A subexponential bound for linear programming

We present a simple randomized algorithm which solves linear programs withn constraints andd variables in expected $$\min \{ O(d^2 2^d n),e^{2\sqrt {dIn({n \mathord{\left/ {\vphantom {n {\sqrt d }}} \right. \kern-\nulldelimiterspace} {\sqrt d }})} + O(\sqrt d + Inn)} \}$$ time in the unit cost model (where we count the number of arithmetic operations on the numbers in the input); to be precise, the algorithm computes the lexicographically smallest nonnegative point satisfyingn given linear inequalities ind variables. The expectation is over the internal randomizations performed by the algorithm, and holds for any input. In conjunction with Clarkson's linear programming algorithm, this gives an expected bound of $$O(d^2 n + e^{O(\sqrt {dInd} )} ).$$ The algorithm is presented in an abstract framework, which facilitates its application to several other related problems like computing the smallest enclosing ball (smallest volume enclosing ellipsoid) ofn points ind-space, computing the distance of twon-vertex (orn-facet) polytopes ind-space, and others. The subexponential running time can also be established for some of these problems (this relies on some recent results due to Gärtner).     

Analysis of multi-agent activity using petri nets

This paper presents the use of place/transition petri nets (PNs) for the recognition and evaluation of complex multi-agent activities. The PNs were built automatically from the activity templates that are routinely used by experts to encode domain-specific knowledge. The PNs were built in such a way that they encoded the complex temporal relations between the individual activity actions. We extended the original PN formalism to handle the propagation of evidence using net tokens. The evaluation of the spatial and temporal properties of the actions was carried out using trajectory-based action detectors and probabilistic models of the action durations. The presented approach was evaluated using several examples of real basketball activities. The obtained experimental results suggest that this approach can be used to determine the type of activity that a team has performed as well as the stage at which the activity ended.     

Multiple spatial sounds in hierarchical menu navigation for visually impaired computer users

This paper describes a user study on the benefits and drawbacks of simultaneous spatial sounds in auditory interfaces for visually impaired and blind computer users. Two different auditory interfaces in spatial and non-spatial condition were proposed to represent the hierarchical menu structure of a simple word processing application. In the horizontal interface, the sound sources or the menu items were located in the horizontal plane on a virtual ring surrounding the user’s head, while the sound sources in the vertical interface were aligned one above the other in front of the user. In the vertical interface, the central pitch of the sound sources at different elevations was changed in order to improve the otherwise relatively low localization performance in the vertical dimension. The interaction with the interfaces was based on a standard computer keyboard for input and a pair of studio headphones for output. Twelve blind or visually impaired test subjects were asked to perform ten different word processing tasks within four experiment conditions. Task completion times, navigation performance, overall satisfaction and cognitive workload were evaluated. The initial hypothesis, i.e. that the spatial auditory interfaces with multiple simultaneous sounds should prove to be faster and more efficient than non-spatial ones, was not confirmed. On the contrary—spatial auditory interfaces proved to be significantly slower due to the high cognitive workload and temporal demand. The majority of users did in fact finish tasks with less navigation and key pressing; however, they required much more time. They reported the spatial auditory interfaces to be hard to use for a longer period of time due to the high temporal and mental demand, especially with regards to the comprehension of multiple simultaneous sounds. The comparison between the horizontal and vertical interface showed no significant differences between the two. It is important to point out that all participants were novice users of the system; therefore it is possible that the overall performance could change with a more extensive use of the interfaces and an increased number of trials or experiments sets. Our interviews with visually impaired and blind computer users showed that they are used to sharing their auditory channel in order to perform multiple simultaneous tasks such as listening to the radio, talking to somebody, using the computer, etc. As the perception of multiple simultaneous sounds requires the entire capacity of the auditory channel and total concentration of the listener, it does therefore not enable such multitasking.     

