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In this paper, we present two new provable nonce-misuseresistantAEAD modes based on tweakable block ciphers and universalhash functions. These new modes target equipping high-speed applicationswith nonce-misuse-resistant AEAD (MRAE). The first mode, LowLatency Synthetic IV (LLSIV), targets similar performance on single-coreplatforms to SCT-2, while eliminating the bottlenecks that make SCT-2not fu
We investigate the persistance of embedded eigenvalues under perturbations of a certain self-adjoint Schrödinger-type differential operator in L2(R; Rn), with an asymptotically periodic potential. The studied perturbations are small and belong to a certain Banach space with a specified decay rate, in particular, a weighted space of continuous matrix valued functions. Our main result is that the se
Network Data Analytics Function (NWDAF) is a key component in 5G networks, introduced by 3G Partnership Project (3GPP) standards, that leverages machine learning to optimize network performance. The 3GPP standards mandate that mobile network operators should retrain NWDAF models to maintain accuracy. However, the presence of adversarial user equipment (UE) can introduce corrupted data points durin
Ensuring availability is a critical requirement for the Internet of Things (IoT). CIDER, a recovery architecture, and its follow-up scheme, Lazarus, are solutions to address this issue. CIDER introduced a new hardware module, the Authenticated Watchdog Timer (AWDT), to keep IoT devices running in normal mode as long as trusted authenticated tickets are received from a hub. If valid tickets are not
This paper considers the problem of recovering either a low rank matrix or a sparse vector from observations of linear combinations of the vector or matrix elements. Recent methods replace the non-convex regularization with ℓ1 or nuclear norm relaxations. It is well known that this approach recovers near optimal solutions if a so called restricted isometry property (RIP) holds. On the other hand i
This paper presents a novel method for 3D human pose and shape estimation from images with sparse views, using joint points and silhouettes, based on a parametric model. Firstly, the parametric model is fitted to the joint points estimated by deep learning-based human pose estimation. Then, we extract the correspondence between the parametric model of pose fitting and silhouettes in 2D and 3D spac
This study evaluates the applicability of scaled reassigned spectrograms (ReSTS) on ultrasound radio frequency data obtained with a clinical linear array ultrasound transducer. The ReSTS's ability to resolve axially closely spaced objects in a phantom is compared to the classical cross-correlation method with respect to the ability to resolve closely spaced objects as individual reflectors using u
Syftet med projekt, AirBeeSafe, var att öka kunskapen om bin och andra pollinerande insekters exponering för olika växtskyddsmedel i odlingslandskapet. Projektet utfördes i ett samarbete mellan SLU Centrum för kemiska bekämpningsmedel i miljön (CKB) och Biologiska institutionen, Lunds universitet, samt lantbrukare och biodlare. Finansiering gavs av Naturvårdsverket och det strategiska forskningsom
This paper presents a methodology for estimation of physically interpretable building energy performance characteristics such as: heat loss coefficient, azimuth angle dependent solar gain, and diurnal periodicity in heat-demand. The models are demonstrated on a case-study with hourly observations of district-heating connected apartment buildings in Denmark. The weather model inputs are obtained fr
Semantic role labeling has become a key module of many language processing applications. To build an unrestricted semantic role labeler, the first step is to develop a comprehensive proposition bank. However, building such a bank is a costly enterprise, which has only been achieved for a handful of languages. In this paper, we describe a technique to build proposition banks for new languages using
High resolution radio based positioning and tracking is a key enabler for new or improved cellular services. In this work, we are aiming to track user movements with accuracy down to centimeters using standard cellular bandwidths of 20-40 MHz. The goal is achieved by using phase information from the multi-path components (MPCs) of the radio channels. First, an extended Kalman filter (EKF) is used
Video data and the tools for automated analysis have a great potential to be used in road traffic research, particularly road safety. In this project a video dataset is built and made public so that researchers can evaluate their algorithms on it. The dataset focuses on the traffic research applications (data from real research projects) and provides recordings of the traffic scenes, meta-data, ca
In this paper, we describe how we use a named entity disambiguation module to merge entities in a question answering system. The question answering system uses a baseline passage retrieval component that extracts paragraphs from the Swedish version of Wikipedia. The passages are indexed and ranked using the Lucene platform. Prior to the indexing, we carried out a recognition and disambiguation of
Several studies have shown the value of using proximity data to understand the social context of users. To simplify the use of social context in application development we have developed Proximates, a social context engine for mobile phones. It scans nearby Bluetooth peers to determine what devices are in proximity. We map Bluetooth MAC ids to user identities on existing social networks which then
When robots are working in dynamic environments, close to humans lacking extensive knowledge of robotics, there is a strong need to simplify the user interaction and make the system execute as autonomously as possible, as long as it is feasible. For industrial robots working side-by-side with humans in manufacturing industry, AI systems are necessary to lower the demand on programming time and sys
Spectral estimation is an important classical problem that has received considerable attention in the signal processing literature. In this contribution, we propose a novel method for estimating the parameters of sums of complex exponentials embedded in additive noise from regularly or irregularly spaced samples. The method relies on Kronecker's theorem for Hankel operators, which enables us to fo
We consider sequences of points obtained by projecting a given point B=B (0) back and forth between two manifolds and , and give conditions guaranteeing that the sequence converges to a limit . Our motivation is the study of algorithms based on finding the limit of such sequences, which have proved useful in a number of areas. The intersection is typically a set with desirable properties but for w
The association between marital status and generalized trust in other people was investigated. The public health survey in Skane 2008 is a cross-sectional study including 28,198 persons (55% participation rate) aged 18-80 in southern Sweden. Logistic regression models investigated associations between marital status and trust, adjusting for age, country of birth, education, emotional support, inst
