An experiment on the role of graphical elements in architecture visualization

The evolution and maintenance of large-scale software systems requires first an understanding of its architecture before delving into lower-level details. Tools facilitating the architecture comprehension tasks by visualization provide different sets of configurable, graphical elements to present information to their users. We conducted a controlled experiment that exemplifies the critical role of such graphical elements when aiming at understanding the architecture. In our setting, a different configuration of graphical elements had significant influence on program comprehension tasks. In particular, a 63% gain in effectiveness in architectural analysis tasks was achieved simply by changing the configuration of the graphical elements of the same tool. Based on the results, we claim that significant effort should be spent on the configuration of architecture visualization tools and that configurability should be a requirement for such tools.

Evolution strategies with cumulative step length adaptation on the noisy parabolic ridge

This paper presents an analysis of the performance of the (μ/μ,λ)-ES with isotropically distributed mutations and cumulative step length adaptation on the noisy parabolic ridge. Several forms of dependency of the noise strength on the distance from the ridge axis are considered. Closed form expressions are derived that describe the mutation strength and the progress rate of the strategy in high-dimensional search spaces. It is seen that as for the sphere model, larger levels of noise present lead to cumulative step length adaptation generating increasingly inadequate mutation strengths, and that the problem can be ameliorated to some degree by working with larger populations.     

Die Mifare-Attacke

Zusammenfassung  Eine Kryptoanalyse des verbreiteten Mifare-Chips, der in ca. 85% aller kontaktlosen Chipkarten zum Einsatz kommt, wurde erstmalig auf dem CCC-Jahreskongress am 28.12.2007 vorgestellt. Inzwischen wurden weitere Details bekannt — und der Angriff erheblich verbessert. Mitte April 2008 stellten Forscher der Radboud Universiteit Nijmegen einen Kurzfilm in You-Tube ein, in dem sie den erfolgreichen Angriff auf eine Campus-Zugangskarte zeigen. Dirk Fox Gesch?ftsführer der Secorvo Security Consulting GmbH und Herausgeber der DuD.     

Local statistics of retinal optic flow for self-motion through natural sceneries

Image analysis in the visual system is well adapted to the statistics of natural scenes. Investigations of natural image statistics have so far mainly focused on static features. The present study is dedicated to the measurement and the analysis of the statistics of optic flow generated on the retina during locomotion through natural environments. Natural locomotion includes bouncing and swaying of the head and eye movement reflexes that stabilize gaze onto interesting objects in the scene while walking. We investigate the dependencies of the local statistics of optic flow on the depth structure of the natural environment and on the ego-motion parameters. To measure these dependencies we estimate the mutual information between correlated data sets. We analyze the results with respect to the variation of the dependencies over the visual field, since the visual motions in the optic flow vary depending on visual field position. We find that retinal flow direction and retinal speed show only minor statistical interdependencies. Retinal speed is statistically tightly connected to the depth structure of the scene. Retinal flow direction is statistically mostly driven by the relation between the direction of gaze and the direction of ego-motion. These dependencies differ at different visual field positions such that certain areas of the visual field provide more information about ego-motion and other areas provide more information about depth. The statistical properties of natural optic flow may be used to tune the performance of artificial vision systems based on human imitating behavior, and may be useful for analyzing properties of natural vision systems.     

Autonomic information flow improves prognostic impact of task force HRV monitoring

Heart rate variability (HRV) represents the cardiovascular control mediated by the autonomic nervous system and other mechanisms. In the established task force HRV monitoring different cardiovascular control mechanisms can approximately be identified at typical frequencies of heart rate oscillations by power spectral analysis. HRV measures assessing complex and fractal behavior partly improved clinical risk stratification. However, their relationship to (patho-)physiology is not sufficiently explored. Objective of the present work is the introduction of complexity measures of different physiologically relevant time scales. This is achieved by a new concept of the autonomic information flow (AIF) analysis which was designed according to task force HRV. First applications show that different time scales of AIF improve the risk stratification of patients with multiple organ dysfunction syndrome and cardiac arrest patients in comparison to standard HRV. Each group's significant time scales correspond to their respective pathomechanisms.     