Nodes on ropes: a comprehensive data and control flow for steering ensemble simulations

Flood disasters are the most common natural risk and tremendous efforts are spent to improve their simulation and management. However, simulation-based investigation of actions that can be taken in case of flood emergencies is rarely done. This is in part due to the lack of a comprehensive framework which integrates and facilitates these efforts. In this paper, we tackle several problems which are related to steering a flood simulation. One issue is related to uncertainty. We need to account for uncertain knowledge about the environment, such as levee-breach locations. Furthermore, the steering process has to reveal how these uncertainties in the boundary conditions affect the confidence in the simulation outcome. Another important problem is that the simulation setup is often hidden in a black-box. We expose system internals and show that simulation steering can be comprehensible at the same time. This is important because the domain expert needs to be able to modify the simulation setup in order to include local knowledge and experience. In the proposed solution, users steer parameter studies through the World Lines interface to account for input uncertainties. The transport of steering information to the underlying data-flow components is handled by a novel meta-flow. The meta-flow is an extension to a standard data-flow network, comprising additional nodes and ropes to abstract parameter control. The meta-flow has a visual representation to inform the user about which control operations happen. Finally, we present the idea to use the data-flow diagram itself for visualizing steering information and simulation results. We discuss a case-study in collaboration with a domain expert who proposes different actions to protect a virtual city from imminent flooding. The key to choosing the best response strategy is the ability to compare different regions of the parameter space while retaining an understanding of what is happening inside the data-flow system.     

Extending applications using an advanced approach to DLL injection and API hooking

When programmers need to modify third‐party applications, they frequently do not have access to their source code. In such cases, DLL injection and API hooking are techniques that can be used to modify applications without intervening into their source code. The commonly used varieties of injection and hooking approaches have many practical limitations: they are inconvenient for a programmer to implement, do not work reliably in conjunction with all applications and with certain low‐level machine instructions. In this paper we present two novel approaches to DLL injection and API hooking, which we call Debugger‐aided DLL injection and Single Instruction Hooking. Our approaches overcome the limitations of the state‐of‐the art approaches. Despite incurring greater execution times, our approach allows extending of the applications in situations where the comparable approaches fail. As such, it has a notable practical value for beneficial practical applications of injection and hooking approaches, which are present in malware detection programs and computer security tools. Copyright © 2010 John Wiley & Sons, Ltd.     

Multi-scale computational model for failure analysis of metal frames that includes softening and local buckling

In this work we present a new modelling paradigm for computing the complete failure of metal frames by combining the stress-resultant beam model and the shell model. The shell model is used to compute the material parameters that are needed by an inelastic stress-resultant beam model; therefore, we consider the shell model as the meso-scale model and the beam model as the macro-scale model. The shell model takes into account elastoplasticity with strain-hardening and strain-softening, as well as geometrical nonlinearity (including local buckling of a part of a beam). By using results of the shell model, the stress-resultant inelastic beam model is derived that takes into account elastoplasticity with hardening, as well as softening effects (of material and geometric type). The beam softening effects are numerically modelled in a localized failure point by using beam finite element with embedded discontinuity. The original feature of the proposed multi-scale (i.e. shell-beam) computational model is its ability to incorporate both material and geometrical instability contributions into the stress-resultant beam model softening response. Several representative numerical simulations are presented to illustrate a very satisfying performance of the proposed approach.     

Computing median and antimedian sets in median graphs

The median (antimedian) set of a profile π=(u ₁,…,u _k ) of vertices of a graph G is the set of vertices x that minimize (maximize) the remoteness ∑ _i d(x,u _i ). Two algorithms for median graphs G of complexity O(n idim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes.     

Explanation and reliability of prediction models: the case of breast cancer recurrence

In this paper, we describe the first practical application of two methods, which bridge the gap between the non-expert user and machine learning models. The first is a method for explaining classifiers’ predictions, which provides the user with additional information about the decision-making process of a classifier. The second is a reliability estimation methodology for regression predictions, which helps the users to decide to what extent to trust a particular prediction. Both methods are successfully applied to a novel breast cancer recurrence prediction data set and the results are evaluated by expert oncologists.