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Project ElectriFly: Electric Commuter Aircraft with Mid-Flight Recharging Capability

Dadoo, Vani (author), Jadhavrao, Vishwa (author), Vale de Almeida Norte, Marta (author), Aversa, Alberto (author), Fabrykiewicz, Ada (author), van der Spek, Bas (author), Broos, Sam (author), Savelberg, Thijs (author), Gniadek, Gosia (author), Dissel, Luca (author)

Bachelor Thesis: Design Synthesis Exercise 2023<br/>Group 13: Electric General Aircraft<br/><i>in collaboration with</i><br/>Group 10: Mid-Flight Recharging System<br/><br/>Addressing the pressing need for sustainability amid climate change, the aviation sector is under pressure to mitigate its significant carbon emissions. As aviation accounts...

bachelor thesis 2023

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Survey of Affect Representation Schemes used in Automatic Affect Prediction for Speech Emotion Recognition: A Systematic Review

Rawat, Aditi (author)

Automatic affect prediction systems usually assume its underlying affect representation scheme (ARS). This systematic review aims to explore how different ARS are used for in affect prediction systems based on spoken input. The focus is only on the audio input from speakers. Various datasets for speech emotion recognition were also involved in...

bachelor thesis 2023

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Effects of weather data on traffic flow predictions using an LSTM deep learning model

Nachev, Nikola (author)

Accurate traffic forecasts are a key element in improving the traffic flow of urban cities. An efficient approach to this problem is to use a deep learning Long Short Term Memory (LSTM) model. Including weather data in the model can improve prediction accuracy because traffic volumes are sensitive to weather changes. The aim of this study is to...

bachelor thesis 2023

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Survey of Affect Representation Schemes used in Vision-Based Automatic Affect Prediction: A Systematic Literature Review

Serrano Ruber, Lucia (author)

In human-human interactions, the majority of information is conveyed through body language, specifically facial expressions. Consequently, researchers have been interested in improving human-computer interactions through developing systems with automatic understanding of body language and facial expressions.  This technology is especially useful...

bachelor thesis 2023

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Affect Representation Schemes Used in Affective Video Content Analysis: A Systematic Literature Review

Chakravorty, Ashika (author)

Affective Video Content Analysis aims to automatically analyze the intensity and type of affect (emotion or feeling) that are contained in a video and are expected to arise in users while watching that video. This study aims to provide a systematic overview of various affect representation schemes utilised by researchers in the field of...

bachelor thesis 2023

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Short-term Earthquake Prediction with Deep Neural Networks: Finding the optimal time prior to earthquake strikes to use in predictions

van den Belt, Glenn (author)

Earthquakes can have tremendous effects. They can result in casualties, massive damage, and hurt the economy. Therefore, one would like to predict earthquakes as early as possible and with the highest accuracy possible. This paper contains the proposal for the optimal prediction-time, which is the time between the execution of a prediction and...

bachelor thesis 2022

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Comment Or Not To Comment: The Effects Of Comments On Method Name Prediction

Mouman, Nada (author)

Machine learning (ML) algorithms have been used frequently in the past years for Software Engineering tasks.<br/>One of the popular tasks researchers use is method name prediction, which helps them generate an identifier for methods with ML models such as Code2Seq.<br/>This model represents code snippets as Abstract Syntax Trees (AST) and...

bachelor thesis 2022

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Impact of seismic wave length to detect high-magnitude earthquakes via deep learning

Georgiev, Gancho (author)

Earthquakes are one of the most destructive natural phenomena, both in terms of human lives, and property damage. Although they are treated as a random phenomenon, the ability to predict them, even few seconds before they occur, could be of great benefit to society. Lots of research has been done on this topic but without any significant results...

bachelor thesis 2022

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How long before strike can we predict earthquakes with an LSTM neural network?

