Searched for: subject%3A%22graph%22
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Hristov, Tsvetomir (author)
Although digital watermarking has been a well-researched topic for the past decades and has seen numerous implementations for relational databases, it still lacks research for non-relational schema-less databases. In this paper, we explore proposed techniques for non-relational database watermarking and introduce an improved technique for NoSQL...
bachelor thesis 2023
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Sui, Zhongyi (author), Wen, Yuanqiao (author), Huang, Yamin (author), Song, R. (author), Piera, Miquel Angel (author)
The theoretical analysis of maritime accidents is a hot topic, but the time characteristics and dynamics of maritime accidents time series are still unclear. It is difficult to draw a clear conclusion from the cause analysis, so the accident is difficult to be predicted. To bridge this gap, this research analyzes the characteristics and...
journal article 2023
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Huijsman, Robbert (author)
TreeContainment is a well-known problem within phylogenetics, which asks whether a binary phylogenetic tree is embedded in a binary phylogenetic network. For this problem, Jones, Weller and van Iersel (2022) have created an algorithm that uses dynamic programming on tree-decompositions to achieve a running time that is exponential in the tree...
master thesis 2023
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Driebergen, Tim (author)
The minimum vertex cover problem (MinVertexCover) is an important optimization problem in graph theory, with applications in numerous fields outside of mathematics. As MinVertexCover is an NP-hard problem, there currently exists no efficient algorithm to find an optimal solution on arbitrary graphs. We consider quantum optimization algorithms,...
master thesis 2023
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Croft, Maxime (author)
This paper presents a novel approach to regional forecasting of SARS-Cov-2 infections one week ahead, which involves developing a municipality level COVID-19 dataset of the Netherlands and using a spatio-temporal graph neural network (GNN) to predict the number of infections. The developed model captures the spread of infectious diseases within...
master thesis 2023
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Shi, S. (author), Cheng, Xiaodong (author), Van den Hof, Paul M.J. (author)
Identifiability of a single module in a network of transfer functions is determined by whether a particular transfer function in the network can be uniquely distinguished within a network model set, on the basis of data. Whereas previous research has focused on the situations that all network signals are either excited or measured, we develop...
journal article 2023
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Yang, Qiuling (author), Coutino, Mario (author), Leus, G.J.T. (author), Giannakis, Georgios B. (author)
Graph-based learning and estimation are fundamental problems in various applications involving power, social, and brain networks, to name a few. While learning pair-wise interactions in network data is a well-studied problem, discovering higher-order interactions among subsets of nodes is still not yet fully explored. To this end, encompassing...
journal article 2023
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Duan, Xiaowei (author)
The inverse shortest path problem (ISPP) is a problem based on graph theory, that is to design link weights in a graph to satisfy that given paths are the shortest between the corresponding node pairs. It can be used in networks of complex systems to solve practical problems such as re-routing in transportation systems and reallocating resources...
master thesis 2022
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Niessen, Lex (author)
In the past decade, the application of Neural Networks (NNs) has received increasing interest due to the growth in computing power. In the field of computational mechanics, this has led to numerous publications presenting surrogate models to assist or replace conventional simulation methods. A subset of these networks, referred to as Graph...
master thesis 2022
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Li, Zhuoheng (author)
Programmers usually write test cases to test onboard software. However, this procedure is time-consuming and needs sufficient prior knowledge. As a result, small satellite developers may not be able to test the software thoroughly. <br/> <br/>A promising direction to solve this problem is reinforcement learning (RL) based testing. It searches...
master thesis 2022
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Chandrashekar, Rohan (author)
Humans make decisions when presented with choices based on influences. The Internet today presents people with abundant choices to choose from. Recommending choices with an emphasis on people's preferences has become increasingly sought. Grundy (1979), the first computer librarian Recommender System (RS), provided users with book recommendations...
master thesis 2022
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Mc Donald, Tom (author)
Recently, ReLU neural networks have been modelled as constraints in mixed integer linear programming (MILP) enabling surrogate-based optimisation in various domains as well as efficient solution of machine learning verification problems. However, previous works have been limited to multilayer perceptrons (MLPs). The Graph Convolutional Neural...
master thesis 2022
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van Velzen, Daan (author)
Preferential Attachment models offer an explanation for why power laws are so common in real-world data. In these models, we start out with an initial network and add nodes one at a time. For each new node, we make m connections to existing nodes and if we define the attachment probability of attaching to a vertex to be proportional to its...
master thesis 2022
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Meng, Zixi (author)
Leakage is the main source of water loss in water distribution networks (WDNs). Therefore, leak detection and localization technology is a major concern for water utilities to save water and meet the ever-growing water demand. This study presents two methodologies for leak localization in District Metered Areas (DMAs): (1) a model-based method...
master thesis 2022
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Jin, Ying (author)
The main goal of this thesis is to understand the topological properties of semantic networks, to find language-specific patterns, and to investigate their connection principles. Interpreting unstructured texts in natural language is a crucial task for computers. Natural Language Processing (NLP) applications rely on semantic networks for...
master thesis 2022
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de Jong, Arnoud (author)
The impact of delays and disturbances in railway traffic can be mitigated by advanced rail traffic rescheduling models (RTRMs) which make use of mathematical optimization models. In the past several researches have been carried out on the effectiveness of an RTRM in reducing delay and improving punctuality. However, in most of these researches...
master thesis 2022
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Klisse, M. (author)
This dissertation is concerned with the study of the structure of certain deformations of operator algebras associated with Coxeter groups. These operator algebras, called Hecke C*-algebras and Hecke-von Neumann algebras, are operator algebraic completions of Iwahori-Hecke algebras. They occur as natural abstractions of certain endomorphism...
doctoral thesis 2022
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Chuang, Ching Chi (author)
Dependency management is an important task in software maintenance. However, identifying and removing unused dependencies takes a lot of effort from developers as existing tools may discover many false positives which are challenging to distinguish. This paper proposes a decision framework to improve unused dependency detection. It is applied to...
master thesis 2022
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Shirekar, Ojas (author)
A primary trait of humans is the ability to learn rich representations and relationships between entities from just a handful of examples without much guidance. Unsupervised few-shot learning is an undertaking aimed at reducing this fundamental gap between smart human adaptability and machines. We present a contrastive learning scheme for...
master thesis 2022
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Habib, Benjamin (author)
Whereas in the past, Distribution Systems played a passive role in connecting customers to electricity, Distribution System Operators (DSOs) will have to take in the future a more active role in monitoring and regulating the network to deal with the new behaviors and dynamics of the system brought by the energy transition. State Estimation, a...
master thesis 2022
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