SOA-enabled compliance management: instrumenting, assessing, and analyzing service-based business processes

Facilitating compliance management, that is, assisting a company’s management in conforming to laws, regulations, standards, contracts, and policies, is a hot but non-trivial task. The service-oriented architecture (SOA) has evolved traditional, manual business practices into modern, service-based IT practices that ease part of the problem: the systematic definition and execution of business processes. This, in turn, facilitates the online monitoring of system behaviors and the enforcement of allowed behaviors—all ingredients that can be used to assist compliance management on the fly during process execution. In this paper, instead of focusing on monitoring and runtime enforcement of rules or constraints, we strive for an alternative approach to compliance management in SOAs that aims at assessing and improving compliance. We propose two ingredients: (i) a model and tool to design compliant service-based processes and to instrument them in order to generate evidence of how they are executed and (ii) a reporting and analysis suite to create awareness of a company’s compliance state and to enable understanding why and where compliance violations have occurred. Together, these ingredients result in an approach that is close to how the real stakeholders—compliance experts and auditors—actually assess the state of compliance in practice and that is less intrusive than enforcing compliance.     

A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem

Meta-heuristics are frequently used to tackle NP-hard combinatorial optimization problems. With this paper we contribute to the understanding of the success of 2-opt based local search algorithms for solving the traveling salesperson problem (TSP). Although 2-opt is widely used in practice, it is hard to understand its success from a theoretical perspective. We take a statistical approach and examine the features of TSP instances that make the problem either hard or easy to solve. As a measure of problem difficulty for 2-opt we use the approximation ratio that it achieves on a given instance. Our investigations point out important features that make TSP instances hard or easy to be approximated by 2-opt.     

Dependable Low‐altitude Obstacle Avoidance for Robotic Helicopters Operating in Rural Areas

This paper presents a system enabling robotic helicopters to fly safely without user interaction at low altitude over unknown terrain with static obstacles. The system includes a novel reactive behavior‐based method that guides rotorcraft reliably to specified locations in sparsely occupied environments. System dependability is, among other things, achieved by utilizing proven system components in a component‐based design and incorporating safety margins and safety modes. Obstacle and terrain detection is based on a vertically mounted off‐the‐shelf two‐dimensional LIDAR system. We introduce two flight modes, pirouette descent and waggle cruise, which extend the field of view of the sensor by yawing the aircraft. The two flight modes ensure that all obstacles above a minimum size are detected in the direction of travel. The proposed system is designed for robotic helicopters with velocity and yaw control inputs and a navigation system that provides position, velocity, and attitude information. It is cost effective and can be easily implemented on a variety of helicopters of different sizes. We provide sufficient detail to facilitate the implementation on single‐rotor helicopters with a rotor diameter of approximately 1.8 m. The system was extensively flight‐tested in different real‐world scenarios in Queensland, Australia. The tests included flights beyond visual range without a backup pilot. Experimental results show that it is feasible to perform dependable autonomous flight using simple but effective methods. © 2013 Wiley Periodicals, Inc.     

A benchmark of kriging-based infill criteria for noisy optimization

Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.     

The Lattice-Boltzmann Method on Optimal Sampling Lattices

In this paper, we extend the single relaxation time Lattice-Boltzmann Method (LBM) to the 3D body-centered cubic (BCC) lattice. We show that the D3bQ15 lattice defined by a 15 neighborhood connectivity of the BCC lattice is not only capable of more accurately discretizing the velocity space of the continuous Boltzmann equation as compared to the D3Q15 Cartesian lattice, it also achieves a comparable spatial discretization with 30 percent less samples. We validate the accuracy of our proposed lattice by investigating its performance on the 3D lid-driven cavity flow problem and show that the D3bQ15 lattice offers significant cost savings while maintaining a comparable accuracy. We demonstrate the efficiency of our method and the impact on graphics and visualization techniques via the application of line-integral convolution on 2D slices as well as the extraction of streamlines of the 3D flow. We further study the benefits of our proposed lattice by applying it to the problem of simulating smoke and show that the D3bQ15 lattice yields more detail and turbulence at a reduced computational cost.     

Image staining and differential diagnosis of ultrasound scans based on the Mahalanobis distance

The covariance matrices associated with each state of health or disease from a previous study are used as the basis of an image staining display technique for aid in quantitative differential diagnosis. A state of health or disease is chosen by the clinician: this selects the covariance matrix from the data base. A region of interest (ROI) is then scrolled through an abdominal B-scan. For each position of the ROI a point in the four-dimensional feature space is calculated. A natural measure of the distance of this point from the center of mass (multivariate mean) of the disease class is calculated in terms of the covariance matrix of this class; this measure is the Mahalanobis distance. The confidence level for acceptance or rejection of the hypothesized disease class is obtained from the probability distribution of this distance, the T(2) probability law. This confidence level is color coded and used as a color stain that overlays the original scan at that position. The variability of the calculated features is studied as a function of ROI size, or the spatial resolution of the color coded image, and it is found that for an ROI in the neighborhood of 4 cm(2) most of the variability due to the finite number of independent samples (speckles) is averaged out, leaving the "noise floor" associated with inter- and intra-patient variability. ROIs on the order of 1 cm(2) may result with technical advances in B-scan resolution. A small number of points on organ boundaries are entered by the user, to fit with arcs of ellipses to be used to switch between organ (liver and kidney) data bases as the ROI encounters the boundary. By selecting in turn various state-of-health or state-of-disease databases, such images of confidence levels may be used for quantitative differential diagnosis. The method is not limited to ultrasound, being applicable in principle to features obtained from any modality or multimodality combination.     

Modelling the three-dimensional elastic constants of parallel-fibred and lamellar bone

The complex hierarchical structure of lamellar bone makes understanding structure–mechanical function relations, very difficult. We approach the problem by first using the relatively simple structure of parallel-fibred bone to construct a mathematical model for calculating Young's moduli in three-dimensions. Parallel-fibred bone is composed essentially of arrays of mineralized collagen fibrils, which are also the basic structural motif of the individual lamellae of lamellar bone. Parallel-fibred bone structure has orthotropic symmetry. As the sizes and shapes of crystals in bone are not well known, the model is also used to compare the cases of platelet-, ribbon- and sheet-reinforced composites. The far more complicated rotated plywood structure of lamellar bone results in the loss of the orthotropic symmetry of individual lamellae. The mathematical model used circumvents this problem by sub-dividing the lamellar unit into a thin lamella, thick lamella, transition zone between them, and the recently observed back-flip lamella. Each of these is regarded as having orthotropic symmetry. After the calculation of their Young's moduli they are rotated in space in accordance with the rotated plywood model, and then the segments are combined to present the overall modulus values in three-dimensions. The calculated trends compare well with the trends in microhardness values measured for circumferential lamellar bone. Microhardness values are, as yet, the only measurements available for direct comparison. Although the model is not directly applicable to osteonal bone, which is composed of many hollow cylinders of lamellar bone, the range of calculated modulus values and the trends observed for off-axis calculations, compare well with measured values. © 1998 Chapman & Hall     

Optical computing: introduction by the feature editors

This feature issue of Applied Optics: Information Processing contains 19 papers on Optical Computing. Many of these papers are expanded versions of presentations given at the Optical Society of America's Sixth Topical Meeting on Optical Computing held in Salt Lake City, Utah, in March 1995. This introduction provides a brief historical account of the series of optical computing meetings and a brief review of the papers contained in this special issue.