A two‐scale generalized finite element approach for modeling localized thermoplasticity

Predicting localized, nonlinear, thermoplastic behavior and residual stresses and deformations in structures subjected to intense heating is a prevalent challenge in a range of modern engineering applications. The authors present a generalized finite element method targeted at this class of problems, involving the solution of intrinsically parallelizable local boundary value problems to capture localized, time‐dependent thermo‐elasto‐plastic behavior, which is embedded in the coarse, structural‐scale approximation via enrichment functions. The method accommodates approximation spaces that evolve in between time or load steps while maintaining a fixed global mesh, which avoids the need to map solutions and state variables on changing meshes typical of traditional adaptive approaches. Representative three‐dimensional examples exhibiting localized, transient, nonlinear thermal and thermomechanical effects are presented to demonstrate the advantages of the method with respect to available approaches, especially in terms of its flexibility and potential for realistic future applications in this area. Parallelism of the approach is also discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Long-pulse narrow-linewidth dispersive solid-state dye-laser oscillator

We report on narrow-linewidth long-pulse laser emission from a dispersive solid-state dye-laser oscillator. Output energy was ~0.4 mJ/pulse at laser linewidths of 650 MHz and pulse lengths of 105 ns FWHM. The solid-state gain medium utilized was Rhodamine 6G dye-doped 2-hydroxyethyl methacrylate:methyl methacrylate.     

Determination of sulfur dioxide in wine using a quartz crystal microbalance

A new method for the analysis of both total and bound SO(2) in wine is proposed, based on a quartz crystal microbalance (QCM), and it is compared with the widely used Ripper method. The proposed method is faster than the Ripper's, and the instrumentation is either home-made or widely available. When both methods are applied to the same sample, the results obtained using the QCM method are bracketed in an interval less than one-tenth the size of that obtained using the Ripper method. Although the SO(2) concentrations found using the QCM method correlate well with the ones obtained with the Ripper method, the results are systematically higher, which can be explained as due to the absence of interferences known to affect the Ripper method.     

On the design of multi‐rate tracking controllers: Application to rotorcraft guidance and control

This paper presents a new methodology for the design and implementation of gain‐scheduled controllers for multi‐rate systems. The proposed methodology provides a natural way to address the integrated guidance and control problem for autonomous vehicles when the outputs are sampled at different instants of time. A controller structure is first proposed for the regulation of non‐square multi‐rate systems with more measured outputs than inputs. Based on this structure, an implementation for a gain‐scheduled controller is obtained that satisfies an important property known as the linearization property. The implementation resembles the velocity implementation for single‐rate systems. The method is then applied to the problem of steering an autonomous rotorcraft along a predefined trajectory defined in terms of space and time coordinates. By considering a convenient error vector to describe the vehicle's dynamics, the trajectory tracking problem is reduced to that of regulating the error variables to zero. Because of the periodic multi‐rate nature of the onboard sensor suite, the controller synthesis is dealt with under the scope of linear periodic systems theory. Simulation results obtained with a full non‐linear rotorcraft dynamic model are presented and discussed. Copyright © 2010 John Wiley & Sons, Ltd.     

Hybridizing the cross-entropy method: An application to the max-cut problem

Cross-entropy has been recently proposed as a heuristic method for solving combinatorial optimization problems. We briefly review this methodology and then suggest a hybrid version with the goal of improving its performance. In the context of the well-known max-cut problem, we compare an implementation of the original cross-entropy method with our proposed version. The suggested changes are not particular to the max-cut problem and could be considered for future applications to other combinatorial optimization problems.     

Application of functionalised carbon nanotubes immobilised into chitosan films in amperometric enzyme biosensors

A new approach for building a bio-conductive interface for enzyme immobilisation is described. This strategy permits very simple preparation of the enzyme biosensor and also reveals direct electron transfer features. A graphite-epoxy resin composite (GrEC) electrode modified with functionalised multi-wall carbon nanotubes (MWCNTs) immobilised by 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide together with N-hydroxysuccinimide (EDC–NHS) in a chitosan (Chit) matrix was prepared and characterised by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) in the presence of hexaammineruthenium (III) chloride. It was then used as a base for glucose oxidase (GOx) immobilisation by the simple method of crosslinking with glutaraldehyde (GA) with bovine serum albumin (BSA) as carrier protein. The resulting mediator-free biosensor was applied to the determination of glucose in amperometric mode at different applied potentials and the mechanism of reaction was also investigated by cyclic voltammetry, with and without dissolved oxygen in solution. Analytical parameters, as well as reproducibility, repeatability and stability were determined. Interferences were assessed using different compounds usually present in natural samples, such as wines, juices or blood, in order to evaluate the selectivity of the developed biosensor. The novel combination of carbon nanotubes immobilised with chitosan crosslinked with EDC–NHS and glucose oxidase immobilised by crosslinking with glutaraldehyde offers an excellent, easy to make biosensor for glucose determination without interferences.     

Hand gesture recognition from depth and infrared Kinect data for CAVE applications interaction

This paper presents a real-time framework that combines depth data and infrared laser speckle pattern (ILSP) images, captured from a Kinect device, for static hand gesture recognition to interact with CAVE applications. At the startup of the system, background removal and hand position detection are performed using only the depth map. After that, tracking is started using the hand positions of the previous frames in order to seek for the hand centroid of the current one. The obtained point is used as a seed for a region growing algorithm to perform hand segmentation in the depth map. The result is a mask that will be used for hand segmentation in the ILSP frame sequence. Next, we apply motion restrictions for gesture spotting in order to mark each image as a ‘Gesture’ or ‘Non-Gesture’. The ILSP counterparts of the frames labeled as “Gesture” are enhanced by using mask subtraction, contrast stretching, median filter, and histogram equalization. The result is used as the input for the feature extraction using a scale invariant feature transform algorithm (SIFT), bag-of-visual-words construction and classification through a multi-class support vector machine (SVM) classifier. Finally, we build a grammar based on the hand gesture classes to convert the classification results in control commands for the CAVE application. The performed tests and comparisons show that the implemented plugin is an efficient solution. We achieve state-of-the-art recognition accuracy as well as efficient object manipulation in a virtual scene visualized in the CAVE.     

Productivity paradoxes revisited

The adoption of quality assurance methods based on software process improvement models has been regarded as an important source of variability in software productivity. Some companies perceive that their implementation has prohibitive costs, whereas some authors identify in their use a way to comply with software development patterns and standards, produce economic value and lead to corporate performance improvement. In this paper, we investigate the relationship between quality maturity levels and labor productivity, using a data set containing 687 Brazilian software firms. We study here the relationship between labor productivity, as measured through the annual gross revenue per worker ratio, and quality levels, which were appraised from 2006 to 2012 according to two distinct software process improvement models: MPS.BR and CMMI. We perform independent statistical tests using appraisals carried out according to each of these models, consequently obtaining a data set with as many observations as possible, in order to seek strong support for our research. We first show that MPS.BR and CMMI appraised quality maturity levels are correlated, but we find no statistical evidence that they are related to higher labor productivity or productivity growth. On the contrary, we present evidence suggesting that average labor productivity is higher in software companies without appraised quality levels. Moreover, our analyses suggest that companies with appraised quality maturity levels are more or less productive depending on factors such as their business nature, main origin of capital and maintained quality level.