Accelerating network applications by distributed interfaces on heterogeneous multiprocessor architectures

Hosts with several, possibly heterogeneous and/or multicore, processors provide new challenges and opportunities to accelerate applications with high communications bandwidth requirements. Many opportunities to scale these network applications with the increase in the link bandwidths are related to the exploitation of the available parallelism provided by the presence of several processing cores in the servers, not only for computing the workload of the user application but also for decreasing the overhead associated to the network interface and the system software.     

Optimization of biochemical systems through mathematical programming: Methods and applications

In this work we present a general (mono and multiobjective) optimization framework for the technological improvement of biochemical systems. The starting point of the method is a mathematical model in ordinary differential equations (ODEs) of the investigated system, based on qualitative biological knowledge and quantitative experimental data. In the method we take advantage of the special structural features of a family of ODEs called power-law models to reduce the computational complexity of the optimization program. In this way, the genetic manipulation of a biochemical system to meet a certain biotechnological goal can be expressed as an optimization program with some desired properties such as linearity or convexity.The general method of optimization is presented and discussed in its linear and geometric programming versions. We furthermore illustrate the use of the method by several real case studies. We conclude that the technological improvement of microorganisms can be afforded using the combination of mathematical modelling and optimization. The systematic nature of this approach facilitates the redesign of biochemical systems and makes this a predictive exercise rather than a trial-and-error procedure.     

Protein radial distribution function (P-RDF) and Bayesian-Regularized Genetic Neural Networks for modeling protein conformational stability: chymotrypsin inhibitor 2 mutants

Development of novel computational approaches for modeling protein properties is a main goal in applied Proteomics. In this work, we reported the extension of the radial distribution function (RDF) scores formalism to proteins for encoding 3D structural information with modeling purposes. Protein-RDF (P-RDF) scores measure spherical distributions on protein 3D structure of 48 amino acids/residues properties selected from the AAindex data base. P-RDF scores were tested for building predictive models of the change of thermal unfolding Gibbs free energy change (DeltaDeltaG) of chymotrypsin inhibitor 2 upon mutations. In this sense, an ensemble of Bayesian-Regularized Genetic Neural Networks (BRGNNs) yielded an optimum nonlinear model for the conformational stability. The ensemble predictor described about 84% and 70% variance of the data in training and test sets, respectively.     

Computing the homology of groups: The geometric way

In this paper, we present several algorithms related with the computation of the homology of groups, from a geometric perspective (that is to say, carrying out the calculations by means of simplicial sets and using techniques of Algebraic Topology). More concretely, we have developed some algorithms which, making use of the effective homology   method, construct the homology groups of Eilenberg–MacLane spaces K(G,1)$K(G,1)$ for different groups G$G$, allowing one in particular to determine the homology groups of G$G$.     

FOS: a low-power cache organization for multicores

The Journal of Supercomputing - The cache hierarchy of current multicore processors typically consists of one or two levels of private caches per core and a large shared last-level cache. This...     

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.     

An improved 3D imaging system for dimensional quality inspection of rolled products in the metal industry

Measurement, inspection and quality control in industry have benefited from 3D techniques for imaging and visualization in recent years. The development of machine vision devices at decreased costs, as well as their miniaturization and integration in industrial processes, have accelerated the use of 3D imaging systems in industry. In this paper we describe how to improve the performance of a 3D imaging system for inline dimensional quality inspection of long, flat-rolled metal products manufactured in rolling mills we designed and developed in previous works. Two dimensional characteristics of rolled products are measured by the system: width and flatness. The system is based on active triangulation using a single-line pattern projected onto the surface of the product under inspection for range image acquisition. Taking the system calibration into account the range images are transformed into a calibrated point cloud representing the 3D surface reconstruction of the product. Two approaches to improve the line detection and extraction method used in the original system are discussed, one intended for high-speed processing with lower accuracy, and the other providing high accuracy while incurring higher computational time expenses. A mechanism to remove, or at least reduce, the effects of product movements while manufacturing, such as bouncing and flapping, is also proposed to improve the performance of the system.     

Scheduling component replacement for timely execution in dynamic systems

Timely run‐time software replacement techniques are a corner stone for reconciling real‐time systems development and dynamic behavior. Typical real‐time systems do not consider dynamic behavior because it deeply challenges predictability and timeliness. Current efforts are starting to merge the safe and predictable execution with a controllable level of dynamicity by imposing a set of bounds and limitations to the system dynamic behavior. One of the obstacles for this is how to time‐bound the different operations required to effectively implement component replacement. In this paper, the main challenges for this problem are identified, and a model to ensure that components can be replaced at run time preserving the temporal properties of the system is provided that also avoids failures in replacements. A real example and simulations of our replacement model are provided that validate the presented ideas. Copyright © 2013 John Wiley & Sons, Ltd.     

Interactive collision detection in three-dimensional visualizations of simulated construction operations

This paper presents research that led to the design and implementation of fast and interactive collision detection methods that can be used to identify and report undesirable conflicts that occur among static (e.g., structure in-place, idle equipment), dynamic (e.g., active machines and workers), and abstract (e.g., hazard spaces) construction resources in 3D animations of construction operations modeled using discrete-event simulation. Computational efficiency and interactive speed in the designed interference detection methods were the primary challenges that the research addressed. In addition, the efficiency and speed were achieved with minimal trade-off against accuracy. In order to achieve this, the authors capitalized on advanced documented algorithms for proximity queries between arbitrarily moving 3D geometric objects to design mechanisms for interference detection, control, and response in construction process visualizations. The designed methods are implemented in a software tool called C-Collide that integrates as an add-on with the VITASCOPE visualization system.