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.     

The clinical assessment of cancer tests: a statistical approach to the prediction of "false positive" rates from controls

As the sensitivity of the new in vitro cancer detection techniques increases, a larger number of "false positive" results can be expected from control populations apparently free from malignant disease at the time of the test. An attempt is made to predict the number of unexplained positives, together with the expected age and sex distribution, using published cancer registration statistics. The predicted numbers are compared with the observed numbers of unexplained positives in two clinical trials of the MEM test.     

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.     

Effect of tinidazole, metronidazole and nitrofurazone on nucleic acid synthesis in Clostridium bifermentans

Coplanar lines of different orientations rotating in depth and viewed in parallel projection may appear to rotate in different directions and reverse independently of each other, or they may appear coplanar and all reverse together. The frequency of the latter "grouped" appearance for lines with an orientation range of 30 degrees was a function of the number of lines in a given space. Grouping was greater for lines converging to an implicit vanishing point and for lines with collinear edges regardless of their orientations. Line length, and by inference, interline separation also had effect of the nature of the response.     

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     

Integrating a flexible anthropomorphic, robot hand into the control, system of a humanoid robot

This article presents the approaches taken to integrate a novel anthropomorphic robot hand into a humanoid robot. The requisites enabling such a robot hand to use everyday objects in an environment built for humans are presented. Starting from a design that resembles the human hand regarding size and movability of the mechatronical system, a low-level control system is shown providing reliable and stable controllers for single joint angles and torques, entire fingers and several coordinated fingers. Further on, the high-level control system connecting the low-level control system with the rest of the humanoid robot is presented. It provides grasp skills to the superior robot control system, coordinates movements of hand and arm and determines grasp patterns, depending on the object to grasp and the task to execute. Finally some preliminary results of the system, which is currently tested in simulations, will be presented.     

The Conditional Probability Density Function for a Reflected Brownian Motion

Models in economics and other fields often require a restricted Brownian motion because frequently implicit or explicit barriers restrict the domain. This paper contributes to the literature on reflected Brownian motion by deriving its conditional density function as a closed-form expression that consists of infinite sums of Gaussian densities. This solution is compared with an alternative, trigonometric expression derived earlier. Numerical analyses reveal that convergence properties of the expression derived in this paper are superior to those of the alternative representation for most practically relevant set-ups. Despite the complex appearance of the density formula, its use only requires fractions of a second on simple desktop computers such that, next to the theoretical appeal, also practicability is guaranteed.