A decision support system for interactive decision making - Part II: analysis and output interpretation

For pt.I see ibid., p.42-55 (2003). The development of a comprehensive decision support system, GMCR II, for the systematic study of real-world interactive decision problems is presented. The companion paper (Part I), discusses how GMCR II elicits, stores, and manages conflict models; here (Part II), the focus is on GMCR IIs analysis and output interpretation subsystems. Specifically, this paper describes the powerful and efficient analysis engine contained in GMCR II, its informative output presentation and interpretation facilities, and a number of follow-up analyses. Furthermore, an illustrative case study is used to demonstrate how GMCR II can be conveniently applied in practice.     

Control system design on a power-split CVT for high-power agricultural tractors

The problem considered in this paper is the design and tuning of the control system of a power-split continuously variable transmission (CVT) used in high-power tractors. Power-split CVTs are characterized by the combination of a traditional mechanical transmission and by a continuously-variable transmission. This guarantees, at the same time, smooth variations of the transmission-ratio and high efficiency of the overall transmission system. The control architecture of an hydrostatic power-split CVT is constituted by three main parts: 1) servo-controller on the current of the valve which drives the hydraulic transmission; 2) a servo-controller on the hydraulic transmission-ratio; and 3) a synchronizer which coordinates the hydraulic and the mechanical parts of the CVT. In this work, these three controllers are fully developed, including: design, implementation, and evaluation on an experimental system.     

Impact of Reaction Conditions on MnO2 Genesis during Permanganate Oxidation

To enhance the understanding of the behavior and effects of the precipitation of MnO2 particles in the subsurface generated during in situ chemical oxidation (ISCO) using permanganate, laboratory batch experiments were completed to examine the influence that varied reaction matrix conditions have on the generation and properties of manganese oxides. The conditions examined include organic material type and concentration, permanganate concentration, pH, and the presence of calcium (as a representative divalent cation) in solution. Experimental studies included: (1) spectrophotometric examination of permanganate depletion and manganese oxides generation over time during reactions with trichloroethene; (2) scanning electron microscopy analyses of manganese particle morphology; (3) particle size distribution (filtration) characterization studies; and (4) optical particle sizing and numeration studies. Bench-scale, batch experiments were conducted to focus on fundamental chemical properties affecting particle development under varied potential environmental conditions. The amount of manganese oxides particles that develop, grow, and potentially settle as a result of permanganate ISCO of organic contaminants is a function of the particle size and concentration, the time allowed for particle development, and the impact of matrix conditions on the ability of particles to agglomerate.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.     

Finite element analysis of advanced multilayer capacitors

We establish a systematic methodology to design and analyse electromagnetic components such as advanced multilayer ceramic capacitors (MLCCs) using the finite element (FE) method. We employ a coupled formulation to compute the interaction between the electric and magnetic fields. Unlike a linear distribution of current assumed in the circuit model, an accurate electrostatic solution to model the entire advanced MLCCs (4 × 4 × 27 = 432 cells) is presented. The FE solution is used to compute the lumped parameters for a range of frequencies. These lumped parameters are then used to compute the parasitic elements of the MLCCs. We introduce two algorithms to efficiently analyse the behaviour of a capacitor with changing frequency. The lower frequency (much below the self‐resonant frequency of the capacitor) algorithm separates the effect of the electric and magnetic fields and reduces the computational effort required to solve the FE problem, whereas, the high‐frequency algorithm couples the effect between the electric and the magnetic fields. We use these algorithms in conjunction with a new multiple scale technique to effectively determine the small values of R, L and C in MLCCs. The formulation, the implementation, and the numerical results demonstrate the efficacy of the present FE formulation and establish a systematic methodology to design and analyse advanced electromagnetic components. Copyright © 2003 John Wiley & Sons, Ltd.     

Mass Transfer in a Flat Gas/Liquid Interface using non‐Newtonian Media

Gas/liquid mass transfer has been investigated using a stirred vessel gas/liquid contactor using non‐Newtonian media and carbon dioxide as absorbent and gas phase, respectively. The volumetric mass transfer coefficients at different operational variables have been determined. Non‐Newtonian media (liquid phase) were prepared as aqueous solutions of sodium carboxymethyl cellulose salt. The influence of the rheological properties, polymer concentration, stirring rate, and gas flow rate on mass transfer was studied for these liquid phases. Kinematic viscosity and density experimental data were used to calculate the average molecular weight corresponding to the polymer employed. The Ostwald model has been used to fit the rheological behavior of aqueous solutions of the polymer employed as absorbent phase. Reasonably good agreement was found between the predictions of the proposed models and the experimental data of mass transfer coefficients.     

Asymptotic performance of single parity-check product codes

This article investigates the asymptotic performance of single parity-check (SPC) product codes (PCs) from a decoding point of view. Specifically, the probability of bit error is bounded before and after the decoding of each dimension, similar to the analysis of "iterated codes" by Elias (1954). It is shown that the asymptotic probability of bit error can be driven to zero as the number of dimensions, and hence the block length, increases at signal-to-noise ratios (SNRs) within 2 dB of capacity over the additive white Gaussian noise (AWGN) channel.     

High-efficiency LEDs of 1.6–2.4 µm spectral range for medical diagnostics and environment monitoring

High efficient LED structures covering the spectral range of 1.6–2.4 μm have been developed on the basis of GaSb and its solid solutions. The electroluminescent characteristics and their temperature and current dependences have been studied. The radiative and nonradiative recombination mechanisms and their effect on the quantum efficiency have been investigated. A quantum efficiency of 40–60% has been obtained in the quasi-steady mode at room temperature. A short-pulse optical power of 170 mW was reached. __________ Translated from Fizika i Tekhnika Poluprovodnikov, Vol. 37, No. 8, 2003, pp. 996–1009. Original Russian Text Copyright ? 2003 by Stoyanov, Zhurtanov, Astakhova, Imenkov, Yakovlev.     

A new mobile robot control approach via fusion of control signals.

This paper proposes an alternative approach to address the problem of coordinating behaviors in mobile robot navigation: fusion of control signals. Such approach is based on a set of two decentralized information filters, which accomplish the data fusion involved. Besides these two fusion engines, control architectures designed according to this approach also embed a set of different controllers that generate reference signals for the robot linear and angular speeds. Such signals are delivered to the two decentralized information filters, which estimate suitable overall reference signals for the robot linear and angular speeds, respectively. Thus, the background for designing such control architectures is provided by the nonlinear systems theory, which makes this approach different from any other yet proposed. This background also allows checking control architectures designed according to the proposed approach for stability. Such analysis is carried out in the paper, and shows that the robot always reaches its final destination, in spite of either obstacles along its path or the environment layout. As an example, a control architecture is designed to guide a mobile robot in an experiment, whose results allows checking the good performance of the control architecture and validating the design approach proposed as well.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.