Consideration on thermal decomposition of calcium hydroxide pellets for energy storage

The reversible chemical reaction of Ca(OH)2/CaO appears to be attractive for storage of solar thermal energy, in view of the nonpolluting and nontoxic nature of the reactants. This paper presents some data on thermal decomposition of calcium hydroxide pellets along with its additives of aluminum, aluminum hydroxide, zinc, and copper. The addition of aluminum and zinc powder enhanced the rate of decomposition considerably at 450°C, but copper had no effect. Considerations on the effect of additives are also discussed in some detail, though their effects are not established with certainty. There is some evidence that heat transfer into the pellet, and the number of potential nucleation sites due to thermal stresses, influence the kinetics and mechanism of decomposition.

Penetration of hydromagnetic energy deep into the magnetosphere

Magnetometer data, acquired on spacecraft and simultaneously at high and low latitudes on the ground, are compared in order to study the propagation characteristics of hydromagnetic energy deep into the magnetosphere. Single events provide evidence that wave energy at L ∼ 3 can at times be only one order of magnitude lower than at L ∼ 13. In addition, statistical analyses of the H-component groundbased data obtained during local daytime hours of 17 July-3 August 1985 show that wave amplitudes at L ∼ 3 are generally 10-30 times lower than at L ∼ 13. The L-dependence of near-equator magnetic field fluctuations measured on ISEE-2 show a sharp drop in energy near the magnetopause and a more gradual fall-off of energy deeper inside the magnetosphere. Such high levels of wave power deep in the magnetosphere have not been quantitatively understood previously. Our initial attempt is to calculate the decay length of an evanescent wave generated at a thick magnetopause boundary. Numerical calculations show that fast magnetosonic modes (called magnetopause and inner mode) can be generated under very restrictive conditions for the field and plasma parameters. These fast compressional modes may have their energy reduced by only one order of magnitude over a penetration depth of about 8RE. More realistic numerical simulations need to be carried out to see whether better agreement with the data can be attained.

A Wavelet based Teager Energy Operator for Spike Detection in Microelectrode Array Recordings

Spike detection in neural recordings is the initial step in the creation of brain machine interfaces. The Teager energy operator (TEO) treats a spike as an increase in the `local' energy and detects this increase. The performance of TEO in detecting action potential spikes suffers due to its sensitivity to the frequency of spikes in the presence of noise which is present in microelectrode array (MEA) recordings. The multiresolution TEO (mTEO) method overcomes this shortcoming of the TEO by tuning the parameter k to an optimal value m so as to match to frequency of the spike. In this paper, we present an algorithm for the mTEO using the multiresolution structure of wavelets along with inbuilt lowpass filtering of the subband signals. The algorithm is efficient and can be implemented for real-time processing of neural signals for spike detection. The performance of the algorithm is tested on a simulated neural signal with 10 spike templates obtained from [14]. The background noise is modeled as a colored Gaussian random process. Using the noise standard deviation and autocorrelation functions obtained from recorded data, background noise was simulated by an autoregressive (AR(5)) filter. The simulations show a spike detection accuracy of 90%and above with less than 5% false positives at an SNR of 2.35 dB as compared to 80% accuracy and 10% false positives reported [6] on simulated neural signals.

Text localization and extraction from complex gray images

We propose two texture-based approaches, one involving Gabor filters and the other employing log-polar wavelets, for separating text from non-text elements in a document image. Both the proposed algorithms compute local energy at some information-rich points, which are marked by Harris' corner detector. The advantage of this approach is that the algorithm calculates the local energy at selected points and not throughout the image, thus saving a lot of computational time. The algorithm has been tested on a large set of scanned text pages and the results have been seen to be better than the results from the existing algorithms. Among the proposed schemes, the Gabor filter based scheme marginally outperforms the wavelet based scheme.

Exploring energy-performance trade-offs for heterogeneous interconnect clustered VLIW processors

Clustered architecture processors are preferred for embedded systems because centralized register file architectures scale poorly in terms of clock rate, chip area, and power consumption. Although clustering helps by improving clock speed, reducing energy consumption of the logic, and making the design simpler, it introduces extra overheads by way of inter-cluster communication. This communication happens over long global wires which leads to delay in execution and significantly high energy consumption.In this paper, we propose a new instruction scheduling algorithm that exploits scheduling slacks of instructions and communication slacks of data values together to achieve better energy-performance trade-offs for clustered architectures with heterogeneous interconnect. Our instruction scheduling algorithm achieves 35% and 40% reduction in communication energy, whereas the overall energy-delay product improves by 4.5% and 6.5% respectively for 2 cluster and 4 cluster machines with marginal increase (1.6% and 1.1%) in execution time. Our test bed uses the Trimaran compiler infrastructure.

