Searched for: contributor%3A%22Zuniga%2C+Marco+%28graduation+committee%29%22
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Goel, Saransh (author)
This research investigates the impact of multipath signals in UWB communications and explores their potential to improve localization accuracy of tags using the additional information captured in the Channel Impulse Response (CIR). While traditional localization typically relies on multiple anchors, this study focuses on using a single anchor...
master thesis 2024
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van Diepen, Chiel (author)
Indoor localisation is a well-researched topic and it is a challenge to improve the accuracy of existing techniques. In recent years, edge computing and federated learning have opened up new possibilities and challenges for indoor localisation. This thesis presents a federated implementation for spatial mapping of the network based on the RSSI...
master thesis 2024
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Van Opstal, Quinten (author)
Federated learning provides a lot of opportunities, especially with the built-in privacy considerations. There is however one attack that might compromise the utility of federated learning: backdoor attacks [14]. There are already some existing defenses, like flame [13] but they are computationally expensive [14]. This paper evaluates a version...
bachelor thesis 2024
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Nenovski, Lazar (author)
Abstract— Federated Learning (FL) makes it possible for a network of clients to jointly train a machine learning model, while also keeping the training data private. There are several approaches when designing a FL network and while most existing research is focused on a single-server design, new and promising variations are arising that make...
bachelor thesis 2024
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van der Meulen, Jan (author)
Federated learning (FL) is a privacy preserving machine learning approach which allows a machine learning model to be trained in a distributed fashion without ever sharing user data. Due to the large amount of valuable text and voice data stored on end-user devices, this approach works particularly well for natural language processing (NLP)...
bachelor thesis 2024
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Li, Zirui (author)
End-to-end Automatic Speech Recognition (ASR) systems improved drastically in recent years and they work extremely well on many large datasets. However, research shows that these models failed to capture the variability in speech production and have biases against the variant caused by the regional accented speech. Moreover, ASR research on...
master thesis 2023
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Mandlik, Nishad (author)
This thesis presents Screen Antenna - A Visible Light Communication (VLC) system that integrates data transmission and reception, with the conventional pixel display capability of RGB LEDs. The system is constructed with off-the-shelf components and runs on the Arduino Due microcontroller. The hardware and software have been designed with the...
master thesis 2023
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Miao, Michael (author)
Due to recent developments in DNA sequencing technology, there is a growing abundance of available genomic data. To process this information for use in fields such as healthcare and forensics, raw sequencing data have to be processed using computationally intensive algorithms. Currently, one of the major bottlenecks in this processing pipeline...
master thesis 2023
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van Mierop, Ron (author)
The considerable increase in the number of devices needing connectivity, such as mobile phones and Internet of Things (IoT) devices, has led to an exponential rise in data volumes during the last years, that will surely continue over the next decade. Therefore, it will be increasingly challenging to provide sufficient RF resources. A novel...
master thesis 2023
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Ren, Liyuan (author)
For the development of automatic People Counting systems, radar is increasingly becoming a popular technology because of the increasingly stringent privacy requirements for people demographic information and the requirement to operate in a challenging environment. Because of the complexity of multi-target movement and the diversity of...
master thesis 2022
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Tian, Yuhang (author)
In this work, we propose FLVoogd, an updated federated learning method in which servers and clients collaboratively eliminate Byzantine attacks while preserving privacy. In particular, servers use automatic Density-based Spatial Clustering of Applications with Noise (DBSCAN) combined with S2PC to cluster the benign majority without acquiring...
master thesis 2022
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Dierick, Luc (author)
In recent years, the big data era has produced an increasing volume and complexity of data that requires processing. To analyze and process these large amounts of data, applications are being scaled on large clusters using distributed data processing frameworks. A more recent trend utilizes hardware accelerators to offload computationally...
master thesis 2022
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Chen, Qilin (author)
Convolutional neural networks (CNNs) are often pruned to achieve faster training and inference speed while also requiring less memory. Nevertheless, during computation, most modern GPUs cannot take advantage of the sparsity automatically, especially on networks with unstructured sparsity. Therefore, many libraries that exploit sparsity, have...
bachelor thesis 2022
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Deshamudre, Rohan (author)
Smart contracts allow for the collaboration and transaction processes between multiple parties/organisations to be automated and conducted in a neutral environment. In many situations these agreements are confidential and running a smart contract that contains private/sensitive information on a public blockchain network which is transparent and...
bachelor thesis 2022
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Nanhekhan, Kevin (author)
Smart contracts play an important role within the blockchain by ensuring that valid transactions are being recorded. However, there are critical concerns regarding the security and privacy of data within these blockchain applications. This research provides information on how the integration of the Trusted Platform Module can achieve more...
bachelor thesis 2022
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Starke, Zeddrich (author)
Block-chain technology is gaining momentum in both industry and academics. With<br/>this momentum there are a lot of potential gains, but also potential risk involved. This papers proposes a solution for security risks, like a man-in-the-middle-attack, of the permissioned block-chain distributed ledger software Hyperledger Fabric. A prototype is...
bachelor thesis 2022
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Chatterjee, Agniv (author)
Blockchain networks are increasingly recognized as a disruptive technology across sectors such as online services, finance, supply chain, administration etc. They are underpinned by smart contracts which provide programmatic instruction for the blockchain to operate. A major obstacle in the widespread adoption of blockchain technology is the...
bachelor thesis 2022
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SONG, TIANLI (author)
Big data analytics is one of the foundations for booming technologies such as machine learning, genetics/genomics, and computer vision. These big data applications require a large amount of data transfers for distributed and parallel processing. Networking is thus a crucial facilitator and could make big impact on big data processing.<br/><br/...
master thesis 2021
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Meral, Murat Kaan Meral (author)
Automated asset trading is a crucial method used by financial entities such as investment firms or hedge funds. It allows them to allocate their capital in order to maximize their rate of returns. In scientific literature, there are multiple models suggested to solve this problem. However, these models either lack the complexity to understand...
bachelor thesis 2021
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Dönszelmann, Jonathan (author)
Multi-agent pathfinding (MAPF) is the process of finding collision-free paths for multiple agents. MAPF can be extended by grouping agents into teams. In a team, agents need to be assigned (or matched) to one of the team's goals such that the sum of individual cost} is minimised. This extension is called MAPF with matching (MAPFM). M* is a...
bachelor thesis 2021
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