Multi-camera calibration based on an invariant pattern

In this paper we present a method for the calibration of multiple cameras based on the extraction and use of the physical characteristics of a one-dimensional invariant pattern which is defined by four collinear markers. The advantages of this kind of pattern stand out in two key steps of the calibration process. In the initial step of camera calibration methods, related to sample points capture, the proposed method takes advantage of using a new technique for the capture and recognition of a robust sample of projective invariant patterns, which allows to capture simultaneously more than one invariant pattern in the tracking area and recognize each pattern individually as well as each marker that composes them. This process is executed in real time while capturing our sample of calibration points in the cameras of our system. This new feature allows to capture a more numerous and robust set of sample points than other patterns used for multi-camera calibration methods. In the last step of the calibration process, related to camera parameters' optimization, we explore the collinearity feature of the invariant pattern and add this feature in the camera parameters optimization model. This approach obtains better results in the computation of camera parameters. We present the results obtained with the calibration of two multi-camera systems using the proposed method and compare them with other methods from the literature.     

Guidelines for the incremental identification of aspects in requirements specifications

The desired principle of separation of concerns in software development can be jeopardized by the so-called crosscutting concerns, which tend to be scattered over (and tangled with) the functionality of the modular units of a system. The correct identification of such concerns (and their encapsulation into separate artifacts) is thereby considered a way to improve software understanding and evolution. Pursuing a proper management of concerns from the requirements engineering stage can greatly benefit the entire software life-cycle. In this paper, we propose conceptual guidelines on how to perform the identification of crosscutting concerns in the process of building requirements specifications. We argue that the identification must be carried out in an incremental way, to encapsulate apart the crosscutting concerns even if they have not emerged completely yet.

Human cytidine deaminase: a three-dimensional homology model of a tetrameric metallo-enzyme inferred from the crystal structure of a distantly related dimeric homologue

Cytidine deaminase (CDA) is a cytosolic metalloprotein whose functional unit can be either a homotetramer (T-CDA) or a homodimer (D-CDA), depending on the species. In 1994, the first crystal structure of the dimeric Escherichia coli CDA has been published. However, a crystal structure of a tetrameric CDA was not determined until 2002. Prior to the disclosure of the experimentally elucidated structure of a tetrameric CDA, we derived a homology model of the human T-CDA employing the crystal structure of the dimeric E. coli CDA as a template. The comparison of our theoretical model with the crystal structure of the human T-CDA, subsequently published in 2004, validates our prediction: not only of the structural features of the monomer and the details of the binding site, but also the multimeric arrangement of the subunits were determined with high accuracy in our model. By means of a phylogenetic analysis conducted on CDAs from various organisms, we demonstrate that the E. coli CDA is one of the furthest known homologues of the human enzyme. Nonetheless, despite the evolutionary distance and, more importantly, the different multimeric arrangement of their functional units, the E. coli CDA proved to have all the necessary information to accurately infer the structure of its human homologue.     

Coordination components for collaborative virtual environments

This paper deals with the behavior of virtual environments from the collaboration point-of-view, in which actors (human or virtual beings) interact and collaborate by means of interdependent tasks. In this sense, actors may realize tasks that are dependent on tasks performed by other actors, while the interdependencies between tasks (through resource management and temporal relations) delineate the overall behavior of a virtual environment. Our main goal is to propose an approach for the coordination of those behaviors. Initially a generic study of possible interdependencies between collaborative tasks is presented, followed by the formal modeling (using Petri Nets) of coordination mechanisms for those dependencies. In order to implement such mechanisms, an architecture of reusable and pluggable coordination components is also introduced. These components are used in an implementation of a multi-user videogame. The presented approach is a concrete step to create virtual societies of actors that collaborate to reach common goals without the risk of getting involved in conflicting or repetitive tasks.     

Rules and Strategies for Contextual Specialization of Constraint Logic Programs

We address the problem of specializing a constraint logic program w.r.t. a constrained atom which specifies the context of use of the program. We follow an approach based on transformation rules and strategies. We introduce a novel transformation rule, called contextual constraint replacement, to be combined with variants of the traditional unfolding and folding rules. We present a general Partial Evaluation Strategy for automating the application of these rules, and two additional strategies: the Context Propagation Strategy which is instrumental for the application of our contextual constraint replacement rule, and the Invariant Promotion Strategy for taking advantage of invariance properties of the computation. We show through some examples the power of our method and we compare it with existing methods for partial deduction of constraint logic programs based on extensions of Lloyd and Shepherdson's approach.     

Robust quantification of the exposure to operational risk: Bringing economic sense to economic capital

Operational risk is commonly analyzed in terms of the distribution of aggregate yearly losses. Risk measures can then be computed as statistics of this distribution that focus on the region of extreme losses. Assuming independence among the operational risk events and between the likelihood that they occur and their magnitude, separate models are made for the frequency and for the severity of the losses. These are then combined to estimate the distribution of aggregate losses. While the detailed form of the frequency distribution does not significantly affect the risk analysis, the choice of model for the severity often has a significant impact on operational risk measures. For heavy-tailed distributions these measures are dominated by extreme losses, whose probability cannot be reliably extrapolated from the available data. With limited empirical evidence, it is difficult to distinguish among alternative models that produce very different values of the risk measures. Furthermore, the estimates obtained can be unstable and overly sensitive to the presence or absence of single extreme events. Setting a bound on the maximum amount that can be lost in a single event reduces the dependence on the distributional assumptions and improves the robustness and stability of the risk measures, while preserving their sensitivity to changes in the risk profile. This bound should be determined by expert assessment on the basis of economic arguments and validated by the regulator, so that it can be used as a control parameter in the risk analysis.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.