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When it comes to innovation, economic growth, affluence and international attractiveness, there are currently few places in the world that can compare with the San Francisco Bay Area. However, new megatrends such as Sustainability, can challenge its attractiveness. Scholars talk about the “Nordic approach”.In the geographical area of Southern Scandinavia, ‘The Strait Area’, the focus is on Sustai
This paper examines the development of the Artificial Intelligence (AI) meta-debate in Sweden before and after the release of ChatGPT. From the perspective of agenda-setting theory, we propose that it is an elite outside of party politics that is leading the debate – i.e. that the politicians are relatively silent when it comes to this rapid development. We also suggest that the debate has become This paper examines the development of the Artificial Intelligence (AI) meta-debate in Sweden before and after the release of ChatGPT. From the perspective of agenda-setting theory, we propose that it is an elite outside of party politics that is leading the debate – i.e. that the politicians are relatively silent when it comes to this rapid development. We also suggest that the debate has become
An increasingly globalised world has led to great language diversity in institutional settings. Sweden is no exception; 3 of 10 students in compulsory school have a migrant background. Increased diversity may result in challenges, e.g. knowing how to balance the use of the target language with other languages represented among the students to facilitate learning and interaction. As educational pol
Bayesian Optimization has emerged as a crucial technique for optimizing costly, black-box functions where each evaluation comes at a high cost, such as in scientific experiments, and machine learning hyperparameter optimization. By combining probabilistic modeling with sequential decision-making, Bayesian Optimization achieves efficient exploration, guiding the search toward optimal parameters wit
Network Function Virtualization (NFV) has shifted communication networks towards more adaptable software solutions, but this transition raises new security concerns, particularly in public cloud deployments. While Intel’s Software Guard Extensions (SGX) offers a potential remedy, it requires complex application adaptations. This paper investigates AMD’s Secure Encrypted Virtualization (SEV) as an
People form part of the biosphere - the biosphere being the whole intertwined network of life on Earth. While there is convergence on the need for societal change for just sustainability and a healthy biosphere, the pathways to achieve these transformations remain relatively unclear. Through legal interpretation, conceptual and thematic analysis of academic and grey literature, we seek to answer t
This thesis explores the challenges and advancements in high-dimensional Bayesian optimization (HDBO), focusing on understanding, quantifying, and improving optimization techniques in high-dimensional spaces.Bayesian optimization (BO) is a powerful method for optimizing expensive black-box functions, but its effectiveness diminishes as the dimensionality of the search space increases due to the cu
During recent years, research on authenticated encryption has been thriving through two highly active and practice-motivated research directions: provably secure leakage-resilience schemes and key- or context-commitment security. However, the intersection of both fields had been overlooked until very recently. In ToSC 1/2024, Struck and Weish\"aupl studied generic compositions of Encryption scheme
This chapter discusses a wide range of arguments that critically reflects on the use of experiments as method in visual strategic communication research. Methodological improvements and additional psychological research are needed in the interpretation of multimodal messages to facilitate the development of valid measures of content in research. The chapter presents a brief overview of controlled
We present a unique comparative analysis, and evaluation of vision, radio, and audio based localization algorithms. We create the first baseline for the aforementioned sensors using the recently published Lund University Vision, Radio, and Audio (LuViRA) dataset, where all the sensors are synchronized and measured in the same environment. Some of the challenges of using each specific sensor for in
In this paper, we revisit the rotation averaging problem applied in global Structure-from-Motion pipelines. We argue that the main problem of current methods is the minimized cost function that is only weakly connected with the input data via the estimated epipolar geometries. We propose to better model the underlying noise distributions by directly propagating the uncertainty from the point corre
The upcoming Artificial Intelligence (AI) Act is the European Union's attempt to regulate high-risk AI systems and foundation models. We give an up-to-date overview of the act's key requirements, explain how the high-risk classification works, and highlight what matters for its operationalization.
The dramatic improvements in Boolean satisfiability (SAT) solving since the turn of the millennium have made it possible to leverage conflict-driven clause learning (CDCL) solvers for many combinatorial problems in academia and industry, and the use of proof logging has played a crucial role in increasing the confidence that the results these solvers produce are correct. However, the fact that SAT
We present novel solutions to previously unsolved prob-lems of relative pose estimation from images whose calibration parameters, namely focal lengths and radial distortion, are unknown. Our approach enables metric reconstruction without modeling these parameters. The minimal case for reconstruction requires 13 points in 4 views for both the calibrated and uncalibrated cameras. We describe and imp
Line segments are ubiquitous in our human-made world and are increasingly used in vision tasks. They are complementary to feature points thanks to their spatial extent and the structural information they provide. Traditional line detectors based on the image gradient are extremely fast and accurate, but lack robustness in noisy images and challenging conditions. Their learned counterparts are more
The paper explores the usage of minimax adaptive controllers to guarantee finite L2 -gain simultaneous stabilization of linear time-invariant (LTI) plants. It is shown that a minimax adaptive controller simultaneously stabilizes any two multiple-input multiple-output (MIMO) P-stabilizable LTI plants when no LTI controller can achieve that, and the worst attained L2 -gain bound for the transient dy
We study optimal information provision in transportation networks when users are strategic and the network state is uncertain. An omniscient planner observes the network state and discloses information to the users with the goal of minimizing the expected travel time at the user equilibrium. Public signal policies, including full-information disclosure, are known to be inefficient in achieving opt
A convex optimization framework over contrast current density is developed to calculate fundamental bounds on the performance of linear passive cloaks. The formulation uses the method of moments applied to the electric field integral equation while using extincted power as the optimized metric. The presented results show that high cloaking efficiency requires cloaks made of low-loss and high-contr
This paper presents INTRACFG, a declarative and language-independent framework for constructing precise intraprocedural control-flow graphs (CFGs) based on the reference attribute grammar system JastAdd. Unlike most other frameworks, which build CFGs on an Intermediate Representation level, e.g., bytecode, our approach superimposes the CFGs on the Abstract Syntax Tree, enabling accurate client ana
