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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 allows calculating minimum safe inter-vehicular distances for arbitrary ego vehicle control policies. We use this framework to enhance the Responsibility-Sensitive Safety (RSS) model and models based on it,
This issue marks the start of my term as department editor for the “Requirements” column. I very much look forward to exploring contemporary aspects of requirements and requirements engineering (RE) in the coming years! As an institute researcher with RISE, I primarily work in strictly regulated domains, in which requirements are cornerstones in the development activities. Please check my introduc
Memories may integrate elements experienced in different events. For instance, meeting a woman leaving her house, and later meeting another woman entering the same house, may allow us to infer that the two women live together. Such memory representations are thought to rely on integrative encoding mechanisms, allowing us to make inferences about the world and generalize knowledge to entirely new s
ObjectivesThe formation of episodic memories is critically determined by how we visually sample the world over time via sequences of eye movements. Nonetheless, in the neuroscience of human memory, memory encoding has almost exclusively been studied in experimental paradigms where the study material is presented in a single fixed location on the screen, and where eye movements are treated as artif
Episodic memory enables mental time travel, allowing us to relive specific, personally experienced events tied in time and place. This feat of human memory is considered to be dependent on the reinstatement of the cortical patterns that were active at the time of encoding. A growing body of recent literature has provided support for this idea by showing that retrieval success co-varies with the ne
Cellular-based localization and sensing pave the way for a variety ofapplications across various domains, ranging from autonomous driv-ing to emergency care and intelligent traffic management. Althoughtraditional methods have been effective, they still face challenges such as therequirement for highly accurate models and the inherent complexity of thealgorithms. This thesis explores the potential
Iterative algorithms are becoming more common in modern systems. This ranges from algorithms for communicationsystems receivers, machine learning, group testing, and various computation problems. The success of thesealgorithms lies in the ability to simplify computation by breaking down the system into components and exchangingmessages on graphs. The graph has the components as nodes and connectio
With the increase in the number of antennas at base stations (BSs), centralized multi-antenna architectures have encountered scalability problems from excessive interconnection bandwidth to the central processing unit (CPU), as well as increased processing complexity. Thus, research efforts have been directed towards finding decentralized receiver architectures where a part of the processing is pe
Background: Participants in epidemiological cohorts may not be representative of the full invited population, limiting the generalizability of prevalence and incidence estimates. We propose that this problem can be remedied by exploiting data on baseline participants who refused to participate in a re-examination, as such participants may be more similar to baseline non-participants than what base
We study stochastic interaction network models whereby a finite population of agents, identified with the nodes of a graph, update their states in response to pairwise interactions with their neighbors as well as spontaneous mutations. These include the main epidemic models, such as the Susceptible-Infected -Susceptible, the Susceptible-Infected-Recovered, and the Susceptible-Infected-Recovered-Su
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
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
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
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
Field-theory simulation by the complex Langevin method offers an alternative to conventional sampling techniques for exploring the forces driving biomolecular liquid–liquid phase separation. Such simulations have recently been used to study several polyampholyte systems. Here, we formulate a field theory corresponding to the hydrophobic/polar (HP) lattice protein model, with finite same-site repul
We study optimal information provision in transportation networks when users are strategic and the network state is uncertain. An omniscient planner observes the network state and discloses information to the users with the goal of minimizing the expected travel time at the user equilibrium. Public signal policies, including full-information disclosure, are known to be inefficient in achieving opt
As a counterweight to depersonalization, dementia care settings collect personal biographies, life stories, when residents move in. In Sweden, life story work has established itself as an indicator when measuring quality in dementia care. To facilitate the writing of life stories, care settings use a variety of life story templates, with a set of questions to be filled in about the care recipient.
Software development is a complex activity that needs a lot of tool assistance. Over the years there has been a lot of effort put into development of automated assistance to help with activities such as detection of issues via program analysis, or refactoring of code. Recently, the landscape of developer tool assistance is being disrupted with the entry of AI tools, such as Copilot and ChatGPT, po
