Maximum entropy models and subjective interestingness: an application to tiles in binary databases

Recent research has highlighted the practical benefits of subjective interestingness measures, which quantify the novelty or unexpectedness of a pattern when contrasted with any prior information of the data miner (Silberschatz and Tuzhilin, Proceedings of the 1st ACM SIGKDD international conference on Knowledge discovery and data mining (KDD95), 1995; Geng and Hamilton, ACM Comput Surv 38(3):9, 2006). A key challenge here is the formalization of this prior information in a way that lends itself to the definition of a subjective interestingness measure that is both meaningful and practical. In this paper, we outline a general strategy of how this could be achieved, before working out the details for a use case that is important in its own right. Our general strategy is based on considering prior information as constraints on a probabilistic model representing the uncertainty about the data. More specifically, we represent the prior information by the maximum entropy (MaxEnt) distribution subject to these constraints. We briefly outline various measures that could subsequently be used to contrast patterns with this MaxEnt model, thus quantifying their subjective interestingness. We demonstrate this strategy for rectangular databases with knowledge of the row and column sums. This situation has been considered before using computation intensive approaches based on swap randomizations, allowing for the computation of empirical p-values as interestingness measures (Gionis et al., ACM Trans Knowl Discov Data 1(3):14, 2007). We show how the MaxEnt model can be computed remarkably efficiently in this situation, and how it can be used for the same purpose as swap randomizations but computationally more efficiently. More importantly, being an explicitly represented distribution, the MaxEnt model can additionally be used to define analytically computable interestingness measures, as we demonstrate for tiles (Geerts et al., Proceedings of the 7th international conference on Discovery science (DS04), 2004) in binary databases.     

Smooth velocity approximation for constrained systems in real-time simulation

The rapidly increasing complexity of multi-body system models in applications like vehicle dynamics, robotics and bio-mechanics requires qualitative new solution methods to slash computing times for the dynamical simulation.     

Forward dynamical analysis of flexible multibody systems using system-level model reduction

Fast simulation (e.g., real-time) of flexible multibody systems is typically restricted by the presence of both differential and algebraic equations in the model equations, and the number of degrees of freedom required to accurately model flexibility. Model reduction techniques can alleviate the problem, although the classically used body-level model reduction and general-purpose system-level techniques do not eliminate the algebraic equations and do not necessarily result in optimal dimension reduction. In this research, Global Modal Parametrization, a model reduction technique for flexible multibody systems is further developed to speed up simulation of flexible multibody systems. The reduction of the model is achieved by projection on a curvilinear subspace instead of the classically used fixed vector space, requiring significantly less degrees of freedom to represent the system dynamics with the same level of accuracy. The numerical experiment in this paper illustrates previously unexposed sources of approximation error: (1) the rigid body motion is computed in a forward dynamical analysis resulting in a small divergence of the rigid body motion, and (2) the errors resulting from the transformation from the modal degrees of freedom of the reduced model back to the original degrees of freedom. The effect of the configuration space discretization coarseness on the different approximation error sources is investigated. The trade-offs to be defined by the user to control these approximation errors are explained.     

Simulation process of flexible multibody systems with non-modal model order reduction techniques

One important issue for the simulation of flexible multibody systems is the reduction of the flexible body’s degrees of freedom. In this work, nonmodal model reduction techniques for flexible multibody systems within the floating frame of reference framework are considered. While traditionally in the multibody community modal techniques in many different forms are used, here other methods from system dynamics and mathematics are in the focus. For the reduction process, finite element data and user inputs are necessary. Prior to the reduction process, the user first needs to choose boundary conditions fitting the chosen reference frame before defining the appropriate in- and outputs. In this work, four different possibilities of modeling appropriate interface points to reduce the number of inputs and outputs are presented.     

Nested multigrid methods for time-periodic,parabolic optimal control problems

We present a nested multigrid method to optimize time-periodic, parabolic, partial differential equations (PDE). We consider a quadratic tracking objective with a linear parabolic PDE constraint. The first order optimality conditions, given by a coupled system of boundary value problems can be rewritten as an Fredholm integral equation of the second kind, which is solved by a multigrid of the second kind. The evaluation of the integral operator consists of solving sequentially a boundary value problem for respectively the state and the adjoints. Both problems are solved efficiently by a time-periodic space-time multigrid method.     

