A geostatistical algorithm to reproduce lateral gradual facies transitions: Description and implementation

Valid representations of geological heterogeneity are fundamental inputs for quantitative models used in managing subsurface activities. Consequently, the simulation of realistic facies distributions is a significant aim. Realistic facies distributions are typically obtained by pixel-based, object-based or process-based methods. This work presents a pixel-based geostatistical algorithm suitable for reproducing lateral gradual facies transitions (LGFT) between two adjacent sedimentary bodies. Lateral contact (i.e. interfingering) between distinct depositional facies is a widespread geometric relationship that occurs at different scales in any depositional system. The algorithm is based on the truncation of the sum of a linear expectation trend and a random Gaussian field, and can be conditioned to well data. The implementation introduced herein also includes subroutines to clean and geometrically characterize the obtained LGFT. The cleaned sedimentary body transition provides a more appropriate and realistic facies distribution for some depositional settings. The geometric measures of the LGFT yield an intuitive measure of the morphology of the sedimentary body boundary, which can be compared to analogue data. An example of a LGFT obtained by the algorithm presented herein is also flow simulated, quantitatively demonstrating the importance of realistically reproducing them in subsurface models, if further flow-related accurate predictions are to be made.     

The MarineGrid project in Ireland with Webcom

The 1999–2007 Irish National Seabed Survey is one of the largest ocean floor mapping projects ever attempted. Its aim is to map the ocean floor of the Irish territorial waters (approximately $525000{\mathrm{km}}^2$). To date, the Geological Survey of Ireland has gathered in excess of 4 TB of multibeam sonar data from the Irish National Seabed, and this data set is expected to exceed 10 TB upon completion. The main challenge that arises from having so much data is how to extract accurate information given the size of the data set. Geological interpretation is carried out by visual inspection of bathymetric patterns. The size of this, and similar, data sets renders the extraction of knowledge by human observers infeasible. Consequently, the focus has turned to using artificial intelligence and computational methods for assistance. The commercial and environmental sensitivity of the data means that secure data processing and transmission are of paramount importance. This has lead to the creation of the MarineGrid project within the Grid-Ireland organisation. New methods have been developed for statistical analysis of bathymetric information specifically for automated geological interpretation of rock types on the sea floor and feature extraction from the sea floor. We present a discussion on how to provide Marine and Geological researchers convenient yet secure access to resources that make use of grid technologies including pre-written algorithms in order to exploit the Irish National Seabed Survey data archive.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

Agent mobility architecture based on IEEE-FIPA standards

Mobile agents are autonomous software entities driven by a set of goals and tasks. Reactivity, social ability, autonomy, the ability to move to different network locations, and the weak agent notion of proactiveness, allow for autonomous processing of distributed information according to their environment (context awareness).Although agent mobility has been devised for homogeneous environments, deployment of agent mobility in heterogeneous environments has been hindered by the absence of a common set of interoperation rules and ontologies for different agent middlewares.In this article, an agent migration model based on the communication standards of the IEEE-FIPA organisation is proposed. The approach described encompasses the definition of several specifications to achieve interoperability in the migration process in heterogeneous environments.The model provides a basic and extensible common migration process, which is flexible enough to support different kinds of migration methods and future upgrades. It is completely independent of any specific middleware implementation.     

COBRA: Compression of the Basis for PCA Represented Animations

In this paper, we present an extension of dynamic mesh compression techniques based on PCA. Such representation allows very compact representation of moving 3D surfaces; however, it requires some side information to be transmitted along with the main data. The biggest part of this information is the PCA basis, and since the data can be encoded very efficiently, the size of the basis cannot be neglected when considering the overall performance of a compression algorithm.
We present a new work in this area, as none of the papers about PCA based compression really addresses this issue. We will show that for an efficient and accurate encoding there are better choices than even sophisticated algorithms such as LPC.
We will present results showing that our approach can reduce the size of the basis by 90% with respect to direct encoding, which can lead to approximately 25% increase of performance of the compression algorithm without any significant loss of accuracy. Such improvement moves the performance of the PCA encoder beyond the performance of current state of the art dynamic mesh compression algorithms, such as the recently adopted MPEG standard, FAMC.     

Complexity classes for self-assembling flexible tiles

We present a theoretical model for self-assembling DNA tiles with flexible branches. We encode an instance of a “problem” as a pot of such tiles for which a “solution” is an assembled complete complex without any free sticky ends. Using the number of tiles in an assembled complex as a measure of complexity we show how NTIME classes (such as NP and NEXP) can be represented with corresponding classes of the model.     

Learning Fast Emulators of Binary Decision Processes

Computation time is an important performance characteristic of computer vision algorithms. The paper shows how existing (slow) binary decision algorithms can be approximated by a (fast) trained WaldBoost classifier. WaldBoost learning minimises the decision time of the classifier while guaranteeing predefined precision. We show that the WaldBoost algorithm together with bootstrapping is able to efficiently handle an effectively unlimited number of training examples provided by the implementation of the approximated algorithm. Two interest point detectors, the Hessian-Laplace and the Kadir-Brady saliency detectors, are emulated to demonstrate the approach. Experiments show that while the repeatability and matching scores are similar for the original and emulated algorithms, a 9-fold speed-up for the Hessian-Laplace detector and a 142-fold speed-up for the Kadir-Brady detector is achieved. For the Hessian-Laplace detector, the achieved speed is similar to SURF, a popular and very fast handcrafted modification of Hessian-Laplace; the WaldBoost emulator approximates the output of the Hessian-Laplace detector more precisely.     

Unmanned Aerial Vehicle Localization Based on Monocular Vision and Online Mosaicking

This paper presents a new approach for vision-based UAV localization, using mosaics as environment representations. Inter-image motions are used to estimate the motion of the UAV. Online mosaicking is applied to reduce the impact of the accumulative errors in UAV position estimation. A new method to build an stochastic mosaic given the image-to-image homographies is detailed. The mosaic consists of a network of inter-image relations, and is used to create a consistent view of the environment of the UAV and hence, to detect the drift in position estimation by using the mosaic as a resource. The technique could be called simultaneous localization and mosaicking. This technique is specially suitable for monitoring and surveillance tasks in which the UAV will repeatedly cover the same area. The paper also shows experimental results with real UAVs where the benefits of the proposed method are evident.     

Characterizing the measures on the unit circle with exact quadrature formulas in the space of polynomials

In the present paper we characterize the measures on the unit circle for which there exists a quadrature formula with a fixed number of nodes and weights and such that it exactly integrates all the polynomials with complex coefficients. As an application we obtain quadrature rules for polynomial modifications of the Bernstein measures on [−1,1], having a fixed number of nodes and quadrature coefficients and such that they exactly integrate all the polynomials with real coefficients.     

Broadband system to increase bitrate in train communication networks

MVB (Multifunction Vehicle Bus), defined in IEC 61375, has been broadly adopted as the communication standard between embedded control systems on-board modern trains. In this work a new method to take advantage of the full bandwidth of the channel using an OFDM technique is described. With this new method it is possible to share the physical medium between standard MVB traffic and new OFDM traffic. A 90 Mbps theoretical bitrate can be achieved. The results of this work have been validated in a test bench including standard MVB nodes transmitting on a line similar to a real vehicle bus.