Swedish Defence Research Agency

About: Swedish Defence Research Agency is a government organization based out in Stockholm, Sweden. It is known for research contribution in the topics: Radar & Synthetic aperture radar. The organization has 1413 authors who have published 2731 publications receiving 56083 citations. The organization is also known as: Totalförsvarets forskningsinstitut.

Conflicting Reasons in the Small‐Improvement Argument

Abstract: Essay I develops a new framework for preference relations, that makes further preference relations beyond the trichotomy of preference, dispreference and indifference conceptually possible. The new framework models relations in terms of swaps, which are conceived of as transfers from one alternative state to another. With this new preference framework the essay presents a fitting-attitude analysis of new value relations that avoids some problems of earlier proposals. Essay II examines the small-improvement argument that is usually considered the most powerful argument against comparability, that is, the view that for any two alternatives an agent is rationally required to either prefer one of the alternatives to the other or be indifferent between them. The essay argues that while there might be reasons to believe each of the premises in the small-improvement argument, there is a conflict between these reasons. The conflict is such that we are not provided with a reason to believe the conjunction of the premises. Essay III develops a new measure of freedom of choice based on the proposal that a set offers more freedom of choice than another if, and only if, the expected degree of dissimilarity between a random alternative from the set of possible alternatives and the most similar offered alternative in the set is smaller. Furthermore, a version of this measure is developed that is able to take into account the values of the possible options.

Shooter localization in wireless sensor networks

Abstract: Shooter localization is considered in a wireless network of microphones. Both the acoustic muzzle blast (MB) from the gunfire and the ballistic shock wave (SW) from the bullet can be detected by the microphones and are considered as measurements. The MB measurements give rise to a standard sensor network problem, similar to time difference of arrivals in cellular phone networks, and the localization accuracy is good provided that the sensors are well synchronized compared to the MB detection accuracy. The detection times of the SW depend on both shooter position and aiming angle, and we demonstrate that estimation based on these measurements can potentially also reveal the shooting direction beside the position, but again this requires good synchronization. We propose to base the estimation on the time difference of MB and SW at each sensor, which becomes insensitive to synchronization. Cramer-Rao lower bound analysis indicates how a lower bound of the root mean square error depends on the synchronization error for MB and MB-SW differences, respectively. Results from field trials with different type of ammunition show excellent accuracy of the proposed method for both the position and the aiming angle of the shooter.

Geometric integration in Born-Oppenheimer molecular dynamics

Abstract: Geometric integration schemes for extended Lagrangian self-consistent Born-Oppenheimer molecular dynamics, including a weak dissipation to remove numerical noise, are developed and analyzed. The extended Lagrangian framework enables the geometric integration of both the nuclear and electronic degrees of freedom. This provides highly efficient simulations that are stable and energy conserving even under incomplete and approximate self-consistent field (SCF) convergence. We investigate three different geometric integration schemes: (1) regular time reversible Verlet, (2) second order optimal symplectic, and (3) third order optimal symplectic. We look at energy conservation, accuracy, and stability as a function of dissipation, integration time step, and SCF convergence. We find that the inclusion of dissipation in the symplectic integration methods gives an efficient damping of numerical noise or perturbations that otherwise may accumulate from finite arithmetics in a perfect reversible dynamics.

Representation and Recognition of Uncertain Enemy Policies Using Statistical Models

Abstract: To incorporate new technical advances into military domain and make those processes more efficient in accuracy, time and cost, a new concept of Network Centric Warfare has been introduced in the US military forces. In Sweden a similar concept has been studied under the name Network Based Defence (NBD). Here we present one of the methodologies, called tactical plan recognition that is aimed to support NBD in future. Advances in sensor technology and modelling produce large sets of data for decision makers. To achieve decision superiority, decision makers have to act agile with proper, adequate and relevant information (data aggregates) available. Information fusion is a process aimed to support decision makers’ situation awareness. This involves a process of combining data and information from disparate sources with prior information or knowledge to obtain an improved state estimate about an agent or phenomena. Plan recognition is the term given to the process of inferring an agent’s intentions from a set of actions and is intended to support decision making. The aim of this work has been to introduce a methodology where prior (empirical) knowledge (e.g. behaviour, environment and organization) is represented and combined with sensor data to recognize plans/behaviours of an agent or group of agents. We call this methodology multi-agent plan recognition. It includes knowledge representation as well as imprecise and statistical inference issues. Successful plan recognition in large scale systems is heavily dependent on the data that is supplied. Therefore we introduce a bridge between the plan recognition and sensor management where results of our plan recognition are reused to the control of, give focus of attention to, the sensors that are supposed to acquire most important/relevant information. Here we combine different theoretical methods (Bayesian Networks, Unified Modeling Language and Plan Recognition) and apply them for tactical military situations for ground forces. The results achieved from several proof-ofconcept models show that it is possible to model and recognize behaviour of tank units.

Functional analyses of pilin-like proteins from Francisella tularensis: complementation of type IV pilus phenotypes in Neisseria gonorrhoeae.

Abstract: Accumulating evidence from a number of studies strongly suggests that proteins orthologous to those involved in type IV pili (Tfp) assembly and function are required for Francisella pathogenicity. However, the molecular mechanisms by which the components exert their influence on virulence remain poorly understood. Owing to the conservation and promiscuity of Tfp biogenesis machineries, expression of Tfp pilins in heterologous species has been used successfully to analyse organelle structure–function relationships. In this study we expressed a number of Francisella pilin genes in the Tfp-expressing pathogen Neisseria gonorrhoeae lacking its endogenous pilin subunit. Two gene products, the orthologous PilA proteins from Francisella tularensis subspecies tularensis and novicida, were capable of restoring the expression of Tfp-like appendages that were shown to be dependent upon the neisserial Tfp biogenesis machinery for surface localization. Expression of Francisella PilA pilins also partially restored competence for natural transformation in N. gonorrhoeae. This phenotype was not complemented by expression of the PulG and XcpT proteins, which are equivalent components of the related type II protein secretion system. Taken together, these findings provide compelling, although indirect, evidence of the potential for Francisella PilA proteins to express functional Tfp.