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Sverige har ett proportionellt valsystem, med en faktor som kan göra valresultatet mindre representativt - riksdagsspärren på fyra procent. Hur påverkar spärren väljares och partiers strategiska beteende? Vilka förändringar har genomförts i systemet de senaste femtio åren och hur kan det komma att utformas i framtiden?
Background: Surgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based
In this paper, we investigate the effects of different augmentation strategies in self-supervised representation learning from electrocardiograms. Our study examines the impact of random resized crop and time out on downstream performance. We also consider the importance of the signal length. Furthermore, instead of using two augmented copies of the sample as a positive pair, we suggest augmenting
Timely detection and surveillance of disease community spread is a potent tool for implementing effective public health interventions. This study investigates the National Telehealth Service (1177 helpline) across 18 regions in Sweden in 2020 to identify early signals of community transmission of COVID-19 at the beginning of the pandemic. Focusing on calls related to key COVID-19 symptoms (cough,
This paper addresses the hybrid quantized signal detection problem in a distributed radar system, where widely separated antennas transmit low-bit quantized data with varying quantization levels depending on the different bandwidth constraint for each channel to a fusion center. To enable a high detection performance with such hybrid quantized data, we formulate the generalized likelihood ratio, R
In this work, a computationally efficient evolutionary algorithm is proposed for estimating the direction of arrival (DOA) of coherently distributed (CD) sources corrupted by additive impulsive noise. The typical method, such as distributed signal parameter estimation (DSPE) method, requires a 2-D spectral peak search and cannot allow for coherent signals. The proposed method in this article uses
The problem of echo separation using digital beamforming (DBF) on receive for multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is of notable importance to allow for practical systems. Regrettably, current DBF-MIMO-SAR schemes, such as the short-term shift-orthogonal (STSO) scheme, are computationally cumbersome, increasing the required hardware complexity. To alleviate this pro
Traditional power reduction techniques such as DVFS or RAPL are challenging to use with web services because they significantly affect the services' latency and throughput. Previous work suggested the use of controllers based on control theory or machine learning to reduce performance degradation under constrained power. However, generating these controllers is challenging as every web service app
This paper considers the problem of jointly designing the transmit waveforms and weights for a frequency diverse array (FDA) in a spectrally congested environment in which unintentional spectral interferences exist. Exploiting the properties of the interference signal induced by the processing of the multi-channel mixing and low-pass filtering FDA receiver, the interference covariance matrix struc
Machine Learning (ML) offers many opportunities, but its reliance on personal data raises privacy concerns. One such example is the Membership Inference Attack (MIA), which aims to determine whether a specific data point was part of a model’s training dataset. In this paper, we investigate this attack on Random Forests (RFs) and propose a method to quantify their vulnerability to MIA. We also demo
Today, the overwhelming majority of Internet of Things (IoT) and mobile edge devices have extreme resource limitations, e.g., in terms of computing, memory, and energy. As a result, training Deep Neural Networks (DNNs) using the complex Backpropagation (BP) algorithm on such edge devices presents a major challenge. Forward-only algorithms have emerged as more computation- and memory-efficient alte
Alteration in postural orientation (i.e., the ability to align body segments in relation to each other) can occur due to pain or injury and is suggested to be a risk factor for traumatic knee injuries and early onset and progression of knee osteoarthritis. However, clinical and biomechanical assessment of postural orientation is time-consuming, thus new and faster methods are needed in order to be
Levodopa provides effective symptomatic treatment for Parkinson's disease. However, nonmotor symptoms are often insufficiently relieved, and its long-term use is complicated by motor fluctuations and dyskinesia. To clarify mechanisms of levodopa-induced dyskinesia and pharmacological interventions aimed at reducing dyskinetic symptoms, we have here characterized the neurophysiological activity pat
Dopamine replacement therapy for Parkinson's disease can induce impulsive-compulsive behaviours (ICBs). Here we compare the D2/3 agonist ropinirole and L-DOPA, given alone or combined, with regard to their potential to induce ICBs in rats sustaining bilateral striatal injections of 6-hydroxydopamine. Daily treatment with ropinirole (2.5 mg/kg), L-DOPA (24.0 mg/kg), or their combination was given f
Given two neural network classifiers with the same in-put and output domains, our goal is to compare the two networksin relation to each other over an entire input region (e.g., within avicinity of an input sample). To this end, we establish the foundationof formal local implication between two networks, i.e., N2D=⇒ N1, in an entire input region D. That is, network N1 consistently makesa correct d
In this paper, we revisit the problem of estimating the relative pose from a sparse set of point-correspondences. For each point-correspondence we also estimate the relative depth, i.e. the relative distance to the scene point in the two images. This yields an additional constraint, allowing us to use fewer matches in RANSAC to generate the pose candidates. In the paper we propose two novel minima
One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current s
Background: Primary graft failure (PGF) remains the most common cause of short-term mortality after heart transplantation. The main objective was to develop and validate a risk model for prediction of short-term mortality due to PGF after heart transplantation using the ISHLT Heart Transplant Registry. Methods: We developed a non-linear artificial neural networks (ANN) model to evaluate the associ
