Spatial correlation in grain misorientation distribution

Grain misorientation was studied in relation to the nearest neighbor's mutual distance using electron back-scattered diffraction measurements. The misorientation correlation function was defined as the probability density for the occurrence of a certain misorientation between pairs of grains separated by a certain distance. Scale-invariant spatial correlation between neighbor grains was manifested by a power law dependence of the preferred misorientation vs. inter-granular distance in various materials after diverse strain paths. The obtained negative scaling exponents were in the range of -2 +/- 0.3 for high-angle grain boundaries. The exponent decreased in the presence of low-angle grain boundaries or dynamic recrystallization, indicating faster decay of correlations. The correlations vanished in annealed materials. The results were interpreted in terms of lattice incompatibility and continuity conditions at the interface between neighboring grains. Grain-size effects on texture development, as well as the implications of such spatial correlations on texture modeling, were discussed.

Convergence analysis of the Newton algorithm and a pseudo-time marching scheme for diffuse correlation tomography

We propose a self-regularized pseudo-time marching scheme to solve the ill-posed, nonlinear inverse problem associated with diffuse propagation of coherent light in a tissuelike object. In particular, in the context of diffuse correlation tomography (DCT), we consider the recovery of mechanical property distributions from partial and noisy boundary measurements of light intensity autocorrelation. We prove the existence of a minimizer for the Newton algorithm after establishing the existence of weak solutions for the forward equation of light amplitude autocorrelation and its Frechet derivative and adjoint. The asymptotic stability of the solution of the ordinary differential equation obtained through the introduction of the pseudo-time is also analyzed. We show that the asymptotic solution obtained through the pseudo-time marching converges to that optimal solution provided the Hessian of the forward equation is positive definite in the neighborhood of optimal solution. The superior noise tolerance and regularization-insensitive nature of pseudo-dynamic strategy are proved through numerical simulations in the context of both DCT and diffuse optical tomography. (C) 2010 Optical Society of America.

Augmenting process elicitation with visual priming: An empirical exploration of user behaviour and modelling outcomes

Business process models have become an effective way of examining business practices to identify areas for improvement. While common information gathering approaches are generally efficacious, they can be quite time consuming and have the risk of developing inaccuracies when information is forgotten or incorrectly interpreted by analysts. In this study, the potential of a role-playing approach to process elicitation and specification has been examined. This method allows stakeholders to enter a virtual world and role-play actions similarly to how they would in reality. As actions are completed, a model is automatically developed, removing the need for stakeholders to learn and understand a modelling grammar. An empirical investigation comparing both the modelling outputs and participant behaviour of this virtual world role-play elicitor with an S-BPM process modelling tool found that while the modelling approaches of the two groups varied greatly, the virtual world elicitor may not only improve both the number of individual process task steps remembered and the correctness of task ordering, but also provide a reduction in the time required for stakeholders to model a process view.

Deuterium-carbon correlation in static oriented systems using DAPT - A windowless multiple pulse sequence

We present a new method for establishing correlation between deuterium and its attached carbon in a deuterated liquid crystal. The method is based on transfer of polarization using the DAPT pulse sequence proposed originally for two spin half nuclei, now extended to a spin-1 and a spin-1/2 nuclei. DAPT utilizes the evolution of magnetization of the spin pair under two blocks of phase shifted BLEW-12 pulses on one of the spins separated by a 90 degree pulse on the other spin. The method is easy to implement and does not need to satisfy matching conditions unlike the Hartmann-Hahn cross-polarization. Experimental results presented demonstrate the efficacy of the method.

Correlation between conductivity or diffusivity and activation energy in amorphous solids

There exist many investigations of ionic transport in a variety of glasses. These studies exhibit strong correlation between ionic conductivity and activation energy: Typically, it is found that higher conductivity is associated with lower activation energies and vice versa. Although there are explanations for this at a phenomenological level, there is no consistent physical picture to explain the correlation between conductivity and activation energy. We have carried out molecular dynamics simulation as a function of the size of the impurity atom or diffusant (both neutral and charged) in a host amorphous matrix. We find that there is a maximum in self-diffusivity as a function of the size of the impurity atom suggesting that there is an appropriate size for which the diffusivity is maximum. The activation energy is found to be the lowest for this size of the impurity. A similar maximum has been previously found in other condensed phases, such as confined fluids and dense liquids, and has its origin in the levitation effect. The implications of this result for understanding ionic conductivity in glasses are discussed. Our results suggest that there is a relation between microscopic structure of the amorphous solid, diffusivity or conductivity, and activation energy. The nature of this relationship is discussed in terms of the levitation parameter showing that diffusivity is maximum when the size of the neck or doorway radius is comparable with the size of the diffusant. Our computational results here are in excellent agreement with independent experimental results of Nascimento et al. [Braz. J. Phys. 35, 626 (2005)] that structural features of the glass are important in determining the ionic conductivity.

