The role of lithium and magnesium perchlorate ammines in ammonium perchlorate decomposition

The preparation and thermal decomposition of lithium and magnesium perchlorate ammines have been investigated. The catalytic effect of these ammines on AP decomposition has been studied. The catalytic effect of lithium and magnesium salts on AP decomposition has been attributed to the formation of the metal perchlorate ammine intermediate. In the case of a magnesium salt: AP mixture, the melting of the magnesium perchlorate monoammine intermediate seems to play an important role in catalysing the decomposition.

Thermal Decomposition and Combustion Studies on Potassium Perchlorat e/Polystyrene Propellant Systems

STUDIES on potassium perchlorate/polystyrene (KP/PS) propellant systems have been carried out by using such techniques as thermogravimetry (TG), differential thermal analysis (DTA), and mass spectrometry (MS). It has been found that the thermal decomposition (TD) behavior of the KP/PS propellant is similar to that of the AP/PS propellant studied earlier.! It has also been observed that the TD of KP in the melt has a correlation with the burning rate (r) of KP/PS propellant at atmospheric pressure.

A Proof of Convergence of the B-RED and P-RED Algorithms for Random Early Detection

In [8], we recently presented two computationally efficient algorithms named B-RED and P-RED for random early detection. In this letter, we present the mathematical proof of convergence of these algorithms under general conditions to local minima.

Spinodal Decomposition in Tellurite-Based Glasses Induced by Excimer Laser Irradiation

Tellurite-based glasses in the TeO2-K3Li2Nb5O15, TeO2-Ba5Li2Ti2Nb8O30, and V2Te2O9 were fabricated by the conventional melt-quenching technique. Amorphous and glassy characteristics of the as-quenched samples were established via the X-ray powder diffraction technique and differential thermal analysis, respectively. The as-quenched samples were irradiated by an excimer laser (248 nm). The effect of laser power, duration of irradiation, and the frequency of the laser pulses on the surface features of the above glasses were studied. The optical microscopic studies carried out on the above systems revealed the presence of quasi-periodic and periodic structures on their surfaces. The local compositional variations of these structures were confirmed by back-scattered electron imaging using scanning electron microscope accompanied by energy-dispersive X-ray analysis. These results were convincing enough to state that the glasses in the present investigations had undergone spinodal decomposition on laser irradiation. The incidence of the interconnected texture of two different phases was observed owing to the quenching effect produced by the heating and cooling cycle of the successive laser pulses. Ring- and line-shaped patterns were also observed, respectively, when the pulse frequency of the laser and the duration of irradiation were increased.

Topology-based denoising of chaos

In this article, we propose a denoising algorithm to denoise a time series y(i) = x(i) + e(i), where {x(i)} is a time series obtained from a time- T map of a uniformly hyperbolic or Anosov flow, and {e(i)} a uniformly bounded sequence of independent and identically distributed (i.i.d.) random variables. Making use of observations up to time n, we create an estimate of x(i) for i<n. We show under typical limiting behaviours of the orbit and the recurrence properties of x(i), the estimation error converges to zero as n tends to infinity with probability 1.

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.

Natural actor-critic algorithms

We present four new reinforcement learning algorithms based on actor-critic, natural-gradient and functi approximation ideas,and we provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated by stochastic gradient descent. Methods based on policy gradients in this way are of special interest because of their compatibility with function-approximation methods, which are needed to handle large or infinite state spaces. The use of temporal difference learning in this way is of special interest because in many applications it dramatically reduces the variance of the gradient estimates. The use of the natural gradient is of interest because it can produce better conditioned parameterizations and has been shown to further reduce variance in some cases. Our results extend prior two-timescale convergence results for actor-critic methods by Konda and Tsitsiklis by using temporal difference learning in the actor and by incorporating natural gradients. Our results extend prior empirical studies of natural actor-critic methods by Peters, Vijayakumar and Schaal by providing the first convergence proofs and the first fully incremental algorithms.

Conservative Design Optimization of Laminated Composite Structures Using Genetic Algorithms and Multiple Failure Criteria

This article analyzes the effect of devising a new failure envelope by the combination of the most commonly used failure criteria for the composite laminates, on the design of composite structures. The failure criteria considered for the study are maximum stress and Tsai-Wu criteria. In addition to these popular phenomenological-based failure criteria, a micromechanics-based failure criterion called failure mechanism-based failure criterion is also considered. The failure envelopes obtained by these failure criteria are superimposed over one another and a new failure envelope is constructed based on the lowest absolute values of the strengths predicted by these failure criteria. Thus, the new failure envelope so obtained is named as most conservative failure envelope. A minimum weight design of composite laminates is performed using genetic algorithms. In addition to this, the effect of stacking sequence on the minimum weight of the laminate is also studied. Results are compared for the different failure envelopes and the conservative design is evaluated, with respect to the designs obtained by using only one failure criteria. The design approach is recommended for structures where composites are the key load-carrying members such as helicopter rotor blades.