Meetings and meeting modeling in smart environments

In this paper we survey our research on smart meeting rooms and its relevance for augmented reality meeting support and virtual reality generation of meetings in real time or off-line. The research reported here forms part of the European 5th and 6th framework programme projects multi-modal meeting manager (M4) and augmented multi-party interaction (AMI). Both projects aim at building a smart meeting environment that is able to collect multimodal captures of the activities and discussions in a meeting room, with the aim to use this information as input to tools that allow real-time support, browsing, retrieval and summarization of meetings. Our aim is to research (semantic) representations of what takes place during meetings in order to allow generation, e.g. in virtual reality, of meeting activities (discussions, presentations, voting, etc.). Being able to do so also allows us to look at tools that provide support during a meeting and at tools that allow those not able to be physically present during a meeting to take part in a virtual way. This may lead to situations where the differences between real meeting participants, human-controlled virtual participants and (semi-) autonomous virtual participants disappear.

Optimum tracking with evolution strategies

Evolutionary algorithms are frequently applied to dynamic optimization problems in which the objective varies with time. It is desirable to gain an improved understanding of the influence of different genetic operators and of the parameters of a strategy on its tracking performance. An approach that has proven useful in the past is to mathematically analyze the strategy's behavior in simple, idealized environments. The present paper investigates the performance of a multiparent evolution strategy that employs cumulative step length adaptation for an optimization task in which the target moves linearly with uniform speed. Scaling laws that quite accurately describe the behavior of the strategy and that greatly contribute to its understanding are derived. It is shown that in contrast to previously obtained results for a randomly moving target, cumulative step length adaptation fails to achieve optimal step lengths if the target moves in a linear fashion. Implications for the choice of population size parameters are discussed.     

Machine learning for vessel trajectories using compression,alignments and domain knowledge

In this paper we present a machine learning framework to analyze moving object trajectories from maritime vessels. Within this framework we perform the tasks of clustering, classification and outlier detection with vessel trajectory data. First, we apply a piecewise linear segmentation method to the trajectories to compress them. We adapt an existing technique to better retain stop and move information and show the better performance of our method with experimental results. Second, we use a similarity based approach to perform the clustering, classification and outlier detection tasks using kernel methods. We present experiments that investigate different alignment kernels and the effect of piecewise linear segmentation in the three different tasks. The experimental results show that compression does not negatively impact task performance and greatly reduces computation time for the alignment kernels. Finally, the alignment kernels allow for easy integration of geographical domain knowledge. In experiments we show that this added domain knowledge enhances performance in the clustering and classification tasks.     

Influence of particle elasticity in shear testers

Two dimensional simulations of non-cohesive granular matter in a biaxial shear tester are discussed. The effect of particle elasticity on the mechanical behavior is investigated using two complementary distinct element methods (DEM): Soft particle molecular dynamics simulations (Particle Flow Code, PFC) for elastic particles and contact dynamics simulations (CD) for the limit of perfectly rigid particles. As soon as the system dilates to form shear bands, it relaxes the elastic strains so that one finds the same stresses for rigid respectively elastic particles in steady state flow. The principal stresses in steady state flow are determined. They are proportional to each other, giving rise to an effective macroscopic friction coefficient which is about 10% smaller than the microscopic friction coefficient between the grains.     

Design mechanisms and constraints

This paper describes a model of design, which takes a different perspective in that it emphasises mechanisms and constraints. The model accommodates design-related activities from the enterprise level through to activities of individuals (e.g. decision-making processes), and provides a holistic treatment of existing design methods. It is suggested that the output of a design stage is not so much the input to the next, as the provider of constraints. Consequently, the creative component of design is not concentrated in one task, with the others being technician tasks: instead each of the tasks augments the design in a creative way. A degree of commonality was observed across different domains and stages of design, which leads to the proposal of a generic design activity (GDA), that can be used in diverse design situations. Sub-activities within the GDA were identified as the generation of candidate solutions, solution assessment, solution selection, implementation, and retrieval of design intent. It is suggested that one of the limitations of many design tools, especially artificial intelligence, is the reliance on on complete problem and constraint specification. In real situations, designers have to determine constraints from incomplete and qualitative specifications, using subjective processes. Furthermore, they subsequently have to negotiate with others for the relaxation of constraints, as the design space may be over-constrained. This negotiation involves interaction with others, and adds the organisational behaviour factors to the design process. Decision-making during design needs to be able to accommodate multiple viewpoints, cope with uncertainty of analysis (incompleteness of knowledge), propagate uncertain variables, and accommodate varying degrees of information abstraction. Other areas of design that may benefit for additional research are identified. This work was performed at the Department of Mechanical Engineering, University of Canterbury, New Zealand. Submitted to Research in Engineering Design