Optimal maintenance and replacement via a semi-Markov decision model

Optimal bang-coast maintenance policies for a machine, subject to failure, are considered. The approach utilizes a semi-Markov model for the system. A simplified model for modifying the probability of machine failure with maintenance is employed. A numerical example is presented to illustrate the procedure and results.

Risk Minimizing Option Pricing in a Semi-Markov Modulated Market

We address risk minimizing option pricing in a semi-Markov modulated market where the floating interest rate depends on a finite state semi-Markov process. The growth rate and the volatility of the stock also depend on the semi-Markov process. Using the Föllmer–Schweizer decomposition we find the locally risk minimizing price for European options and the corresponding hedging strategy. We develop suitable numerical methods for computing option prices.

Portfolio Optimization in a Semi-Markov Modulated Market

We address a portfolio optimization problem in a semi-Markov modulated market. We study both the terminal expected utility optimization on finite time horizon and the risk-sensitive portfolio optimization on finite and infinite time horizon. We obtain optimal portfolios in relevant cases. A numerical procedure is also developed to compute the optimal expected terminal utility for finite horizon problem.

A semi-classical model of the electron containing tachyonic matter

It is shown that the mass of the electron could be conceived as the energy associated with its spinning motion and the angular velocity is such that the linear velocities at the surface exceed the velocity of light; this in fact accounts for its stability against the centrifugal forces in the core region.

A new semi-empirical model for correlating the solubilities of solids in supercritical carbon dioxide with cosolvents

The equilibrium solubilities of the solids in supercritical carbon dioxide (SCCO(2)) are considerably enhanced in the presence of cosolvents. The solubilities of m-dinitrobenzene at 308 and 318 K over a pressure range of 9.5-14.5 MPa in the presence of 1.13-2.17 mol% methanol as cosolvent were determined. The average increase in the solubilities in the presence of methanol compared to that obtained in the absence of methanol was around 35%. A new semi-empirical equation in terms of temperature, pressure, density of SCCO(2) and cosolvent composition comprising of 7 adjustable parameters was developed. The proposed model was used to correlate the solubility of the solids in SCCO(2) for the 44 systems available in the literature along with current data. The average absolute relative deviation of the experimental data from the model equation was 3.58%, which is better than the existing models. (C) 2011 Elsevier B.V. All rights reserved.

Non-Stationary Semi-Markov Decision Processes on a Finite Horizon

We introduce and study a class of non-stationary semi-Markov decision processes on a finite horizon. By constructing an equivalent Markov decision process, we establish the existence of a piecewise open loop relaxed control which is optimal for the finite horizon problem.

Performance Analysis of TCP Uploads in WLANs with Multiple Rates

Throughput analysis of bulk TCP downloads in cases where all WLAN stations are associated at the same rate with the AP is available in the literature. In this paper,we extend the analysis to TCP uploads for the case of multirate associations. The approach is based on a two-dimensional semi- Markov model for the number of backlogged stations. Analytical results are in excellent agreement with simulations performed using QUALNET 4.5.

A semi-empirical theory of molten salts

A semi-empirical model is presented for describing the interionic interactions in molten salts using the experimentally available structure data. An extension of Bertaut's method of non-overlapping charges is used to estimate the electrostatic interaction energy in ionic melts. It is shown, in agreement with earlier computer simulation studies, that this energy increases when an ionic salt melts. The repulsion between ions is described using a compressible ion theory which uses structure-independent parameters. The van der Waals interactions and the thermal free energy are also included in the total energy, which is minimised with respect to isostructural volume variations to calculate the equilibrium density. Detailed results are presented for three molten systems, NaCl, CaCl2 and ZnCl2, and are shown to be in satisfactory agreement with experiments. With reliable structural data now being reported for several other molten salts, the present study gains relevance.

Joint evaluation of multiple speech patterns for speech recognition and training

We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

Joint decoding of multiple speech patterns for robust speech recognition

We are addressing a new problem of improving automatic speech recognition performance, given multiple utterances of patterns from the same class. We have formulated the problem of jointly decoding K multiple patterns given a single Hidden Markov Model. It is shown that such a solution is possible by aligning the K patterns using the proposed Multi Pattern Dynamic Time Warping algorithm followed by the Constrained Multi Pattern Viterbi Algorithm The new formulation is tested in the context of speaker independent isolated word recognition for both clean and noisy patterns. When 10 percent of speech is affected by a burst noise at -5 dB Signal to Noise Ratio (local), it is shown that joint decoding using only two noisy patterns reduces the noisy speech recognition error rate to about 51 percent, when compared to the single pattern decoding using the Viterbi Algorithm. In contrast a simple maximization of individual pattern likelihoods, provides only about 7 percent reduction in error rate.

Average-Delay Optimal Policies for the Point-to-Point Channel

Average-delay optimal scheduflng of messages arriving to the transmitter of a point-to-point channel is considered in this paper. We consider a discrete time batch-arrival batch-service queueing model for the communication scheme, with service time that may be a function of batch size. The question of delay optimality is addressed within the semi-Markov decision-theoretic framework. Approximations to the average-delay optimal policy are obtained.

Multi-Pattern Viterbi Algorithm for joint decoding of multiple speech patterns

Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.

Optimal maintenance policy of a machine subject to failure

Optimal maintenance policies for a machine with degradation in performance with age and subject to failure are derived using optimal control theory. The optimal policies are shown to be, normally, of bang-coast nature, except in the case when probability of machine failure is a function of maintenance. It is also shown, in the deterministic case that a higher depreciation rate tends to reverse this policy to coast-bang. When the probability of failure is a function of maintenance, considerable computational effort is needed to obtain an optimal policy and the resulting policy is not easily implementable. For this case also, an optimal policy in the class of bang-coast policies is derived, using a semi-Markov decision model. A simple procedure for modifying the probability of machine failure with maintenance is employed. The results obtained extend and unify the recent results for this problem along both theoretical and practical lines. Numerical examples are presented to illustrate the results obtained.

Aggregate download throughput for TCP-controlled long file transfers in a WLAN with multiple STA-AP association rates

We consider several WLAN stations associated at rates r(1), r(2), ... r(k) with an Access Point. Each station (STA) is downloading a long file from a local server, located on the LAN to which the Access Point (AP) is attached, using TCP. We assume that a TCP ACK will be produced after the reception of d packets at an STA. We model these simultaneous TCP-controlled transfers using a semi-Markov process. Our analytical approach leads to a procedure to compute aggregate download, as well as per-STA throughputs, numerically, and the results match simulations very well. (C) 2012 Elsevier B.V. All rights reserved.