Variable parameter and double sampling (X)over-bar charts in the presence of correlation: The Markov chain approach

The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.

Analytical approach to the metallomic of Nile tilapia (Oreochromis niloticus) liver tissue by SRXRF and FAAS after 2D-PAGE separation: Preliminary results

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Economic design of (X)over-bar charts with variable parameters: the Markov chain approach

This paper presents an economic design of (X) over bar control charts with variable sample sizes, variable sampling intervals, and variable control limits. The sample size n, the sampling interval h, and the control limit coefficient k vary between minimum and maximum values, tightening or relaxing the control. The control is relaxed when an (X) over bar value falls close to the target and is tightened when an (X) over bar value falls far from the target. A cost model is constructed that involves the cost of false alarms, the cost of finding and eliminating the assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A comprehensive study is performed to examine the economic advantages of varying the (X) over bar chart parameters.

Green chromatographic fingerprinting: An environmentally friendly approach for the development of separation methods for fingerprinting complex matrices

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Low voltage and variable-pressure scanning electron microscopy of fractured composites

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Albendazole sulfoxide enantiomers: Preparative chiral separation and absolute stereochemistry

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Bound states of the barium atom by the hyperspherical approach

We present a nonadiabatic hyperspherical calculation of the highly excited and low lying doubly excited states of the barium atom using effective potentials for the two optically active electrons' interactions. Within the hyperspherical adiabatic approach the investigation of the spectra is performed with potential curves and nonadiabatic couplings of a unique radial variable, which allows clear identification of the states. The convergence of energy is obtained within well established bound limits, and the precision is comparable to accurate configuration interaction calculations. A very good agreement with experimental results is obtained with only few nonadiabatic couplings. (C) 2004 American Institute of Physics.

Economic design of two-stage (X)over-bar charts: the Markov chain approach

When the (X) over bar chart is in use, samples are regularly taken from the process, and their means are plotted on the chart. In some cases, it is too expensive to obtain the X values, but not the values of a correlated variable Y. This paper presents a model for the economic design of a two-stage control chart, that is. a control chart based on both performance (X) and surrogate (Y) variables. The process is monitored by the surrogate variable until it signals an out-of-control behavior, and then a switch is made to the (X) over bar chart. The (X) over bar chart is built with central, warning. and action regions. If an X sample mean falls in the central region, the process surveillance returns to the (Y) over bar chart. Otherwise. The process remains under the (X) over bar chart's surveillance until an (X) over bar sample mean falls outside the control limits. The search for an assignable cause is undertaken when the performance variable signals an out-of-control behavior. In this way, the two variables, are used in an alternating fashion. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A study is performed to examine the economic advantages of using performance and surrogate variables. (C) 2003 Elsevier B.V. All rights reserved.

The non-adiabatic hyperspherical approach to the two-dimensional D- ion in the presence of a magnetic field

We have used the adiabatic hyperspherical approach to determine the energies and wave functions of the ground state and first excited states of a two-dimensional D- ion in the presence of a magnetic field. Using a modified hyperspherical angular variable, potential energy curves are analytically obtained, allowing an accurate determination of the energy levels of this system. Upper and lower bounds for the ground-state energy have been determined by a non-adiabatic procedure, as the purpose is to improve the accuracy of method. The results are shown to be comparable to the best variational calculations reported in the literature.

Separation of dielectric and space charge polarizations in CaCu3Ti4O12/CaTiO3 composite polycrystalline systems

The complex analysis of dielectric/capacitance is a very useful approach to separate different polarization contributions existing in polycrystalline ceramics. In this letter, the authors use this type of spectroscopic analysis to separate the bulk's dielectric dipolar relaxation contributions from the polarization contribution due to space charge in the grain boundaries of a CaCu3Ti4O12/CaTiO3 polycrystalline composite system. The bulk dielectric dipolar relaxation was attributed to the self-intertwined domain structures from the CaCu3Ti4O12 phase coupled to the dipole relaxation from the CaTiO3 phase, while the space charge relaxation was attributed to the Schottky-type potential barrier responsible for the highly non-Ohmic properties observed in this composite polycrystalline system.

Mechanistic approach to predict real machining time for milling free-form geometries applying high feed rate

An accurate estimate of machining time is very important for predicting delivery time, manufacturing costs, and also to help production process planning. Most commercial CAM software systems estimate the machining time in milling operations simply by dividing the entire tool path length by the programmed feed rate. This time estimate differs drastically from the real process time because the feed rate is not always constant due to machine and computer numerical controlled (CNC) limitations. This study presents a practical mechanistic method for milling time estimation when machining free-form geometries. The method considers a variable called machine response time (MRT) which characterizes the real CNC machine's capacity to move in high feed rates in free-form geometries. MRT is a global performance feature which can be obtained for any type of CNC machine configuration by carrying out a simple test. For validating the methodology, a workpiece was used to generate NC programs for five different types of CNC machines. A practical industrial case study was also carried out to validate the method. The results indicated that MRT, and consequently, the real machining time, depends on the CNC machine's potential: furthermore, the greater MRT, the larger the difference between predicted milling time and real milling time. The proposed method achieved an error range from 0.3% to 12% of the real machining time, whereas the CAM estimation achieved from 211% to 1244% error. The MRT-based process is also suggested as an instrument for helping in machine tool benchmarking.

New approach of induction machine drive using an adaptive digital PID controller with gain planning based on artificial neural networks

The present work introduces a new strategy of induction machines speed adjustment using an adaptive PID (Proportional Integral Derivative) digital controller with gain planning based on the artificial neural networks. This digital controller uses an auxiliary variable to determine the ideal induction machine operating conditions and to establish the closed loop gain of the system. The auxiliary variable value can be estimated from the information stored in a general-purpose artificial neural network based on CMAC (Cerebellar Model Articulation Controller).

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.

Separation of flavonoids and naphthopyrones from four Brazilian Paepalanthus species by droplet countercurrent chromatography

A general procedure was developed for the simultaneous separation of flavonoids and naphthopyrones from the polar extracts of the capitula from Brazilian everlasting plants is described. The ethanolic extracts of several species from the Paepalanthus genus (Eriocaulaceae) were fractionated by droplet countercurrent chromatography followed by column chromatography on pvp and sephadex LH-20. The isolated compounds were identified by spectrometric analysis and comparison with literature data. This approach led to the isolation of 9-O-β-D-glucopyranosylpaepalantine (1), 9-O-β-D-glucopyranosyl (1→6)allopyranosylpaepalantine (2), along with the flavonoids 6-methoxykaempferol (3), 3-O-β-D-glucopyranosyl-6-methoxykaempferol (4), patuletin (5), 3-Oβ-D-rutinosylpatuletin (6), 7-O-β-D-glucopyranosylquercetagetin (7), 5,7,4'-trihydroxy-6,3'-dimethoxyflavone (8) and 5,7,4'-trihydroxy-6,3'-dimethoxyflavonol (9).

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.