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Medan autonom AI och AI-agenter inte är en ny idé är dess konsekvenser på längre sikt okända utifrån påverkan på företag och människors arbete. Trots framtidens inbyggda osäkerhet ökar trycket på företagsledare att redan idag besluta om AI-investeringar samtidigt som ledande narrativ inom ämnet ofta har en utopisk eller dystopisk lutning. Syftet med denna studie är att analysera hur AI-agenter pre
This paper is a component of a three-year empirical study of gaming moms undertaken with the aim to modulate the conventional constructions of gamer identities and examine the contested status of gaming in everyday life. It presents samples of mothers in gaming discourse – from TV, Music-video, forums, and ads. Mothers have been largely invisible in popular gaming discourse or formulaically portra
Objectives: The aim of this study was to investigate the influence of specific components of Andersen's behavioural model on adult individuals' perceived oral treatment need. Methods: A questionnaire was sent to a randomly selected sample of 9,690 individuals, 20 to 89 years old, living in Skane, Sweden. The 58 questions, some with follow-up questions, were answered by 6,123 individuals; a 63% res
In this paper, we propose a novel method for estimating the locations of near- and/or far-field harmonic audio sources impinging on an arbitrary, but calibrated, sensor array. Using a joint pitch and location estimation formed in two steps, we first estimate the fundamental frequencies and complex amplitudes under a sinusoidal model assumption, whereafter the location of each source is found by ut
This thesis analyses the debate around the patents on human genes from three most important angles: ethical, legal and economic. In the ethical context, patents on gene-related inventions are often seen as inappropriate because of the alleged special status of human DNA. The special status stems from their alleged responsibility for everything from diseases to social propensities and personal trai
We consider a perturbation problem for embedded eigenvalues of a self-adjoint differential operator in L2(R;Rn). In particular, we study the set of all small perturbations in an appropriate Banach space for which the embedded eigenvalue remains embedded in the continuous spectrum. We show that this set of small perturbations forms a smooth manifold and we specify its co-dimension. Our methods invo
The main focus of this study is preschool teachers' own learning from a specific course aimed to develop their knowledge of how to use learning study (LS) in preschool. The study included 24 qualified and experienced preschool teachers who took part in the course. The course was funded by the Swedish National Agency for Education and the teachers were chosen by their municipal employers. An analys
Recently there has been an increase in the number of available autonomous vehicle (AV) models. To evaluate and compare the safety of the various models the AVs need to be tested in several diverse safety-critical scenarios. We propose the Adversarial Test Case Generator (ATCG) that differently from previous test case generators allows for the generation of realistic collision scenarios with varied
Parkinson’s disease (PD) can produce postural abnormalities of the standing body position such as kyphosis. We investigated the effects of PD, deep brain stimulation (DBS) in the subthalamic nucleus (STN), vision and adaptation on body position in a well-defined group of patients with PD in quiet standing and during balance perturbations. Ten patients with PD and 25 young and 17 old control partic
In this paper we address absolute camera pose estimation. An efficient (and standard) way to solve this problem, is to use sparse keypoint correspondences. In many cases point features are not available, or are unstable over time and viewing conditions. We propose a framework based on silhouettes of quadric surfaces, with special emphasis on cylinders. We provide mathematical analysis of the probl
Activation functions play a central role in deep learning since they form an essential building stone of neural networks. In the last few years, the focus has been shifting towards investigating new types of activations that outperform the classical Rectified Linear Unit (ReLU) in modern neural architectures. Most recently, rational activation functions (RAFs) have awakened interest because they w
Many hand-held or mixed reality devices are used with a single sensor for 3D reconstruction, although they often comprise multiple sensors. Multi-sensor depth fusion is able to substantially improve the robustness and accuracy of 3D reconstruction methods, but existing techniques are not robust enough to handle sensors which operate with diverse value ranges as well as noise and outlier statistics
There exist several datasets for developing self-driving car methodologies. Manually collected datasets impose inherent limitations on the variability of test cases and it is particularly difficult to acquire challenging scenarios, e.g. ones involving collisions with pedestrians. A way to alleviate this is to consider automatic generation of safety-critical scenarios for autonomous vehicle (AV) te
The phase gradient autofocus (PGA) is a robust autofocusing approach that can efficiently refocus defocused synthetic aperture radar (SAR) imagery produced by frequency-domain algorithms. However, from a conventional viewpoint, PGA cannot be extended to refocus SAR imagery produced by time-domain algorithms, such as the filtered backprojection (FBP), as the spectrum of the FBP imagery is range amb
Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel res
This paper presents a robust phase-based positioningframework using a massive multiple-input multiple-output(MIMO) system. The phase-based distance estimates of MPCstogether with other parameters are tracked with an ExtendedKalman Filter (EKF), the state dimension of which varies withthe birth-death processes of paths. The iterative maximumlikelihoodestimation algorithm (RIMAX) and the modeling of
In this paper, we present a robust multipath-based localization and mapping framework that exploits the phases of specular multipath components (MPCs) using a massive multiple-input multipleoutput (MIMO) array at the base station. Utilizing the phase information related to the propagation distances of the MPCs enables the possibility of localization with extraordinary accuracy even with limited ba
