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Existing datasets for autonomous driving (AD) often lack diversity and long-range capabilities, focusing instead on 360° perception and temporal reasoning. To address this gap, we introduce Zenseact Open Dataset (ZOD), a large- scale and diverse multimodal dataset collected over two years in various European countries, covering an area 9×that of existing datasets. ZOD boasts the highest range and
The aim of this thesis is to contribute to the understanding of everyday leisure travel for social and recreational trip purposes by describing and problematising car use for such trips. Leisure trips are a significant contributor to greenhouse gas emissions and reductions are needed to mitigate climate change. Technical solutions, such as electric vehicles, contribute but research has demonstrate
This chapter explores the interaction between competition law and especially Article 101(3) TFEU and environmental and climate change goals in the context of the EU’s Green Deal and the aim of energy transition. First, it reviews the evolution of the Commission’s and national authorities’ approaches to environmental and climate benefits in their general assessment of horizontal and vertical agreem
Aerosolised Polystyrene Latex (PSL) nanoparticles are, due to their well-defined size, spherical shape, and inert surface, useful in many experimental applications, including studies of particle deposition in the human lung. Aerosolising nanoparticles entails added challenges, and nanoparticles can potentially be more hazardous than otherwise equivalent microparticles. The objective of this work w
Background: Nodal assessment in gallbladder cancer remains challenging, particularly in incidental gallbladder cancer. This understages the number of patients with node-positive disease, resulting in prognostic inaccuracy and insufficient adjuvant treatment. This study aimed to identify risk factors for positive nodes in gallbladder cancer and to compare prognostic discrimination of available noda
This thesis investigates the remanufacturing potential of the electric front cross differential (eFXD) within the context of the circular economy (CE) and the R‑framework. Environmental assessment, mechanical validation and structured component classification are combined to identify opportunities and limitations for remanufacturing. The results show that a limited number of components, the tube h
This thesis studied the recording methodologies of conducting unannounced evacuation drills to enhance the understanding of evacuation behaviours and performance within the Complex Muon Solenoid (CMS) cavern at CERN. The primary objective was to validate the CMS underground evacuation simulation model for planned evacuation and compare various data collection methods. An unannounced evacuation dr
Preeclampsia (PE) occurs in up to 5% of worldwide pregnancies. It is a complex disease characterised by sudden onset hypertension, and it is harmful to the mother as well as the growing baby, accounting for 40% of fetal deaths worldwide. The disease can be divided into early and late-onset PE, defined as diagnosis earlier or later than 34 weeks of gestation. Despite decades of research, the cause
We present a data-driven proof of concept model capable of reproducing expected counterparty credit exposures from market and trade data. The model has its greatest advantages in quick single-contract exposure evaluations that could be used in front office xVA solutions. The data was generated using short rates from the Hull-White One-Factor model. The best performance was obtained from a GRU neur
With the ambition to contribute to a sustainable development, this project started with aim to recycle fiber boards. The idea behind the project is to take lose fibers that come from waste product or simply just worn out fiber boards, and make them into new fiber boards. In order to achieve this, a binder is needed to hold the boards together. The aim of this thesis was to evaluate different binde
The food industry is facing challenges in responding to the climate crisis, and research highlights the potential of using Business Intelligence & Analytics for organizations sustainability efforts. The aim of this study is to holistically map through the affordance lens, what capabilities organizations in the food industry may potentially gain by using BI&A for sustainability. The study i
The purpose of the thesis is to design a new antenna system and to verify its link performance in 5G FR2 mmWave frequency for handheld devices to enable cellular communication. The main objective is to design an antenna primarily at 28GHz and 39GHz to enhance spectrum efficiency, along with improved transmission data rates, enabling new cases like Augmented Reality (AR), Virtual Reality (VR) and
Research conducted on industrial symbiosis often brings up the importance of trust and collaboration related constraints and enablers if inter-organizational efforts are to be pursued. This is also found in literature related specifically to Sweden and its agri-food sector. There are limited examples of collecting empirical evidence on trust in relation to IS and even less so with a focus on SMEs.
Spallation sources such as European Spallation Source (ESS) produces neutrons by bombarding high-energy protons onto the target wheel. To determine the location of the proton beam a Proton Beam Imaging (PBI) system will be installed. The PBI system at ESS relies on the properties of a luminescent coating that is sprayed onto the target wheel and the proton beam window. In this study, luminescent m
There is an extensive expansion of fiber infrastructure for high-speed broadband networks in Sweden, and Landskrona municipality is one of the leading examples. Owing to the superior capabilities of a fiber based network, a number of digital welfare services can be provided directly to residents and companies of the municipality. Social care is an example of a welfare service that can utilize the
Deep learning is a machine learning technique inspired by the biological nervous system. The method has been used more and more over the last decades. Within this thesis, convolutional neural networks (CNN:s) are used for Gleason classification of prostate cancer in histopathological images. The data that has been used consists of digitalized microscopic images of prostate biopsies stained with ha
Flow cytometry is a versatile tool for monitoring a microbial population at a single-cell level. Multiple parameters can be monitored based on the users’ requirements through the utilization of different dyes, biosensors etc., and the use of FCM for on-line measurements during fed-batch cultivations has the potential to be used for precise process control. This project consisted of the development
The reassignment method is a technique for improving the concentration of signals in spectrograms and other time-frequency representations (TFR). It achieves this by displacing the points in a TFR according to the reassignment vector for every point. By doing so, the reassignment method gives perfect concentration of infinite constant frequency sinusoids, impulses and linear chirps. A downside to