Distributed information service architecture for overlapping multiaccess networks

Multimedia delivery in mobile multiaccess network environments has emerged as a key area within the future Internet research domain. When network heterogeneity is coupled with the proliferation of multiaccess capabilities in mobile handheld devices, one can expect many new avenues for developing novel services and applications. New mechanisms for audio/video delivery over multiaccess networks will define the next generation of major distribution technologies, but will require significantly more information to operate according to their best potential. In this paper we present and evaluate a distributed information service, which can enhance media delivery over such multiaccess networks. We describe the proposed information service, which is built upon the new distributed control and management framework (DCMF) and the mobility management triggering functionality (TRG). We use a testbed which includes 3G/HSPA, WLAN and WiMAX network accesses to evaluate our proposed architecture and present results that demonstrate its value in enhancing video delivery and minimizing service disruption in an involved scenario.     

Information-based adaptive fast-forward for visual surveillance

Automated video analysis lacks reliability when searching for unknown events in video data. The practical approach is to watch all the recorded video data, if applicable in fast-forward mode. In this paper we present a method to adapt the playback velocity of the video to the temporal information density, so that the users can explore the video under controlled cognitive load. The proposed approach can cope with static changes and is robust to video noise. First, we formulate temporal information as symmetrized Rényi divergence, deriving this measure from signal coding theory. Further, we discuss the animated visualization of accelerated video sequences and propose a physiologically motivated blending approach to cope with arbitrary playback velocities. Finally, we compare the proposed method with the current approaches in this field by experiments and a qualitative user study, and show its advantages over motion-based measures.     

Non-standard bone simulation: interactive numerical analysis by computational steering

Numerous numerical methods have been developed in an effort to accurately predict stresses in bones. The largest group are variants of the h-version of the finite element method (h-FEM), where low order Ansatz functions are used. By contrast, we3 investigate a combination of high order FEM and a fictitious domain approach, the finite cell method (FCM). While the FCM has been verified and validated in previous publications, this article proposes methods on how the FCM can be made computationally efficient to the extent that it can be used for patient specific, interactive bone simulations. This approach is called computational steering and allows to change input parameters like the position of an implant, material or loads and leads to an almost instantaneous change in the output (stress lines, deformations). This direct feedback gives the user an immediate impression of the impact of his actions to an extent which, otherwise, is hard to obtain by the use of classical non interactive computations. Specifically, we investigate an application to pre-surgical planning of a total hip replacement where it is desirable to select an optimal implant for a specific patient. Herein, optimal is meant in the sense that the expected post-operative stress distribution in the bone closely resembles that before the operation.     

Iterant recombination with one-norm minimization for multilevel Markov chain algorithms via the ellipsoid method

Recently, it was shown how the convergence of a class of multigrid methods for computing the stationary distribution of sparse, irreducible Markov chains can be accelerated by the addition of an outer iteration based on iterant recombination. The acceleration was performed by selecting a linear combination of previous fine-level iterates with probability constraints to minimize the two-norm of the residual using a quadratic programming method. In this paper we investigate the alternative of minimizing the one-norm of the residual. This gives rise to a nonlinear convex program which must be solved at each acceleration step. To solve this minimization problem we propose to use a deep-cuts ellipsoid method for nonlinear convex programs. The main purpose of this paper is to investigate whether an iterant recombination approach can be obtained in this way that is competitive in terms of execution time and robustness. We derive formulas for subgradients of the one-norm objective function and the constraint functions, and show how an initial ellipsoid can be constructed that is guaranteed to contain the exact solution and give conditions for its existence. We also investigate using the ellipsoid method to minimize the two-norm. Numerical tests show that the one-norm and two-norm acceleration procedures yield a similar reduction in the number of multigrid cycles. The tests also indicate that one-norm ellipsoid acceleration is competitive with two-norm quadratic programming acceleration in terms of running time with improved robustness.     

Taxonomy,technology and applications of smart objects

Deployment of embedded technologies is increasingly being examined in industrial supply chains as a means for improving efficiency through greater control over purchase orders, inventory and product related information. Central to this development has been the advent of technologies such as bar codes, Radio Frequency Identification (RFID) systems, and wireless sensors which when attached to a product, form part of the product’s embedded systems infrastructure. The increasing integration of these technologies dramatically contributes to the evolving notion of a “smart product”, a product which is capable of incorporating itself into both physical and information environments. The future of this revolution in objects equipped with smart embedded technologies is one in which objects can not only identify themselves, but can also sense and store their condition, communicate with other objects and distributed infrastructures, and take decisions related to managing their life cycle. The object can essentially “plug” itself into a compatible systems infrastructure owned by different partners in a supply chain. However, as in any development process that will involve more than one end user, the establishment of a common foundation and understanding is essential for interoperability, efficient communication among involved parties and for developing novel applications. In this paper, we contribute to creating that common ground by providing a characterization to aid the specification and construction of “smart objects” and their underlying technologies. Furthermore, our work provides an extensive set of examples and potential applications of different categories of smart objects.