Charlot, Amaury (author)

Different methods have been studied to predict earthquakes, but the results are still far from optimal. Due to their seemingly dynamic and unpredictable nature, it has been very hard to find data correlating with earthquakes happening. But recently, various research has been done using neural networks, and some has suggested that it could...

bachelor thesis 2022

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Impact of Focal Depth on Short-Term Earthquake Prediction using Deep Learning

Krisiukėnas, Pijus (author)

Due to the devastating consequences of earthquakes, predicting their occurrence before the first strike has been a long standing research topic. Deep learning models have been used to facilitate prediction, using seismograph data to attempt to classify an earthquake right before it happens. However, this is a difficult task and research needs to...

bachelor thesis 2022

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Predicting Micro-Earthquakes with Deep Neural Networks

Zhu, Kevin (author)

Earthquake prediction is the field of seismology concerned with predicting the time, location, and magnitude of earthquakes within a small time frame, usually defined in terms of minutes or seconds before an event. Such predictions can have a large impact on minimizing the damage caused by these seismic events, by providing early warnings to the...

bachelor thesis 2022

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Evaluation of natural language processing embeddings in protein function prediction for bacteria

Cosma, Bianca (author)

<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...

bachelor thesis 2022

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The Effect of Color Spaces and Spectra on a Strawberry Prediction Model

Rosenberg, Jaron (author)

The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...

bachelor thesis 2022

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Short-term Earthquake Prediction via Recurrent Neural Network Models: Comparison among vanilla RNN, LSTM and Bi-LSTM

Du, XIANGYU (author)

Earthquake prediction has raised many concerns nowadays, due to the massive loss caused by earthquakes, as well as the significance of accurate forecasting. Lots of trials have been investigated and experimented but few achieved satisfying results on short-term prediction (i.e., usually those earthquakes that will happen in three months). It is...

bachelor thesis 2022

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Earthquake Prediction: A MLP & SVM Comparison

van den Akker, Daniel (author)

Multi-Layer Perceptron and Support Vector Machine have both been widely used in machine learning. In this research paper, these models have been applied to binary classification on an individual time series basis. The goal was to see whether they can predict earthquakes, using earthquakes measured at specific stations across New Zealand. As it...

bachelor thesis 2022

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Comparing multichannel mixed CNN-RNN to individual models for earthquake prediction

Houbaer, Maikel (author)

Earthquakes can do great harm to the environment and people's daily lives. Being able to predict an earthquake moments before it happens could therefore reduce harm and save human lives. Traditional methods have not been successful yet, but with the rise of techniques focused on deep learning, there is a growing interest to apply them to the...

bachelor thesis 2022

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Effect of Output Granularity on SARS-CoV-2 Variant Abundance Estimates using Domestic Wastewater Sequencing

Kalia, Yash (author)

Monitoring of SARS-CoV-2 variants is crucial to efforts in combating the COVID-19 pandemic. Lineage level abundance estimates for SARS-CoV-2 can be obtained from viral material present in domestic wastewater. The abundance predictions can be made at different levels of granularity-individual lineage level(high granularity) or variant level(low...

bachelor thesis 2022

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SARS-CoV-2 lineage abundance quantification in wastewater: a benchmark study for the identification of optimal reference set design

Nika, Ioanna (author)

Lineage abundance estimation of SARS-CoV-2 in wastewater is a technique that aims to monitor the lineage prevalence in communities and help contain the COVID-19 pandemic. Lineages are collections of closely related mutants of a virus. It is suggested that the genome sequences of lineages differ across the globe due to random mutations or...

bachelor thesis 2022

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How does a CNN mixed with LSTM methods compare with the individual one in predicting earthquakes?

Hashmi, Irtaza (author)

Earthquakes are one of the most dangerous natural disasters that occur worldwide. Predicting them is one of the unsolved problems in the field of science. In the past decade, there has been an increase in seismic monitoring stations worldwide, which has allowed us to design and implement data-driven and deep learning solutions. In this paper, we...

bachelor thesis 2022

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Improving the performance of Recurrent Neural Networks for time series prediction by combining Long Short-Term Memory and Attention Long Short-Term Memory

van Diepen, Aaron (author)

Recurrent neural networks (RNNs) used in time series prediction are still not perfect in their predictions and improvements can still be made in the area. Most recently transformers have led to great improvements in the field of RNNs, however transformers can not be used on time series data, because the architecture of transformers does not...

bachelor thesis 2021