Comparative study of filter-bank mean-energy distance for automated segmentation of speech signals

This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.

Customer Energy in Relationships

All companies have a portfolio of customer relationships. From a managerial standpoint the value of these customer relationships is a key issue. The aim of the paper is to introduce a conceptual framework for customers’ energy towards a service provider. Customer energy is defined as the cognitive, affective and behavioural effort a customer puts into the purchase of an offering. It is based on two dimensions: life theme involvement and relationship commitment. Data from a survey study of 425 customers of an online gambling site was combined with data about their individual purchases and activity. Analysis showed that involvement and commitment influence both customer behaviour and attitudes. Customer involvement was found to be strongly related to overall spending within a consumption area, whereas relationship commitment is a better predictor of the amount of money spent at a particular company. Dividing the customers into four different involvement / commitment segments revealed differences in churn rates, word-of-mouth, brand attitude, switching propensity and the use of the service for socializing. The framework provides a tool for customer management by revealing differences in fundamental drivers of customer behaviour resulting in completely new customer portfolios. Knowledge of customer energy allows companies to manage their communication and offering development better and provides insight into the risk of losing a customer.

Photophysics of conjugated polymers: interplay between Forster energy migration and defect concentration in shaping a photochemical funnel in PPV

Recent single molecule experiments have suggested the existence of a photochemical funnel in the photophysics of conjugated polymers, like poly[2-methoxy-5-(2'-ethylhexyl)oxy-1,4-phenylenevinylene] (MEH-PPV). The funnel is believed to be a consequence of the presence of conformational or chemical defects along the polymer chain and efficient non-radiative energy transfer among different chromophore segments. Here we address the effect of the excitation energy dynamics on the photophysics of PPV. The PPV chain is modeled as a polymer with the length distribution of chromophores given either by a Gaussian or by a Poisson distribution. We observe that the Poisson distribution of the segment lengths explains the photophysics of PPV better than the Gaussian distribution. A recently proposed version of an extended particle-in-a-box' model is used to calculate the exciton energies and the transition dipole moments of the chromophores, and a master equation to describe the excitation energy transfer among different chromophores. The rate of energy transfer is assumed to be given here, as a first approximation, by the well-known Forster expression. The observed excitation population dynamics confirms the photochemical funneling of excitation energy from shorter to longer chromophores of the polymer chain. The time scale of spectral shift and energy transfer for our model polymer, with realistic values of optical parameters, is in the range of 200-300 ps. We find that the excitation energy may not always migrate towards the longest chromophore segments in the polymer chain as the efficiency of energy transfer between chromophores depends on the separation distance between the two and their relative orientation.

Observation of reduced activation energy and the possible existence of decoupled pancake vortices in superconductor/ferromagnet bilayers

Investigations of different superconducting (S)/ferromagnetic (F) heterostructures grown by pulsed laser deposition reveal that the activation energy (U) for the vortex motion in a high T-c superconductor is reduced remarkably by the presence of F layers. The U exhibits a logarithmic dependence on the applied magnetic field in the S/F bilayers suggesting the existence of decoupled two-dimensional (2D) pancake vortices. This result is discussed in terms of the reduction in the effective S layer thickness and the weakening of the S coherence length due to the presence of F layers. In addition, the U and the superconducting T-c in YBa2Cu3O7-delta/La0.5Sr0.5CoO3 bilayers are observed to be much lower than in the YBa2Cu3O7-delta/La0.7Sr0.3MnO3 ones. This in turn suggests that the degree of spin polarization of the F layer might not play a crucial role for the suppression of superconductivity due to a spin polarized induced pair-breaking effect in S/F bilayers.

Study of the electronic structures of high Tc cuprate superconductors by electron energy loss and secondary electron emission spectroscopies

Energy loss spectra of superconducting YBa2Cu3O6.9' Bi1.5Pb0.5Ca2.5Sr1.5Cu3O10+δ and Tl2CaBa2Cu3O8 obtained at primary electron energies in the 170–310 eV range show features reflecting the commonalities in their electronic structures. The relative intensity of the plasmon peak shows a marked drop across the transition temperature. Secondary electron emission spectra of the cuprates also reveal some features of the electronic structure.

Electronic-Transitions In Hydrogen-Bonded Dimers Of Carboxylic-Acids In The Vapor-Phase - An Electron-Energy Loss Spectroscopic Study

An electron energy loss spectroscopic study of the formic acid dimer has shown bands centred around 7.2, 8.5, 9.8, and 11.1 eV, of which the first and the third bands are assigned to n- rc* transitions and the other two to n-n* transitions; similar transitions are found in the acetic acid dimer.