A Lagrangian Scheme for the Solution of Nonlinear Diffusion Equations Using Moving Simplex Meshes

A Lagrangian numerical scheme for solving nonlinear degenerate Fokker–Planck equations in space dimensions \(d\ge 2\) is presented. It applies to a large class of nonlinear diffusion equations, whose dynamics are driven by internal energies and given external potentials, e.g. the porous medium equation and the fast diffusion equation. The key ingredient in our approach is the gradient flow structure of the dynamics. For discretization of the Lagrangian map, we use a finite subspace of linear maps in space and a variational form of the implicit Euler method in time. Thanks to that time discretisation, the fully discrete solution inherits energy estimates from the original gradient flow, and these lead to weak compactness of the trajectories in the continuous limit. Consistency is analyzed in the planar situation, \(d=2\). A variety of numerical experiments for the porous medium equation indicates that the scheme is well-adapted to track the growth of the solution’s support.     

Structural shape optimization using Cartesian grids and automatic <Emphasis Type="Italic">h</Emphasis>-adaptive mesh projection

We present a novel approach to 3D structural shape optimization that leans on an Immersed Boundary Method. A boundary tracking strategy based on evaluating the intersections between a fixed Cartesian grid and the evolving geometry sorts elements as internal, external and intersected. The integration procedure used by the NURBS-Enhanced Finite Element Method accurately accounts for the nonconformity between the fixed embedding discretization and the evolving structural shape, avoiding the creation of a boundary-fitted mesh for each design iteration, yielding in very efficient mesh generation process. A Cartesian hierarchical data structure improves the efficiency of the analyzes, allowing for trivial data sharing between similar entities or for an optimal reordering of the matrices for the solution of the system of equations, among other benefits. Shape optimization requires the sufficiently accurate structural analysis of a large number of different designs, presenting the computational cost for each design as a critical issue. The information required to create 3D Cartesian h-adapted mesh for new geometries is projected from previously analyzed geometries using shape sensitivity results. Then, the refinement criterion permits one to directly build h-adapted mesh on the new designs with a specified and controlled error level. Several examples are presented to show how the techniques here proposed considerably improve the computational efficiency of the optimization process.     

A cooperative protocol for pervasive underwater acoustic networks

Wireless Networks - The novel Underwater Wireless Sensor Network (UWSN) can contribute to monitor and explore aquatic environments. But, communicating in these environments is still hard and has...     

SDN-based architecture for providing quality of service to high-performance distributed applications

The specification of quality of service (QoS) requirements in most of the existing networks is still challenging. In part, traditional network environments are limited by their high administrative cost, although software-defined networks (SDNs), a newer network paradigm, simplify the management of the whole network infrastructure. In fact, SDN provides a simple way to effectively develop QoS provisioning mechanisms. In this sense, we explore the SDN model and its flexibility to develop a QoS provisioning architecture. Through the use of our new architecture, network operators are able to specify QoS levels in a simple way. Each individual data flow can be addressed, and the architecture we propose also negotiates the QoS requirements between the network controller and applications. On the other hand, the network controller continuously monitors the network environment. Then, it allocates network elements resources and prioritizes traffic, adjusting the network performance. We evaluate the feasibility of our QoS provisioning mechanism by presenting three experimental setups under realistic scenarios. For example, for a given scenario where we evaluate file transfers, our results indicate that the additional SDN modules present negligible overhead. Moreover, for a given setup, we observe a reduction of up to 82% in the file transfer times.     

Correction to: Uniform and scalable sampling of highly configurable systems

Empirical Software Engineering - Testing Internet of Things (IoT) systems is challenging. This is not only because of the various aspects of IoT systems, such as software, hardware, and network...     

Identifying routes and organizational practices for resilient performance: a study in the construction industry

Cognition, Technology & Work - Modern organizations live in a context of political, economic, technological, social and environmental changes for which they need to be prepared to adapt and...     

An efficient nonlinear approach for removing fixed-value impulse noise from grayscale images

