Searched for: contributor%3A%22Epema%2C+D.H.J.+%28graduation+committee%29%22
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Janssen, Martijn (author)
Thread pools, integrated in programming languages, packages and dependencies are widely used by developers. Thread pools assume they are running alone on the system, which is not always the case. Previous research has shown that adapting thread pool size has been effective under specific conditions. In this research, scaling the thread pool with...
master thesis 2022
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Russel, Erwin (author)
Cloud gaming is a new paradigm that allows users to play games in the cloud and stream them to a thin client. While there is little research about cloud gaming, containerization technologies such as Docker could provide a virtualization alternative to Virtual Machines, as these suffer from overhead and GPU pass-through constraints. With Rapture,...
master thesis 2022
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Catlett, Joseph (author)
This paper aims to evaluate which automated measures of aesthetic beauty are the best predictors for human ratings of aesthetics and proposes that typicality and novelty may increase the correlation between the two. To study the correlation between these metrics, a literature study was performed to find a select amount of potentially good...
bachelor thesis 2022
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Çelebi, Betul Irmak (author)
Generative Adversarial Networks (GANs) brought rapid developments in generating synthetic images by mimicking structures in the training data. With the list of application of GANs growing drastically, it has lately become an exciting technology to explore for designers to communicate their ideas and arts through technology and create engaging...
bachelor thesis 2022
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Rahman, Moshiur (author)
Generative Adversarial Networks (GANs) can create artwork images and we need effective ways of rating their aesthetic values. This could help us determine the most aesthetic artwork images (and identify the GANs that created them) and train GANs to produce more aesthetic artwork images in the future. In this research, we analyzed the...
bachelor thesis 2022
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Nguyen, Bill (author)
Despite the fact that climate change is becoming increasingly dangerous and prevalent, there is still a lack of public engagement. This can be explained by the fact that the media portrays climate change as an abstract concept. The message can be more effectively communicated through visual art because it is more likely to invoke emotional...
bachelor thesis 2022
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Lorek, Oskar (author)
Machine learning models require rich, quality data sets to achieve high accuracy. With current exponential growth of data being generated it is becoming increasingly hard to prepare high-quality tables within reasonable time frame. To combat this issue automated data augmentation methods has emerged in recent years. However, existing solution do...
bachelor thesis 2022
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Cruset Pla, Eduard (author)
The democratization of data science, and in particular of the machine learning pipeline, has focused on the automation of model selection, feature processing, and hyperparameter tuning. Nevertheless, the need for high-quality data for increased performance has sparked interest in the inclusion of data augmentation in these automatic machine...
bachelor thesis 2022
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Neut, Oliver (author)
Automatic machine learning is a subfield of machine learning that automates the common procedures faced in predictive tasks. The problem of one such procedure is automatic data augmentation, where one desires to enrich the existing data to increase model performance. In relational data repositories, the data is stored in normal form. This causes...
bachelor thesis 2022
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Mastenbroek, Fabian (author)
Cloud datacenters underpin our increasingly digital society, serving stakeholders across industry, government, and academia. These stakeholders have come to expect reliable operation and high quality of service, yet demand low cost, high scalability, and corporate (environmental) responsibility. Datacenter operators are confronted frequently...
master thesis 2022
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Huang, Guangzhe (author)
With the advent of the cloud-native paradigm, the software development and deployment style has significantly reformed. An increasing number of enterprises are migrating their microservice applications onto Kubernetes, a production-grade container orchestration platform, to fully use the advantages of Kubernetes in self-healing, service...
master thesis 2021
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Albo Martinez, Diego (author)
Serverless computing is an emerging paradigm for structuring applications in such a way that they can benefit from on-demand computing resources and achieve horizontal scalability. As such, it is an ideal substrate for the resource-intensive and often ad-hoc task of training deep learning models. However, the design and stateless nature of...
master thesis 2021
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Timm, Jannes (author)
Thread pools are a pervasive building block for concurrent applications, but their optimal size is often tedious to determine or it changes during execution. Many modern systems use dedicated thread pools for operations that are restricted to a specific resource (e.g IO-bound), their performance can be correlated to OS metrics such as disk...
master thesis 2021
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Cox, Bart (author)
Deep neural networks (DNNs) are becoming the core components of many applications running on edge devices,especially for image-based analysis, e.g., identifying objects, faces, and genders. While very successful in resource rich environments like the cloud of powerful computers, utilizing Deep Learning on edge devices for inference is not used...
master thesis 2020
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Andreadis, G. (author)
Cloud datacenters provide a backbone to our digital society. Crucial to meeting increasing demand while maintaining efficient operation is the activity of capacity planning. Inaccurate capacity planning for cloud datacenters can lead to significant performance degradation, denser targets for failure, and unsustainable energy consumption....
master thesis 2020
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Langhout, T.J. (author), van Leeuwen, S.A.J. (author), Ort, C.I. (author), Volkers, W.S. (author)
The Deal Analytics group of PricewaterhouseCoopers Amsterdam has requested a tool for automatising the business-to-business customer analysis. This analysis was performed manually, which left room for performance improvement. This report discusses how the a product was developed which automates the analyses After two weeks of initial research, a...
bachelor thesis 2020
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Agrawal, Niket (author)
Edge computing extends the cloud computing capabilities to the edge of the network to facilitate processing of the data in the close proximity of its generation. It augments the deployment of several applications in the Internet of Things (IoT) domain which demand low latency and near real-time response for their reliable operation. However, the...
master thesis 2020
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van Schouwenburg, Sietse (author)
Simultaneous Localization And Mapping (SLAM) algorithms provide accurate localization for autonomous vehicles and provide essential information for the path planning module. However, SLAM algorithms as- sume a static environment in order to estimate a location. This assumption influences the pose estimation in dynamic urban environments. The...
master thesis 2019
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