lee, Chia-Jung (author), Liu, Zhengxuan (author), Zhang, G. (author)To explore factors that influence the likelihood of committing fraud in the construction industry, this study concentrated on senior executives and tested whether some characteristics at the individual and firm levels have impacts on the likelihood of fraud committed by top management. Based on social network theory, this study first proposes...journal article 2024
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Ricci, Federica (author), Yang, M. (author), Reniers, G.L.L.M.E. (author), Cozzani, Valerio (author)Emergency response is a procedural safety barrier of paramount importance for the mitigation of fire scenarios and the prevention of escalation. However, in Natech scenarios, emergency response may be affected by the natural event impacting the site. Indeed, when contrasting Natech accidents, emergency responders have to face both the natural...journal article 2024
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Ali Mubarak, Faisal (author), Mascolo, V. (author), Hussain, Faizan (author), Rietveld, Gert (author)Closed-form solutions are presented for calculating the reflection coefficient with corresponding uncertainty of metrology-grade 3.5 mm air-dielectric coaxial transmission lines for use as reference standards in S-parameter measurements up to 33 GHz. The closed-form solutions allow the calculation of the sensitivity coefficients required for...journal article 2024
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Li, Qiongxiu (author), Gundersen, Jaron Skovsted (author), Lopuhaa-Zwakenberg, Milan (author), Heusdens, R. (author)Privacy-preserving distributed average consensus has received significant attention recently due to its wide applicability. Based on the achieved performances, existing approaches can be broadly classified into perfect accuracy-prioritized approaches such as secure multiparty computation (SMPC), and worst-case privacy-prioritized approaches...journal article 2024