A new approach for determining stability constants of metal ion complexes in aquatic systems based on flow injection-ion exchange-flame atomic absorption spectrometry coupling

A method based an ion exchange(IE)-atomic absorption spectrometry(AAS) coupled by flow techniques, allowing the determination of formation constants of, at least, the first species of complex systems, in aqueous solution, was developed.The IE-AAS coupling reduces significantly the number of experimental steps in comparison with IE batch methods, resulting in an important increase in analytical rate. The method is simple both from experimental and computational points of view, making possible its utilization by workers without special expertise in the field of complex equilibria in solution. on the other hand, taking into account mainly the amount of hollow cathode lamps available to date, the developed procedure may be applied, within certain limitations, to the study of many systems whose features prevent the use of traditional approaches.

A column generation approach to capacitated p-median problems

The Capacitated p-median problem (CPMP) seeks to solve the optimal location of p facilities, considering distances and capacities for the service to be given by each median. In this paper we present a column generation approach to CPMP. The identified restricted master problem optimizes the covering of 1-median clusters satisfying the capacity constraints, and new columns are generated considering knapsack subproblems. The Lagrangean/surrogate relaxation has been used recently to accelerate subgradient like methods. In this work the Lagrangean/surrogate relaxation is directly identified from the master problem dual and provides new bounds and new productive columns through a modified knapsack subproblem. The overall column generation process is accelerated, even when multiple pricing is observed. Computational tests are presented using instances taken from real data from Sao Jose dos Campos' city.

An approach of optimal sensitivity applied in the tertiary loop of the automatic generation control

This paper proposes an approach of optimal sensitivity applied in the tertiary loop of the automatic generation control. The approach is based on the theorem of non-linear perturbation. From an optimal operation point obtained by an optimal power flow a new optimal operation point is directly determined after a perturbation, i.e., without the necessity of an iterative process. This new optimal operation point satisfies the constraints of the problem for small perturbation in the loads. The participation factors and the voltage set point of the automatic voltage regulators (AVR) of the generators are determined by the technique of optimal sensitivity, considering the effects of the active power losses minimization and the network constraints. The participation factors and voltage set point of the generators are supplied directly to a computational program of dynamic simulation of the automatic generation control, named by power sensitivity mode. Test results are presented to show the good performance of this approach. (C) 2008 Elsevier B.V. All rights reserved.

A linear optimization approach to the combined production planning model

Two fundamental processes usually arise in the production planning of many industries. The first one consists of deciding how many final products of each type have to be produced in each period of a planning horizon, the well-known lot sizing problem. The other process consists of cutting raw materials in stock in order to produce smaller parts used in the assembly of final products, the well-studied cutting stock problem. In this paper the decision variables of these two problems are dependent of each other in order to obtain a global optimum solution. Setups that are typically present in lot sizing problems are relaxed together with integer frequencies of cutting patterns in the cutting problem. Therefore, a large scale linear optimizations problem arises, which is exactly solved by a column generated technique. It is worth noting that this new combined problem still takes the trade-off between storage costs (for final products and the parts) and trim losses (in the cutting process). We present some sets of computational tests, analyzed over three different scenarios. These results show that, by combining the problems and using an exact method, it is possible to obtain significant gains when compared to the usual industrial practice, which solve them in sequence. (C) 2010 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

A Lagrangian relaxation approach to a coupled lot-sizing and cutting stock problem

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A recursive approach to space resection using straight lines

An approach using straight lines as features to solve the photogrammetric space resection problem is presented. An explicit mathematical model relating straight lines, in both object and image space, is used. Based on this model, Kalman Filtering is applied to solve the space resection problem. The recursive property of the filter is used in an iterative process which uses the sequentially estimated camera location parameters to feedback to the feature extraction process in the image. This feedback process leads to a gradual reduction of the image space for feature searching, and consequently eliminates the bottleneck due to the high computational cost of the image segmentation phase. It also enables feature extraction and the determination of feature correspondence in image and object space in an automatic way, i.e., without operator interference. Results obtained from simulated and real data show that highly accurate space resection parameters are obtained as well as a progressive processing time reduction. The obtained accuracy, the automatic correspondence process, and the short related processing time show that the proposed approach can be used in many real-time machine vision systems, making possible the implementation of applications not feasible until now.

