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Formal models for the safety validation of autonomous vehicles have become increasingly important. To this end, we present a safety framework for longitudinal automated driving. This framework enables the calculation of minimum safe inter-vehicular distances for arbitrary ego vehicle control policies in a computationally efficient manner. We use this framework to enhance and generalize the Respons
We recently proposed a quantitative group testing (GT) scheme with low-complexity peeling decoding based on low-density parity-check (LDPC) codes. Based on finite length simulations and a density evolution analysis we were able to demonstrate that simple (dv,dc)-regular LDPC codes can be more efficient for GT than existing generalized LDPC (GLDPC) code constructions based on BCH component codes. E
Future wireless systems are envisioned to be able to deliver ultra-reliable and low-latency communication.The third generation partner project (3GPP) has identified three different usage scenarios such as enhanced mobile broadband, massive machine-type communication, and ultra-reliable low latency communication.In each of those scenarios, several services and applications can be implemented, e.g.
Microstrip patch antennas have become essential in modern communication systems due to their compact size and ease of fabrication. However, their performance is often constrained by narrow bandwidth, low radiation efficiency, and low gain, especially in miniaturized designs. The performance limits of microstrip patch antennas are helpful in understanding and overcoming these challenges. These perf
To have a successful career in engineering, students need both technical engineering skills and non-technical engineering skills (NTES) in the transition to professional life. To address NTES in engineering education, the concept of six compulsory ‘engineering days’ were introduced in two engineering programs at the undergraduate level. The importance of different NTES for industry has been evalua
The success in the adoption of autonomous vehicles is dependent on their ability to solve rarely occurring safety-critical corner cases. Vehicular communications (V2X) aim at improving safety and efficiency of autonomous driving by adding the capability of explicit inter-vehicular information exchange. We argue that V2X enables another important function, namely the support of ethical driving deci
Background: Data quickly emerges as a core driver of businesses across the worlddue to rapidly expanding use in different areas, such as Machine Learning. In orderfor the data-related organizational operations to be efficient, the topic of data shar-ing has to be explored. This thesis focuses on understanding inter-organizationaldata sharing by exploring practices and challenges that are present w
Purpose: The survival rate of breast cancer for women in low- and middle-income countries is poor compared with that in high-income countries. Point-of-care ultrasound (POCUS) combined with deep learning could potentially be a suitable solution enabling early detection of breast cancer. We aim to improve a classification network dedicated to classifying POCUS images by comparing different techniqu
Static code checkers are tools that help software engineers by automatically finding defects without executing the programs. These tools contain a set of detectors that rely on static program analyses to find common programming defects or to enforce coding guidelines.While existing code checker frameworks package a rich collection of detectors, aimed at common bug defects, the effort to adapt thes
Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function's optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective
Recent work reported that simple Bayesian optimization methods perform well for high-dimensional real-world tasks, seemingly contradicting prior work and tribal knowledge. This paper investigates the 'why'. We identify fundamental challenges that arise in high-dimensional Bayesian optimization and explain why recent methods succeed. Our analysis shows that vanishing gradients caused by Gaussian pr
This study presents a measurement campaign with an ultra-large-scale antenna array in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) outdoor scenarios. Measurements were conducted at a center frequency of 15 GHz with a bandwidth of 4 GHz. A virtual 40×40 planar antenna array, formed by moving a vertically-polarized bi-conical omni-directional antenna (ODA) along regularly spaced grids, was
Clog is a declarative language for describing static code checkers for C. Clog is a dialect of Datalog and adds syntactic pattern matching over the C language. We have built Clog using the MetaDL framework and the Clang C compiler frontend. The MetaDL framework supports Datalog evaluation and syntactic patterns, while the Clang frontend provides AST facts and an AST matching mechanism.We provide t
Many software language tools use declarative domain-specific languages (DDSLs) to implement parts of their functionality, such as context-free grammars for parsing or inference rules for type analysis. For interoperability and ease of use, DDSLs often rely on embedded general-purpose language (GPL) code fragments, as in the semantic actions of parser specifications, but require that these GPL frag
We propose and analyze a novel scheme based on LDPC codes for quantitative group testing. The key underlying idea is to augment the bipartite graph by introducing hidden non-binary variables to strengthen the message-passing decoder. This is achieved by grouping items into bundles of size q within the test matrix, while keeping the testing procedure unaffected. The decoder, inspired by some works
Indoor sensing is challenging because of the multi-bounce effect, spherical wavefront, and spatial nonstationarity (SNS) of the near-field effect. This paper addresses radio-based environment sensing considering these issues. Specifically, graph theory (GT) is used to model the multi-bounce propagation of the near field. In this manner, indoor reflectors/scatterers are modeled as vertices in a pro
The performance of wireless communications at sea are often limited by fading caused by reflections at the sea surface. The reliability could potentially be improved by employing multiple antennas. We have conducted massive multiple-input multiple-output (MIMO) measurements at sea in order to evaluate the performance. The measurements were conducted at 5.6 GHz with 64 dual-polarized antennas, whic
Bayesian optimization is a widely used method for optimizing expensive black-box functions, with Expected Improvement being one of the most commonly used acquisition functions. In contrast, information-theoretic acquisition functions aim to reduce uncertainty about the function’s optimum and are often considered fundamentally distinct from EI. In this work, we challenge this prevailing perspective
A broadband high gain metasurface-based Fabry–Perot resonant cavity antenna (FPRCA) for polarization reconfigurable is proposed in this article. The antenna features a microstrip source antenna with a single-layer 2 × 2 circular patch metasurface, a ground plane, and a double-layer partially reflective surface (PRS), along with four resistors and two diodes. Characteristic mode analysis (CMA) is p
