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Cardinality and rank functions are ideal ways of regularizing under-determined linear systems, but optimization of the resulting formulations is made difficult since both these penalties are non-convex and discontinuous. The most common remedy is to instead use the ℓ1- and nuclear norms. While these are convex and can therefore be reliably optimized, they suffer from a shrinking bias that degrades

We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, i.e., frequency estimation. For the basic formulation of the fixed-point algorithm we show that it converges to the solution of a related minimization problem, namely the one obtained by replacing th

The market of connected devices, IoT devices in particular, is hotter than ever. Today, lightweight IoT devices are used in several sectors, such as smart cities, smart homes, healthcare, and the manufacturing industry.IoT solutions help increase productivity by predictive maintenance and resource management in the industry. Devices with voice interfaces are spreading rapidly in the home automatio

This paper addresses the need for secure storage in virtualized services in the cloud. To this purpose, we evaluate the security properties of Intel's Software Guard Extensions (SGX) technology, which provides hardware protection for general applications, for securing virtual Hardware Security Modules (vHSM). In order for the analysis to be comparable with analyses of physical HSMs, the evaluation

A key enabler for Industry 4.0 is Fifth Generation Wireless Specifications (5G), within which network slicing is a promising technique to ensure customized quality of service for specific end-user groups in industrial scenarios. Massive Multiple Input Multiple Output (MIMO) plays a significant role in 5G but network slicing for massive MIMO has not yet been addressed. In this paper, we propose a n

It is well known that load balancing in data centers can lead to unnecessary energy usage if all servers are kept active. Usingdynamic server provisioning, the number of servers that serve requests can be reduced by turning off idle servers and thereby savingenergy. However, such a scheme, usually increases the risk of instability of server queues. In this work, we analyze the trade-offbetween ene

Side-channel attacks on cryptographic algorithms targets the implementation of the algorithm. Information can leak from the implementation in several different ways and, in this paper, electromagnetic radiation from an FPGA is considered. We examine to which extent key information from an AES implementation can be deduced using a low-end oscilloscope. Moreover, we examine how the antenna's distanc

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

Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantities of interest by bounded (or imprecise) probability. Iterative importance sampling can be used to estimate bounds on the quantity of interest by optimizing over the set of priors. A method for iterative importance samp

Extracting speaker-dependent paralinguistic information out of a person's voice, provides an opportunity for adaptive behaviour related to speaker information in speech processing applications. For instance, in audio-based conversational applications, adapting responses to the attributes of the correspondent is an integral part in making the conversations effective. Two speaker attributes that hum

We developed an automatic algorithm with the purpose to assist pathologists to report Gleason score on malignant prostatic adenocarcinoma specimen. In order to detect and classify the cancerous tissue, a deep convolutional neural network that had been pre-trained on a large set of photographic images was used. A specific aim was to support intuitive interaction with the result, to let pathologists

The most used pavement for paved roads in the world is asphalt. It is therefore important that the asphalt is as durable as possible to avoid expensive repairs of the roads. One important factor of the durability of the road is the adherence between the stones and the bitumen that holds the stones together. The affinity is tested by the so called rolling bottle test, where one put stones covered i

In this paper we discuss AI in industrial robotics. In automatic control, computer vision and optimization, ma- chine learning and data mining algorithms are widely used. However, cognition enabling mechanisms, such as high-level logic and symbolic reasoning, are still limited. This is not due to the lack of available algorithms, rather the bottleneck is knowledge representation, acquisition and t

The Augustan poet Ovid (43 BC – AD 17/18) is mentioned by Seneca the elder for his oratorical skills as a school boy. If we are to believe Seneca, Ovid excelled to such a degree that he even surpassed his teachers. He took special interest in exercises concerning ethos, and is said to have transferred what he learned into his own verse. The influence from rhetorical training is indeed visible in O

An ethopoeia is an imagined speech assigned to a certain character. As a rhetorical exercise it is known from the progymnasmata of Theon, Hermogenes, Aphthonius and Nicolaus as well as contemporary rhetorical theorists. The purpose of the exercise was to teach the student the appropriate use of ethos and pathos for the assigned character. The paper will present the function of the ethopoeia as a p

Organizations and individuals maintain and use an ever increasing amount of computer systems, either deployed locally, or in the cloud.These systems often store and handle vast amounts of data, some of which is sensitive and should be kept private.Regardless of where the data is located, there is a need to prevent data from falling into the wrong hands.To this end, this dissertation presents contr

Vehicle traffic management is becoming more complex due to increased traffic density in cities. Novel solutions are necessary for emergency vehicles, which despite growing congestion must be able to quickly reach their destination. Emergency vehicles are usually equipped with transmitters to control the traffic lights on their path and warn other vehicles with sirens. Transmitters are operated man

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

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