STATISTICAL ASSOCIATION LEARNING OF THE MARKOV DECISION PROCESS

A neural computing approach to the Markov decision problem is presented. The method makes use of historical records of rewards as inputs and average long-run incomes per epoch as targets for training a backpropagation network to associate the two quantities, without a priori knowledge of the state transition probabilities. Estimation of the long-run income, given a new reward matrix as input, is interpreted as a statistical-association learning problem. Following the training, the relevant functional relationship between the income (output) and the reward (input), that has been learned by the network, can be used to compute an unknown expected income. The present study examines network generalization to new inputs, considering the effects of different topological designs and the characteristics of training samples on neural computing accuracy. Successful performance of the best design, which is determined directly from the underlying mathematical model of the Markov decision problem, is demonstrated by a computer simulation experiment.     

Studies on urethane–allophanate networks based on hydroxyl‐terminated polybutadiene: Modeling of network parameters and correlation to mechanical properties

Hydroxyl‐terminated polybutadiene (HTPB)‐based allophanate–urethane networks were prepared by reacting HTPB with di‐isocyanates, such as toluene–di‐isocyanate (TDI), isophorone–di‐isocyanate (IPDI), and 4,4′‐di(socyanatocyclohexyl)methane (H₁₂MDI) at stoichiometric ratios (r‐values) ranging from 1.0 to 1.5. The networks were characterized for mechanical and swell properties. The network parameters, such as “X,” which is the fraction of urethane groups involved in the allophanate formation, and effective chain length (L_x) were calculated from experimental crosslink density values determined from swell data, using α‐model equations developed by Marsh. Excellent linear correlations were obtained between mechanical properties and the calculated network parameters. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 101: 2986–2994, 2006     

Improving production planning by utilizing stochastic programming

The effects of fluctuating demand on production and inventory levels are important in manufacturing resource planning. Thus, the focus of this presentation is on aggregate production planning of manufacturing resources in order to satisfy stochastic demand for a family of products to minimize total costs that include production and inventory holding costs over a rolling horizon.

If it is assumed that, in a commercial setting, the demands are fixed, then the production plans generated by a mathematical programming procedure are not responsive to the actual fluctuations of stochastic demand in each time period.

The situation discussed here considers the case where demands are normally distributed with means and variances that are sequentially revised as new observations of demand are received over time. This assumption allows the probabilistic constraint to be converted to an equivalent linearly-constrained deterministic model. Extensions to the normality assumption are discussed. Also other ideas such as optimal control theory, learning and adaptive signal processing extensions are discussed as well.     

“Central Atoms” models for ternary silicate and alumino-silicate melts

The “Central Atoms” model presented by the authors in an earlier paper is extended to ternary silicate and alumino-silicate melts. The model is applied to the CaO-FeO-SiO₂ and the CaO-Al₂O₃-SiO₂ system. Use is made of the parameters from the relevant binaries only. The agreement between experimental and calculated isoactivity curves is good in all cases. Formerly Research Student, Department of Metallurgy, Indian Institute of Science, Bangalore-560 012, India     

Transient detection with an application to a chemical process

We propose a sequential test procedure for transient detections in a stochastic process which can be expressed as an autoregressive moving average (ARMA) model. Preliminary analysis shows that if an ARMA(p,q) time series exhibits a transient behavior, then its residuals behave as an ARMA(Q,Q) process, where Q ≤ p + q. Based on this fact, we derive a new sequential test to determine when a transient behavior occurs in a given ARMA time series. Simulation experiments conducted in this study show that the proposed test can detect the occurrence of a transient in the ARMA model. We also apply the proposed method to detect transient changes in the pH of an erythromycin salt.     

Studies on ferric oxide electrodes for the photo-assisted electrolysis of water

Results of the photoelectrochemical studies carried out with sintered discs of pure Fe₂O₃ and of Fe₂O₃ doped with TiO₂, SnO₂, ZrO₂ and Ta₂O₅ are compared and discussed. Flat band potential, saturation current and minority charge carrier diffusion length are higher for TiO₂-doped Fe₂O₃ samples than for other doped specimens. Ta₂O₅-doped Fe₂O₃ samples and SrFe₂O₄ have been found to be photo-inactive. The results are analysed in terms of depletion layer theory.     

Studies on the determination of surface deuterium in AISI 1062, 4037, and 4140 steels by secondary ion mass spectrometry

The concentration of deuterium at the surface of cathodically charged high strength steels AISI 1062, 4037, and 4140 has been determined by secondary ion mass spectrometry (SIMS). The beneficial effects of pickling in NAP (a mixture of nitric, acetic, and phosphoric acids) to remove surfacebound deuterium have been observed. formerly with AMCA International Limited, Kanata, ON, Canada     

Studies on the Analysis of hydrogen in steels stored in various media

Mild steel samples charged with hydrogen were stored in EDTA, imidazole and a commercial inhibitor (with an active amino group) and analyzed for hydrogen. These reagents were found to decrease hydrogen loss by diffusion. Imidazole and the commercial inhibitor were also found to minimize the entry of hydrogen into the steel. The surface film consisting of Fe? N and Fe? N? HS bonded structures is thought to minimize hydrogen loss from the samples. Amines such as imidazole are suitable and more convenient than liquid nitrogen as sample storage media.     

Potentiodynamic polarization analysis of silver-palladium alloys in chloride solutions

A comprehensive anodic potentiodynamic polarization analysis of Ag-Pd binary alloys in chloride solutions has revealed composition dependent active-passive polarization profiles. The results are interpreted in terms of the transition metal properties of Pd and the electron donor acceptor theory of passivation.