Open to a Select Few? Matching Partners and Knowledge Content for Open Innovation Performance

The purpose of the paper is to illuminate the costs and benefits of crossing firm boundaries in inbound open innovation (OI) by determining the relationships among partner types, knowledge content and performance. The empirical part of the study is based on a survey of OI collaborations answered by R&D managers in 415 Italian, Finnish and Swedish firms. The results show that the depth of collaboration with different partners (academic/consultants, value chain partners, competitors and firms in other industries) is positively related to innovation performance, whereas the number of different partners and size have negative effects. The main result is that the knowledge content of the collaboration moderates the performance outcomes and the negative impact of having too many different kinds of partners. This illustrates how successful firms use selective collaboration strategies characterized by linking explorative and exploitative knowledge content to specific partners, to leverage the benefits and limit the costs of knowledge boundary crossing processes.     

Application of particle swarm optimization in epileptic spike EEG source localization

Surgical therapy has become an important therapeutic alternative for patients with medically intractable epilepsy. Correct and anatomically precise localization of an epileptic focus is essential to decide if resection of brain tissue is possible. The inverse problem in EEG-based source localization is to determine the location of the brain sources that are responsible for the measured potentials at the scalp electrodes. We propose a new global optimization method based on particle swarm optimization (PSO) to solve the epileptic spike EEG source localization inverse problem. In a forward problem a modified subtraction method is proposed to reduce the computational time. The good accuracy and fast convergence are demonstrated for 2D and 3D cases with realistic head models. The results from the new method are promising for use in the pre-surgical clinic in the future.     

Detailed 3D human body reconstruction from multi-view images combining voxel super-resolution and learned implicit representation

Applied Intelligence - The task of reconstructing detailed 3D human body models from images is interesting but challenging in computer vision due to the high freedom of human bodies. This work...     

On computational homogenization of microscale crack propagation

The effective response of microstructures undergoing crack propagation is studied by homogenizing the response of statistical volume elements (SVEs). Because conventional boundary conditions (Dirichlet, Neumann and strong periodic) all are inaccurate when cracks intersect the SVE boundary, we herein use first order homogenization to compare the performance of these boundary conditions during the initial stage of crack propagation in the microstructure, prior to macroscopic localization. Using weakly periodic boundary conditions that lead to a mixed formulation with displacements and boundary tractions as unknowns, we can adapt the traction approximation to the problem at hand to obtain better convergence with increasing SVE size. In particular, we show that a piecewise constant traction approximation, which has previously been shown to be efficient for stationary cracks, is more efficient than the conventional boundary conditions in terms of convergence also when crack propagation occurs on the microscale. The performance of the method is demonstrated by examples involving grain boundary crack propagation modelled by conventional cohesive interface elements as well as crack propagation modelled by means of the extended finite element method in combination with the concept of material forces. © 2016 The Authors. International Journal for Numerical Methods in Engineering Published by John Wiley & Sons Ltd.     

A flux-free a posteriori error estimator for the incompressible Stokes problem using a mixed FE formulation

In this contribution, we present an a posteriori error estimator for the incompressible Stokes problem valid for a conventional mixed FE formulation. Due to the saddle-point property of the problem, conventional error estimators developed for pure minimization problems cannot be utilized straight-forwardly. The new estimator is built up by two key ingredients. At first, a computed error approximation, exactly fulfilling the continuity equation for the error, is obtained via local Dirichlet problems. Secondly, we adopt the approach of solving local equilibrated flux-free problems in order to bound the remaining, incompressible, error. In this manner, guaranteed upper and lower bounds, of the velocity “energy norm” of the error as well as goal-oriented (linear) output functionals, with respect to a reference (overkill) mesh are obtained. In particular, it should be noted that this approach requires no computation of hybrid fluxes. Furthermore, the estimator is applicable to mixed FE formulations using continuous pressure approximations, such as the Mini and Taylor–Hood class of elements. In conclusion, a few simple numerical examples are presented, illustrating the accuracy of the error bounds.     

