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Gnanavarothayan, Kabilan (author)
The use of Internet of Things (IoT) devices has experienced an increase since its inception and is expected to continue to do so. However, this growth has also attracted individuals with malicious intentions. Botnet attacks on IoT devices have become more potent each year, exploiting new vulnerabilities and attacking more devices. Therefore, it...
master thesis 2023
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Moonen, Djoshua (author)
Payment channels allow parties to utilize the blockchain to send transactions for a cheaper fee. Previous work has analyzed to which degree a party can profit by facilitating the transaction process. The aim is to increase the usability of the network and to be rewarded for providing this service. However, previous work focuses on maximizing the...
master thesis 2023
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Katz, Roy (author)
Federated learning enables the construction of machine learning models, while adhering to privacy constraints and without sharing data between different devices. It is achieved by creating a machine learning model on each device that contains data, and then combining these models through an aggregation algorithm without sharing the data....
bachelor thesis 2023
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Elaref, Mahmoud (author)
Synthetic art is the end result of artificial intelligence models that have been trained to generate images from text prompts. "Comic synthesis" is one such use case, where comic illustrations are produced from textual descriptions. Previous attempts at comic synthesis have utilized conditional Generative Adversarial Networks (cGANs), but this...
bachelor thesis 2023
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van Setten, Jordi (author)
With the increasing demand for high- quality data in the field of Machine Learning and AI, the availability of such data has become a major bottleneck for further advancements. This paper proposes a novel approach to extract valuable data from comic illustrations, aiming to address the scarcity of labeled datasets. By leveraging popular comic...
bachelor thesis 2023
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Cristea, Vlad (author)
Federated Learning is a machine learning paradigm for decentralized training over different clients. The training happens in rounds where each client learns a specific model which is then aggregated by a central server and passed back to the clients. Since the paradigm’s inception, many frameworks that provide Federated Learning tools and...
bachelor thesis 2023
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Sīpols, Emīls (author)
Federated learning (FL) has emerged as a promis-ing approach for training machine learning models using geographically distributed data. This paper presents a comprehensive comparative study of var-ious machine learning models in the context of FL. The aim is to evaluate the efficacy of these models in different data distribution scenarios and...
bachelor thesis 2023
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Xu, Jiaming (author)
Tabular data is widely used in various fields and applications, making the synthesis of such data an active area of research. One important aspect of this research is the development of methods for privacy-preserving data synthesis, which aims to generate synthetic data that retains statistical properties while protecting the privacy of...
master thesis 2023
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Li, Xinqi (author)
Quantitative cardiac MRI is an increasingly important diagnostic tool for cardiovascular diseases. Yet, it is essential to have correct image registration for good accuracy and precision of quantitative mapping. Registering all baseline images from a quantitative cardiac MRI sequence, however, is nontrivial because the patient is moving, leading...
master thesis 2023
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Melas, Minas (author)
Data processing systems have become increasingly important in modern computing, as the volume and complexity of data that needs to be analyzed has grown dramatically. Multiple data processing systems have been and are being developed, that are scalable, resilient and performant.<br/><br/>However, despite the advances made in data processing...
master thesis 2023
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Zarin, Naqib (author)
Blockchain technology has proven to be a promising solution for decentralized systems in various industries. At the core of a blockchain system is the peer-to-peer (P2P) overlay, which facilitates communication be- tween parties in the blockchain system. Recently, there is increasing evidence that this P2P overlay plays a major role in limited...
master thesis 2023
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van Schijndel, Jessie (author)
The workflow of a data science practitioner includes gathering information from different sources and applying machine learning (ML) models. Such dispersed information can be combined through a process known as Data Integration (DI), which defines relations between entities and attributes. When all information is combined in one source suited...
master thesis 2022
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Wang, Wang Hao (author)
Current speed of data growth has exponentially increased over the past decade, highlighting the need of modern organizations for data discovery systems. Several (automated) schema matching approaches have been proposed to find related data, exploiting different parts of schema information (e.g. data type, data distribution, column name, etc.)....
master thesis 2022
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Stallenberg, Dimitri (author)
Traditional software testing is a labor-intensive and expensive manual process. To mitigate the high cost of manual test case generation, researchers have developed various techniques for automated test case generation over the last few decades. These techniques make use of static type information to determine which data types should be used in...
master thesis 2022
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Visser, Maaike (author)
As the amount of information available in the world grows, Information Retrieval (IR) systems have become an integral part of day to day life. They determine what subset of the large pool of information is shown to people. IR algorithms determine which items should be returned in response to a query and rank the results in a ranked list.<br/...
master thesis 2022
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Provó Kluit, Mark (author)
Large­scale machine learning frameworks can accelerate training of a neural network by per­ forming distributed training on a cluster using multiple GPUs per node and multiple nodes. Because distributed training on a cluster involves many nodes which need to communicate and load and exchange data, a machine learning framework may at certain...
master thesis 2022
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Petrescu, Stefan (author)
Modern systems generate a tremendous amount of data, making manual investigations infeasible, hence requiring automating the process of analysis. However, running automated log analysis pipelines is far from straightforward, due to the changing nature of software ecosystems caused by the constant need to adapt to user requirements. In practice,...
master thesis 2022
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Deaconu, Sebastian (author)
This paper analyzes how flocking behavior in fish can be used to develop target protection algorithms. This starts from the hypothesis that fish aggregate into coordinated flocks in order to protect themselves from predatory attacks. In order to test the protection capabilities of fish, a Prey-Predator instance is developed in which faults are...
bachelor thesis 2022
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Ali, Suleyman (author)
A majority of existing single-anchor localization algorithms make use of antenna arrays or special antenna systems. However, the need for specialized antenna systems incurs higher costs, complexity and power consumption. This paper presents a novel single-anchor localization algorithm, which does not require antenna arrays or special antennas....
bachelor thesis 2022
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Gökbulut, Mert (author)
One of the key problems of swarm robotics is how the mobile robots can navigate accurately in a given environment. To achieve this, the mobile robots need to accurately determine where they are globally, or relative to other robots and landmarks. This paper is going to be an investigation of the Monte Carlo Localization algorithm in an...
bachelor thesis 2022
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