Extended Hierarchical Censored Production Rules (EHCPRs) system: An approach toward generalized knowledge representation

One common problem in all basic techniques of knowledge representation is the handling of the trade-off between precision of inferences and resource constraints, such as time and memory. Michalski and Winston (1986) suggested the Censored Production Rule (CPR) as an underlying representation and computational mechanism to enable logic based systems to exhibit variable precision in which certainty varies while specificity stays constant. As an extension of CPR, the Hierarchical Censored Production Rules (HCPRs) system of knowledge representation, proposed by Bharadwaj & Jain (1992), exhibits both variable certainty as well as variable specificity and offers mechanisms for handling the trade-off between the two. An HCPR has the form: Decision If(preconditions) Unless(censor) Generality(general_information) Specificity(specific_information). As an attempt towards evolving a generalized knowledge representation, an Extended Hierarchical Censored Production Rules (EHCPRs) system is suggested in this paper. With the inclusion of new operators, an Extended Hierarchical Censored Production Rule (EHCPR) takes the general form: Concept If (Preconditions) Unless (Exceptions) Generality (General-Concept) Specificity (Specific Concepts) Has_part (default: structural-parts) Has_property (default:characteristic-properties) Has_instance (instances). How semantic networks and frames are represented in terms of an EHCPRs is shown. Multiple inheritance, inheritance with and without cancellation, recognition with partial match, and a few default logic problems are shown to be tackled efficiently in the proposed system.

Transient stability indices from a hybrid approach

This paper deals with hybrid method for transient stability analysis combining time domain simulation and a direct method. Nowadays, the step-by-step simulation is the best available tool for allowing the uses of detailed models and for providing reliable results. The main limitation of this approach involves the large time of computational simulations and the absence of stability margin. On the other hand, direct methods, that demand less CPU time, did not show ample reliability and applicability yet. The best way seems to be using hybrid solutions, in which a direct method is incorporated in a time domain simulation tool. This work has studied a direct method using the transient potential and kinetic energy of the critical machine only. In this paper the critical machine is identified by a fast and efficient method, and the proposal is new for using to get stability margins from hybrid approaches. Results from systems, like 16-machine, show stability indices to dynamic security assessment. © 2001 IEEE.

Clarke's alpha, beta and zero components: A possible approach for the conceptual design of instrumentation compatible with IEEE Std. 1459-2000

The paper explains the conceptual design of instrumentation that measures electric quantities defined in the trial-use Std. 1459-2000. It is shown how the Instantaneous-Space-Phasor (ISP) approach, based on α, β, 0 components, can be used to monitor electric energy flow, evaluate the utilization of transmission line and quantify the level of harmonic pollution injected by nonlinear loads.

A neural approach to evaluate the effect of lightning in power transformers

This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. © 2009 The Berkeley Electronic Press. All rights reserved.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Exploring the multifactorial nature of autism through computational systems biology: Calcium and the Rho GTPase RAC1 under the spotlight

Autism is a neurodevelopmental disorder characterized by impaired social interaction and communication accompanied with repetitive behavioral patterns and unusual stereotyped interests. Autism is considered a highly heterogeneous disorder with diverse putative causes and associated factors giving rise to variable ranges of symptomatology. Incidence seems to be increasing with time, while the underlying pathophysiological mechanisms remain virtually uncharacterized (or unknown). By systematic review of the literature and a systems biology approach, our aims were to examine the multifactorial nature of autism with its broad range of severity, to ascertain the predominant biological processes, cellular components, and molecular functions integral to the disorder, and finally, to elucidate the most central contributions (genetic and/or environmental) in silico. With this goal, we developed an integrative network model for gene-environment interactions (GENVI model) where calcium (Ca2+) was shown to be its most relevant node. Moreover, considering the present data from our systems biology approach together with the results from the differential gene expression analysis of cerebellar samples from autistic patients, we believe that RAC1, in particular, and the RHO family of GTPases, in general, could play a critical role in the neuropathological events associated with autism. © 2013 Springer Science+Business Media New York.

On computational aspects of discrete Sobolev inner products on the unit circle

In this paper, we show how to compute in O(n2) steps the Fourier coefficients associated with the Gelfand-Levitan approach for discrete Sobolev orthogonal polynomials on the unit circle when the support of the discrete component involving derivatives is located outside the closed unit disk. As a consequence, we deduce the outer relative asymptotics of these polynomials in terms of those associated with the original orthogonality measure. Moreover, we show how to recover the discrete part of our Sobolev inner product. © 2013 Elsevier Inc. All rights reserved.

DNA for nano-bio scale computation of chemical formalisms using Higher Order Logic (HOL) and analysis using an interdisciplinary approach

Bio-molecular computing, 'computations performed by bio-molecules', is already challenging traditional approaches to computation both theoretically and technologically. Often placed within the wider context of ´bio-inspired' or 'natural' or even 'unconventional' computing, the study of natural and artificial molecular computations is adding to our understanding of biology, physical sciences and computer science well beyond the framework of existing design and implementation paradigms. In this introduction, We wish to outline the current scope of the field and assemble some basic arguments that, bio-molecular computation is of central importance to computer science, physical sciences and biology using HOL - Higher Order Logic. HOL is used as the computational tool in our R&D work. DNA was analyzed as a chemical computing engine, in our effort to develop novel formalisms to understand the molecular scale bio-chemical computing behavior using HOL. In our view, our focus is one of the pioneering efforts in this promising domain of nano-bio scale chemical information processing dynamics.

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)