Caving performance through the integration of microseismic activity and numerical modeling at DOZ-PT Freeport, Indonesia

This article describes an undergoing research at PT Freeport,Indonesia,in which the main goal is to use the microseismic information recorded as a result of mining to analyze cave propagation and stress performance on the actual production and fixed in-frastructure.At the moment,several numerical experiments have been conducted to correlate the mining activity with the microseis-mic events using the data collected during year 2005 and 2006.As a result of the preliminary analysis a micro-and a macrocracking envelop were proposed on the basis of computation of stress behavior at the location of the events.Stresses have been computed us-ing standard elastic continuous boundary element models.The correlation between the average source radius and the stress perform-ance has provided a method to propose a macrocracking criterion.Several techniques have been tested to nucleate the microseismic activity around different geological features.This last attempt was aimed to look at potential overstresses induced over the undercut and extraction level drifts.A method was devised to integrate the microseismicity into a 3-dimensional ride distribution model.This model has shown to be very effective to quantify the overstress induced as a result of computing volumetric microseismieity density.The volumetric microseismic model showed to induce overstress up to 10 MPa over a period of two months.The future work will concentrate on the calibration of the integrated model with actual damage observations made at the current mining infrastructure.     

Application of position and inertial-rate control to a 2-DOF gyroscopic platform

This paper presents a control application for the inertial stabilization of a gyroscopic platform with two degrees of freedom (2-DOF). The purposes of this application are, first, to control the angular positions of the platform in the absence of inertial disturbances and second, to control velocities measured in an inertial frame, while rejecting the disturbances associated with moving components. With regard to the first objective, a switching-control strategy is proposed in order to reduce the effects of friction as the main source of undesirable non-linear behaviors. Regarding the inertial-rate control, a master–slave control structure is suggested to achieve the desired specifications. Simulation and experimental results are presented, showing the performance attained on a real platform.     

Granular computing neural-fuzzy modelling: A neutrosophic approach

Granular computing is a computational paradigm that mimics human cognition in terms of grouping similar information together. Compatibility operators such as cardinality, orientation, density, and multidimensional length act on both in raw data and information granules which are formed from raw data providing a framework for human-like information processing where information granulation is intrinsic. Granular computing, as a computational concept, is not new, however it is only relatively recent when this concept has been formalised computationally via the use of Computational Intelligence methods such as Fuzzy Logic and Rough Sets. Neutrosophy is a unifying field in logics that extents the concept of fuzzy sets into a three-valued logic that uses an indeterminacy value, and it is the basis of neutrosophic logic, neutrosophic probability, neutrosophic statistics and interval valued neutrosophic theory. In this paper we present a new framework for creating Granular Computing Neural-Fuzzy modelling structures via the use of Neutrosophic Logic to address the issue of uncertainty during the data granulation process. The theoretical and computational aspects of the approach are presented and discussed in this paper, as well as a case study using real industrial data. The case study under investigation is the predictive modelling of the Charpy Toughness of heat-treated steel; a process that exhibits very high uncertainty in the measurements due to the thermomechanical complexity of the Charpy test itself. The results show that the proposed approach leads to more meaningful and simpler granular models, with a better generalisation performance as compared to other recent modelling attempts on the same data set.     

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$G$.     

A curvature-based multiresolution automatic karyotyping system

This paper presents a method to segment, characterise and pair a set of chromosomes in a cell of an eukaryotic organism. This method yields several new features: (i) chromosomes are captured at non-uniform resolution to minimise the problem instance; (ii) segmentation is adaptively conducted by means of a hierarchical structure in a fast way; (iii) the curvature of each chromosome is studied at high resolution by means of attentive steps; (iv) a very short and uncorrelated feature vector is extracted from curvature by analysing its spectral components; and (v) a multistage benchmark classifier is used to pair chromosomes according to shape and banding. The method has been tested with publicly available databases. Results were successfully compared to manual karyotypes. Received: 26 June 2000 / Accepted: 4 December 2001 Published online: 3 June 2003 Correspondence to: Cristina Urdiales García (e-mail: cris@dte.uma.es, Tel.: +34-952-132757, Fax: +34-952-131447)     

