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    Enhanced Identification of Hidden Conductive Objects with Deterministic and Stochastic Methods

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    The identification of conductive objects of known shape embedded in low- or non-conductive regions is a special application of non-destructive testing, with important applications in some surgical procedures. In particular, some classes of fractures are routinely stabilized and aligned by the use of intra-medullary nails. Identifying the position and the orientation of the drill holes hidden by bone and tissue is currently done by X-Ray with all the well known disadvantages of this technology. The idea of substituting this methodology with an eddy-current based one has been explored in previous work but the developed technique suffered from some hard to address shortcomings. In this paper we propose a new technique which is computationally efficient and inexpensive to implement

    Numerical Simulation Framework for Weakly Coupled Multiphysical Problems in Electrical Engineering

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    Every engineering discipline faces the fact of ever-shortening time-to-market windows and development cycles. In order to counteract these, virtual prototyping, sim- ulation and problem optimization are employed in a rapidly increasing number of cases. Yet, the key to efficient problem formulation by professionals still lies in the use of sophisti- cated simulation software capable of processing numerous diverse design and optimization tasks in a versatile way. More often than not, different tools for different workflows need to be coordinated and interdepend on each others data in the design process chain. When toolchains need to be run multiple times, as it is typically the case in numerical optimization, the lineup overhead tends to be tedious to both man and machine. This paper describes different aspects concerning the design of a software and data frame- work which tackles the problem of lining up software tools that may be incoherent in terms of data exchange and control mode. The resulting system covers all parts of multiphysical simulation problems that may arise in electrical engineering and its adjoining disciplines as an application of the finite element method

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Some results on a SMES device optimization benchmark problem

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    The scope of this paper is to throw some light on the difficulties when optimizing in a discrete parameter space. In the first section of this paper some general considerations on the optimization of a SMES device in a discrete space are made. In the second part a pattern search technique as a representative for deterministic, an evolution strategy and a simulated annealing algorithm as members of the class of stochastic methods are presented and used to optimize the problem. The effect of varying the discretization is investigated for the pattern search method. In the next section some features of the benchmark problem are introduced and finally the optimization results are given
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