A numerical modelling for the extraction of decay regions from color images of monuments

An innovative application focused on the segmentation of decay zones from images of stone materials is presented. The adopted numerical approach to extract decay regions from the color images of monuments provides a tool that helps experts analyze degraded regions by contouring them. In this way even if the results of the proposed procedure depend on the evaluation of experts, the approach can be a contribution to improving the efficiency of the boundary detection process. The segmentation is a process that allows an image to be divided into disjoint zones so that partitioned zones contain homogeneous characteristics. The numerical method, used to segment color images, is based on the theory of interface evolution, which is described by the eikonal equation. We adopted the fast marching technique to solve the upwind finite difference approximation of the eikonal equation. The fast marching starts from a seed point in the region of interest and generates a front which evolves according to a specific speed function until the boundary of the region is identified. We describe the segmentation results obtained with two speed functions, attained by the image gradient computation and color information about the object of interest. Moreover, we present the extension of the working modality of the method by introducing the possibility to extract the regions not only in a local way but also in a global way on the entire image. In this case, in order to improve the segmentation efficiency the application of the fast marching technique starts with more seed points defined as seed regions. The study case concerns the impressive remains of the Roman Theatre in the city of Aosta (Italy). In the image segmentation process the color space L^∗a^∗b^∗$L^{\ast }{a}^{\ast }{b}^{\ast }$ is utilized.     

Satellite-based estimates of groundwater storage variations in large drainage basins with extensive floodplains

This study presents monthly estimates of groundwater anomalies in a large river basin dominated by extensive floodplains, the Negro River Basin, based on the synergistic analysis using multisatellite observations and hydrological models. For the period 2003-2004, changes in water stored in the aquifer is isolated from the total water storage measured by GRACE by removing contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by WGHM and LaD hydrological models. The groundwater anomalies show a realistic spatial pattern compared with the hydrogeological map of the basin, and similar temporal variations to local in situ groundwater observations and altimetry-derived level height measurements. Results highlight the potential of combining multiple satellite techniques with hydrological modeling to estimate the evolution of groundwater storage.     

An approach to analyzing and planning post-merger IS integration: Insights from two field studies

Information systems (IS) integration is among the most challenging tasks in corporate mergers and acquisitions (M&As). In this paper we propose and illustrate the use of an approach to analyzing and planning post-merger IS integration that extends general theory for IS planning, considering the specific characteristics of the M&A context. We highlight that planning effectiveness is possible to achieve in fundamentally different ways, dependent on the characteristics of the merger or acquisition at hand.

Optimizing multiple dimensional queries simultaneously in multidimensional databases

Some significant progress related to multidimensional data analysis has been achieved in the past few years, including the design of fast algorithms for computing datacubes, selecting some precomputed group-bys to materialize, and designing efficient storage structures for multidimensional data. However, little work has been carried out on multidimensional query optimization issues. Particularly the response time (or evaluation cost) for answering several related dimensional queries simultaneously is crucial to the OLAP applications. Recently, Zhao et al. first exploited this problem by presenting three heuristic algorithms. In this paper we first consider in detail two cases of the problem in which all the queries are either hash-based star joins or index-based star joins only. In the case of the hash-based star join, we devise a polynomial approximation algorithm which delivers a plan whose evaluation cost is $ O(n^{\epsilon }$) times the optimal, where n is the number of queries and is a fixed constant with . We also present an exponential algorithm which delivers a plan with the optimal evaluation cost. In the case of the index-based star join, we present a heuristic algorithm which delivers a plan whose evaluation cost is n times the optimal, and an exponential algorithm which delivers a plan with the optimal evaluation cost. We then consider a general case in which both hash-based star-join and index-based star-join queries are included. For this case, we give a possible improvement on the work of Zhao et al., based on an analysis of their solutions. We also develop another heuristic and an exact algorithm for the problem. We finally conduct a performance study by implementing our algorithms. The experimental results demonstrate that the solutions delivered for the restricted cases are always within two times of the optimal, which confirms our theoretical upper bounds. Actually these experiments produce much better results than our theoretical estimates. To the best of our knowledge, this is the only development of polynomial algorithms for the first two cases which are able to deliver plans with deterministic performance guarantees in terms of the qualities of the plans generated. The previous approaches including that of [ZDNS98] may generate a feasible plan for the problem in these two cases, but they do not provide any performance guarantee, i.e., the plans generated by their algorithms can be arbitrarily far from the optimal one. Received: July 21, 1998 / Accepted: August 26, 1999     

Digital Image Analysis to Standardize a Photometric Method in Colorimetric Quantification

Abstract

Techniques applying digital images increasingly have been used in biology, medicine, physics, and other research areas. The image coordinates can represent light intensities values to be detected by a CCD. Based on this concept, a photometric system composed of a LED source and a digital camera as a detector was used for optical density measurements. Standards for permanganate, glucose, and protein solutions were determined by colorimetric methods using our device. Samples of protein of Pasteurella mutocida bacteria membrane and, also, fractions of rabbit kidney membrane, rich in Na, K‐ATPase, with unknown concentrations were dosed through the Hartree method using our photometric system.     

The road to intelligence

It is argued that robotic platforms are the way forward towards building intelligent systems, where multiple sensors and manipulation are used for cognitive processes. It is also argued that the cue for developing the right architecture for such a system is human language.     

Least squares support vector machines with tuning based on chaotic differential evolution approach applied to the identification of a thermal process

In the past decade, support vector machines (SVMs) have gained the attention of many researchers. SVMs are non-parametric supervised learning schemes that rely on statistical learning theory which enables learning machines to generalize well to unseen data. SVMs refer to kernel-based methods that have been introduced as a robust approach to classification and regression problems, lately has handled nonlinear identification problems, the so called support vector regression. In SVMs designs for nonlinear identification, a nonlinear model is represented by an expansion in terms of nonlinear mappings of the model input. The nonlinear mappings define a feature space, which may have infinite dimension. In this context, a relevant identification approach is the least squares support vector machines (LS-SVMs). Compared to the other identification method, LS-SVMs possess prominent advantages: its generalization performance (i.e. error rates on test sets) either matches or is significantly better than that of the competing methods, and more importantly, the performance does not depend on the dimensionality of the input data. Consider a constrained optimization problem of quadratic programing with a regularized cost function, the training process of LS-SVM involves the selection of kernel parameters and the regularization parameter of the objective function. A good choice of these parameters is crucial for the performance of the estimator. In this paper, the LS-SVMs design proposed is the combination of LS-SVM and a new chaotic differential evolution optimization approach based on Ikeda map (CDEK). The CDEK is adopted in tuning of regularization parameter and the radial basis function bandwith. Simulations using LS-SVMs on NARX (Nonlinear AutoRegressive with eXogenous inputs) for the identification of a thermal process show the effectiveness and practicality of the proposed CDEK algorithm when compared with the classical DE approach.     

Comments on “A novel dead time compensator for stable processes with long dead times” [Journal of Process Control 22 (2012) 612–625]

This short communication analyzes the results recently presented in the paper “On a novel dead time compensator for stable processes with long dead times” published in the Journal of Process Control. In the mentioned paper it is argued that the proposed strategy, called modified Smith predictor (MSP), gives better performance than the filtered Smith predictor (FSP) dead-time compensator for stable processes with dead time. In fact MSP has the same structure as FSP and only some specific tuning rules of the filters are proposed. Therefore, in this work some aspects of the comparative analysis and tuning rules presented in the referred paper are discussed to show that MSP is a particular case of FSP and that for some particular cases its tuning rule does not allow for a good closed-loop response. Some simulation case studies are used to illustrate these aspects.