Agents Based Algorithms for Design Parameter Estimation in Contaminant Transport Inverse Problems

A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

An adaptive decomposition method for video

Scalable video coding (SVC) is an emerging standard built on the success of advanced video coding standard (H.264/AVC) by the Joint video team (JVT). Motion compensated temporal filtering (MCTF) and Closed loop hierarchical B pictures (CHBP) are two important coding methods proposed during initial stages of standardization. Either of the coding methods, MCTF/CHBP performs better depending upon noise content and characteristics of the sequence. This work identifies other characteristics of the sequences for which performance of MCTF is superior to that of CHBP and presents a method to adaptively select either of MCTF and CHBP coding methods at the GOP level. This method, referred as "Adaptive Decomposition" is shown to provide better R-D performance than of that by using MCTF or CRBP only. Further this method is extended to non-scalable coders.

Delamination of Surfactant-Intercalated Brucite-Like Hydroxy Salts of Cobalt and Copper and Solvothermal Decomposition of the Resultant Colloidal Dispersions

Surfactant anion intercalated hydroxy salts of copper and cobalt of the formula M(OH)(2-x)(surf)(x)center dot mH(2)O [M = Cu, Co; surf = dodecyl sulfate. dodecyl benzene sulfonate. and x = 0.5 for Cu and 0.67 for Co] delaminate readily in 1-butanol to give translucent colloidal dispersions that are stable for months. The extent of delamination and the colloidal dispersion observed in these solids is higher than what had been observed for layered double hydroxides. The dispersions yield the corresponding nanoparticulate oxides on solvothermal decomposition. While the copper hydroxy salt forms similar to 300 nm dendrimer-like CuO nanostructures comprising nanorods of similar to 10 nm diameter, the cobalt analogue forms similar to 20 nm superparamagnetic particles of Co3O4.

Bounding Run-Times of Local Adiabatic Algorithms

A common trick for designing faster quantum adiabatic algorithms is to apply the adiabaticity condition locally at every instant. However it is often difficult to determine the instantaneous gap between the lowest two eigenvalues, which is an essential ingredient in the adiabaticity condition. In this paper we present a simple linear algebraic technique for obtaining a lower bound on the instantaneous gap even in such a situation. As an illustration, we investigate the adiabatic un-ordered search of van Dam et al. [17] and Roland and Cerf [15] when the non-zero entries of the diagonal final Hamiltonian are perturbed by a polynomial (in log N, where N is the length of the unordered list) amount. We use our technique to derive a bound on the running time of a local adiabatic schedule in terms of the minimum gap between the lowest two eigenvalues.

Correction of Ocular Artifacts in EEG Recordings using Empirical Mode Decomposition

EEG recordings are often contaminated with ocular artifacts such as eye blinks and eye movements. These artifacts may obscure underlying brain activity in the electroencephalogram (EEG) data and make the analysis of the data difficult. In this paper, we explore the use of empirical mode decomposition (EMD) based filtering technique to correct the eye blinks and eye movementartifacts in single channel EEG data. In this method, the single channel EEG data containing ocular artifact is segmented such that the artifact in each of the segment is considered as some type of slowly varying trend in the dataand the EMD is used to remove the trend. The filtering is done using partial reconstruction from components of the decomposition. The method is completely data dependent and hence adaptive and nonlinear. Experimental results are provided to check the applicability of the method on real EEG data and the results are quantified using power spectral density (PSD) as a measure. The method has given fairlygood results and does not make use of any preknowledge of artifacts or the EEG data used.

Linear time algorithms for Abelian group isomorphism and related problems

We consider the problem of determining if two finite groups are isomorphic. The groups are assumed to be represented by their multiplication tables. We present an O(n) algorithm that determines if two Abelian groups with n elements each are isomorphic. This improves upon the previous upper bound of O(n log n) [Narayan Vikas, An O(n) algorithm for Abelian p-group isomorphism and an O(n log n) algorithm for Abelian group isomorphism, J. Comput. System Sci. 53 (1996) 1-9] known for this problem. We solve a more general problem of computing the orders of all the elements of any group (not necessarily Abelian) of size n in O(n) time. Our algorithm for isomorphism testing of Abelian groups follows from this result. We use the property that our order finding algorithm works for any group to design a simple O(n) algorithm for testing whether a group of size n, described by its multiplication table, is nilpotent. We also give an O(n) algorithm for determining if a group of size n, described by its multiplication table, is Abelian. (C) 2007 Elsevier Inc. All rights reserved.

Electrical switching and thermal studies on Ge22Te78-xIx chalcohalide glasses: The effect of iodine on network-topology

Investigations on the electrical switching behavior and thermal studies using Alternating Differential Scanning Calorimetry have been undertaken on bulk, melt-quenched Ge22Te78-,Is (3 <= x <= 10) chalcohalide glasses. All the glasses studied have been found to exhibit memory-type electrical switching. The threshold voltages of Ge22Te78-I-x(x) glasses have been found to increase with the addition of iodine and the composition dependence of threshold voltages of Ge22Te78-xIx glasses exhibits a cusp at 5 at.% of iodine. Also, the variation with composition of the glass transition temperature (Tg) of Ge22Te78-I-x(x) glasses, exhibits a broad hump around this composition. Based on the present results, the composition x = 5 has been identified as the inverse rigidity percolation threshold at which Ge22Te78-I-x(x) glassy system exhibits a change from a stressed rigid amorphous solid to a flexible polymeric glass. Further, a sharp minimum is seen in the composition dependence of non-reversing enthalpy (Delta H-nr) of Ge22Te78-I-x(x) glasses at x = 5, which is suggestive of a thermally reversing window at this composition. (C) 2007 Elsevier Ltd. All rights reserved.