Faster Deterministic Communication in Radio Networks

We study the communication primitives of broadcasting (one-to-all communication) and gossiping (all-to-all communication) in known topology radio networks, i.e., where for each primitive the schedule of transmissions is precomputed based on full knowledge about the size and the topology of the network. We show that gossiping can be completed in time units in any radio network of size n, diameter D, and maximum degree Δ=Ω(log n). This is an almost optimal schedule in the sense that there exists a radio network topology, specifically a Δ-regular tree, in which the radio gossiping cannot be completed in less than units of time. Moreover, we show a schedule for the broadcast task. Both our transmission schemes significantly improve upon the currently best known schedules by Gąsieniec, Peleg, and Xin (Proceedings of the 24th Annual ACM SIGACT-SIGOPS PODC, pp. 129–137, 2005), i.e., a O(D+Δlog n) time schedule for gossiping and a D+O(log ³ n) time schedule for broadcast. Our broadcasting schedule also improves, for large D, a very recent O(D+log ² n) time broadcasting schedule by Kowalski and Pelc. A preliminary version of this paper appeared in the proceedings of ISAAC’06. F. Cicalese supported by the Sofja Kovalevskaja Award 2004 of the Alexander von Humboldt Stiftung. F. Manne and Q. Xin supported by the Research Council of Norway through the SPECTRUM project.     

Branch-and-Bound Methods for Euclidean Registration Problems

In this paper, we propose a practical and efficient method for finding the globally optimal solution to the problem of determining the pose of an object. We present a framework that allows us to use point-to-point, point-to-line, and point-to-plane correspondences for solving various types of pose and registration problems involving euclidean (or similarity) transformations. Traditional methods such as the iterative closest point algorithm or bundle adjustment methods for camera pose may get trapped in local minima due to the nonconvexity of the corresponding optimization problem. Our approach of solving the mathematical optimization problems guarantees global optimality. The optimization scheme is based on ideas from global optimization theory, in particular convex underestimators in combination with branch-and-bound methods. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data. We also give examples of where traditional methods fail due to the local minima problem.     

A numerical framework for load identification and regularization with application to rolling disc problem

Indirect identification methods are applied when direct measurement is unfeasible. One example is the measurement of the contact force between wheel and rail in railway traffic. This paper focuses on optimization-based methods for the identification of contact forces with the aim of developing a reliable and robust load identification scheme. A particular issue discussed here is the choice of discretization in space–time, enabling the sampling instances of the measurements, the parameterization of the sought input and the discretization of the pertinent state equations to be decoupled, in contrast to traditional methods such as, e.g. dynamic programming.In the present preliminary study where a 2-D disc is considered as a representative of a train wheel, a radial concentrated force rotates around the disc’s perimeter, representing the contact force acting on the rim of the wheel, while radial strains are measured on a set of points corresponding to the strain gauges position. The strain history data is then used in the identification procedure where the applied force is sought to minimize the discrepancy between the predicted and measured strain history. In particular the convergence of the results with respect to the temporal discretization of the model and the time parameterization of the sought loading history are investigated under the influence of noise. It is seen that choosing a discretization of the sought load that is coarser than that of the state variable gives a more robust scheme. The traditional Tikhonov regularization can also be added within the current framework. Furthermore, with the aid of a sensitivity analysis, the influence of measurement noise can be quantified.     

Optimization strategy in the development process with application to cast components

At the development of commercial vehicles, it is necessary to develop cost-optimized components with respect to their entire lifetime. This requires a product development process that utilizes the possibility to simulate the product performance using modeling of different degrees of sophistication at any predefined level-of-detail (LOD). For example, the mechanical properties of a cast component depend strongly on the casting process, the simulation of which requires complex modeling at a high LOD. In this article, we propose an optimization strategy that is based on the LOD concept to develop cost-effective components. A sizing optimization of a cast model component is carried out with respect to both the mechanical and thermal response to exemplify the process. In particular, a (novel) global measure of the temperature in energy norm is introduced as an indicator of the “production fitness” to ensure high quality of the material properties. This measure is the thermal counterpart of the well-accepted mechanical strain energy.     

Efficient Algorithms for k Maximum Sums

We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers and an integer parameter k, the problem involves finding the k largest values of for The problem for fixed k = 1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. Recently, Bae and Takaoka presented a -time algorithm for the k maximum sum subsequences problem. In this paper we design an efficient algorithm that solves the above problem in time in the worst case. Our algorithm is optimal for and improves over the previously best known result for any value of the user-defined parameter k < 1. Moreover, our results are also extended to the multi-dimensional versions of the k maximum sum subsequences problem; resulting in fast algorithms as well.