Insights on Aliasing Driven Instabilities for Advection Equations with Application to Gauss–Lobatto Discontinuous Galerkin Methods

We analyse instabilities due to aliasing errors when solving one dimensional non-constant advection speed equations and discuss means to alleviate these types of errors when using high order discontinuous Galerkin (DG) schemes. First, we compare analytical bounds for the continuous and discrete version of the PDEs. Whilst traditional \(L^2\) norm energy bounds applied to the discrete PDE do not always predict the physical behaviour of the continuous version of the equation, more strict elliptic norm bounds correctly bound the behaviour of the continuous PDE. Having derived consistent bounds, we analyse the effectiveness of two stabilising techniques: over-integration and split form variations (conservative, non-conservative and skew-symmetric). Whilst the former is shown to not alleviate aliasing in general, the latter ensures an aliasing-free solution if the splitting form of the discrete PDE is consistent with the continuous equation. The success of the split form de-aliasing is restricted to DG schemes with the summation-by-parts simultaneous-approximation-term properties (e.g. DG with Gauss–Lobatto points). Numerical experiments are included to illustrate the theoretical findings.     

A Fully Syntactic AC-RPO

We present the first fully syntactic (i.e., non-interpretation-based) AC-compatible recursive path ordering (RPO). It is simple, and hence easy to implement, and its behaviour is intuitive as in the standard RPO. The ordering is AC-total and defined uniformly for both ground and nonground terms, as well as for partial precedences. More important, it is the first one that can deal incrementally with partial precedences, an aspect that is essential, together with its intuitive behaviour, for interactive applications such as Knuth–Bendix completion.     

Network-aware heuristics for inter-domain meta-scheduling in Grids

Grid computing generally involves the aggregation of geographically distributed resources in the context of a particular application. As such resources can exist within different administrative domains, requirements on the communication network must also be taken into account when performing meta-scheduling, migration or monitoring of jobs. Similarly, coordinating efficient interaction between different domains should also be considered when performing such meta-scheduling of jobs. A strategy to perform peer-to-peer-inspired meta-scheduling in Grids is presented. This strategy has three main goals: (1) it takes the network characteristics into account when performing meta-scheduling; (2) communication and query referral between domains is considered, so that efficient meta-scheduling can be performed; and (3) the strategy demonstrates scalability, making it suitable for many scientific applications that require resources on a large scale. Simulation results are presented that demonstrate the usefulness of this approach, and it is compared with other proposals from literature.     

Analysis of thermal infrared data from the Digital Airborne Imaging Spectrometer

Thermal infrared data of the Digital Airborne Imaging Spectrometer (DAIS), whose channels 74-79 are in the 8-13 w m waveband region, were analysed with the aim of recovering land surface temperature (LST). DAIS images were acquired over an experimental site where field and laboratory emissivity measurements were performed, and these were used to recover the LST from the six DAIS thermal channels. Atmospheric correction of DAIS data was calculated by means of a nearby radiosounding and a radiative transfer model. DAIS derived LSTs were compared with ground measurements of LST made coincidentally for a few test fields, the central DAIS channels yielding temperatures up to 10°C higher than ground measurements. A linear calibration was performed using in situ measurements of temperature and emissivity for two reference fields, and the large differences in temperature were then considerably reduced. Temperatures obtained from DAIS channel 79 agreed with the in situ measurements within - 2°C. This channel seemed the most reliable for deriving accurate LSTs in the dataset analysed here.     

Modeling of the relative humidity via functional networks and control of the temperature via classic controls for a bird incubator

The control of the relative humidity and the temperature is important for the birds to be born. It is not easy to control the relative humidity, but it is possible to obtain the measure of the relative humidity as a consequence of the control of the temperature in a bird incubator. In this article, (1) the mathematical model for the control of temperature in the bird incubator is presented, (2) a functional network to approximate the relative humidity behavior in the bird incubator is proposed, (3) a control for the temperature in the bird incubator is proposed, the error of the proportional control applied to the mathematical model of the temperature of the bird incubator is assured to be uniformly stable, (4) the comparison results of four classic control laws for the control of the temperature considering the proposed mathematical model of the temperature and the functional network to approximate the relative humidity behavior in the bird incubator are presented.