The latest-generation earth observation instruments on airborne and satellite platforms are currently producing an almost continuous high-dimensional data stream. This exponentially growing data poses a new challenge for real-time image processing and recognition. Making full and effective use of the spectral information and spatial structure information of high-resolution remote sensing image is the key to the processing and recognition of high-resolution remote sensing data. In this paper, the adaptive multipoint moment estimation (AMME) stochastic optimization algorithm is proposed for the first time by using the finite lower-order moments and adding the estimating points. This algorithm not only reduces the probability of local optimum in the learning process, but also improves the convergence rate of the convolutional neural network (Lee Cun et al. in Advances in neural information processing systems, 1990). Second, according to the remote sensing image with characteristics of complex background and small sensitive targets, and by automatic discovery, locating small targets, and giving high weights, we proposed a feature extraction method named weighted pooling to further improve the performance of real-time image recognition. We combine the AMME and weighted pooling with the spatial pyramid representation (Harada et al. in Comput Vis Pattern Recognit 1617–1624, 2011) algorithm to form a new, multiscale, and multilevel real-time image recognition model and name it weighted spatial pyramid networks (WspNet). At the end, we use the MNIST, ImageNet, and natural disasters under remote sensing data sets to test WspNet. Compared with other real-time image recognition models, WspNet achieve a new state of the art in terms of convergence rate and image feature extraction compared with conventional stochastic gradient descent method [like AdaGrad, AdaDelta and Adam (Zeiler in Comput Sci, 2012; Kingma and Ba in Comput Sci, 2014; Duchi et al. in J Mach Learn Res 12(7):2121–2159, 2011] and pooling method [like max-pooling, avg-pooling and stochastic-pooling (Zeiler and Fergus in stochastic-pooling for regularization of deep convolutional neural networks, 2013)].     

Exploring the Ordered Weighted Averaging Operator Knowledge Domain: A Bibliometric Analysis

Ordered weighted averaging (OWA) operator has been received increasingly widespread interest since its appearance in 1988. Recently, a topic search with the keywords “ordered weighted averaging operator” or “OWA operator” on Web of Science (WOS) found 1231 documents. As the publications about OWA operator increase rapidly, thus a scientometric analysis of this research field and discovery of its knowledge domain becomes very important and necessary. This paper studies the publications about OWA operator between 1988 and 2015, and it is based on 1213 bibliographic records obtained by using topic search from WOS. The disciplinary distribution, most cited papers, influential journals, as well as influential authors are analyzed through citation and cocitation analysis. The emerging trends in OWA operator research are explored by keywords and references burst detection analysis. The research methods and results in this paper are meaningful for researchers associated with OWA operator field to understand the knowledge domain and establish their own future research direction.     

On the Stability of the Quadruple Solutions of the Forward Kinematic Problem in Analytic Parallel Robots

Many parallel robots can change between different assembly modes (solutions of the forward kinematic problem) without crossing singularities, either by enclosing cusps or alpha-curves of the planar sections of their singularity loci. Both the cusps and the alpha-curves are stable singularities, which do not disappear under small perturbations of the geometry of the robot. Recently, it has been shown that some analytic parallel robots can also perform these nonsingular changes of assembly mode by encircling isolated points of their singularity loci at which the forward kinematic problem admits solutions with multiplicity four. In this paper, we study the stability of these quadruple solutions when the design of the robot deviates from the analytic geometry, and we show that such quadruple solutions are not stable since the isolated singular points at which they occur degenerate into closed deltoid curves. However, we also demonstrate that, although the quadruple solutions are unstable, the behavior of the robot when moving around them is practically unaffected by the perturbations from the analytic geometry. This means that the robot preserves its ability to perform nonsingular transitions by enclosing the quadruple solutions, even when its geometry is not exactly analytic due to small manufacturing tolerances.     

Comparison of the effects of dietary sunflower oil and virgin olive oil on rat exocrine pancreatic secretion <Emphasis Type="Italic">in vivo</Emphasis>

The aim of this study was to investigate the functional consequences in vivo of adapting the rat exocrine pancreas to different dietary fats. Weanling rats were fed diets containing 10 wt% virgin olive oil or sunflower oil for 8 wk. We then examined resting and cholecystokinin-octapeptide (CCK-8)-stimulated pancreatic secretion in the anesthetized animals. To confirm a direct influence of the type of fat upon the gland, the FA composition of pancreatic membranes as well as tissue protein and amylase content were determined in separate rats. The membrane FA profile was profoundly altered by the diets, reflecting the type of dietary fat given, although this was not paralleled by variations in the pancreatic content of protein or amylase. Nevertheless, dietary intake of oils evoked different effects on in vivo secretory activity. Resting flow rate and amylase output were significantly (P<0.05) enhanced by sunflower oil feeding. Time course changes in response to CCK-8 infusion also showed a different pattern in each group. Secretion of fluid, protein, and amylase increased markedly in all animals, reaching a maximum within 20–40 min of infusion that was followed by a dramatic decline in both groups. In the sunflower oil group, this resulted in values reaching the resting level as soon as 60 min after CCK-8 infusion was begun. However, after the initial decline, olive oil group values showed a prolonged plateau elevation above the baseline (P<0.05) that was maintained for at least the infusion time. In addition, a positive correlation between flow rate and both protein concentration and amylase activity existed in the olive oil group, but not in the sunflower oil group. The precise mechanism by which these effects are produced remains to be elucidated.