Correlation, Coding, and Cooperation in Wireless Sensor Networks

We consider a single-hop data-gathering sensor network, consisting of a set of sensor nodes that transmit data periodically to a base-station. We are interested in maximizing the lifetime of this network. With our definition of network lifetime and the assumption that the radio transmission energy consumption forms the most significant portion of the total energy consumption at a sensor node, we attempt to enhance the network lifetime by reducing the transmission energy budget of sensor nodes by exploiting three system-level opportunities. We pose the problem of maximizing lifetime as a max-min optimization problem subject to the constraint of successful data collection and limited energy supply at each node. This turns out to be an extremely difficult optimization to solve. To reduce the complexity of this problem, we allow the sensor nodes and the base-station to interactively communicate with each other and employ instantaneous decoding at the base-station. The chief contribution of the paper is to show that the computational complexity of our problem is determined by the complex interplay of various system-level opportunities and challenges.

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.

Low correlation sequences over AM-PSK and QAM alphabets

A construction for a family of sequences over the 8-ary AM-PSK constellation that has maximum nontrivial correlation magnitude bounded as theta(max) less than or similar to root N is presented here. The famfly is asymptotically optimal with respect to the Welch bound on maximum magnitude of correlation. The 8-ary AM-PSK constellation is a subset of the 16-QAM constellation. We also construct two families of sequences over 16-QAM with theta(max) less than or similar to root 2 root N. These families are constructed by interleaving sets of sequences. A construction for a famBy of low-correlation sequences over QAM alphabet of size 2(2m) is presented with maximum nontrivial normalized correlation parameter bounded above by less than or similar to a root N, where N is the period of the sequences in the family and where a ranges from 1.61 in the case of 16-QAM modulation to 2.76 for large m. When used in a CDMA setting, the family will permit each user to modulate the code sequence with 2m bits of data. Interestingly, the construction permits users on the reverse link of the CDMA channel to communicate using varying data rates by switching between sequence famflies; associated to different values of the parameter m. Other features of the sequence families are improved Euclidean distance between different data symbols in comparison with PSK signaling and compatibility of the QAM sequence families with sequences belonging to the large quaternary sequence families {S(p)}.

Do inventory management practices affect economic performance? An empirical evaluation of the machine tool SMEs in Bangalore

Inventory management (IM) has a decisive role in the enhancement of manufacturing industry's competitiveness. Therefore, major manufacturing industries are following IM practices with the intention of improving their performance. However, the effort to introduce IM in SMEs is very limited due to lack of initiation, expertise, and financial constraints. This paper aims to provide a guideline for entrepreneurs in enhancing their IM performance, as it presents the results of a survey based study carried out for machine tool Small and Medium Enterprises (SMEs) in Bangalore. Having established the significance of inventory as an input, we probed the relationship between IM performance and economic performance of these SMEs. To the extent possible all the factors of production and performance indicators were deliberately considered in pure economic terms. All economic performance indicators adopted seem to have a positive and significant association with IM performance in SMEs. On the whole, we found that SMEs which are IM efficient are likely to perform better on the economic front also and experience higher returns to scale.

Mapping of Average Shear Wave Velocity for Bangalore Region: A Case Study

Mapping the shear wave velocity profile is an important part in seismic hazard and microzonation studies. The shear wave velocity of soil in the city of Bangalore was mapped using the Multichannel Analysis of Surface Wave (MASW) technique. An empirical relationship was found between the Standard Penetration Test (SPT) corrected N value ((N1)60cs) and measured shear wave velocity (Vs). The survey points were selected in such a way that the results represent the entire Bangalore region, covering an area of 220 km2. Fifty-eight 1-D and 20 2-D MASW surveys were performed and their velocity profiles determined. The average shear wave velocity of Bangalore soils was evaluated for depths of 5 m, 10 m, 15 m, 20 m, 25 m and 30 m. The sub-soil classification was made for seismic local site effect evaluation based on average shear wave velocity of 30-m depth (Vs30) of sites using the National Earthquake Hazards Reduction Program (NEHRP) and International Building Code (IBC) classification. Mapping clearly indicates that the depth of soil obtained from MASW closely matches with the soil layers identified in SPT bore holes. Estimation of local site effects for an earthquake requires knowledge of the dynamic properties of soil, which is usually expressed in terms of shear wave velocity. Hence, to make use of abundant SPT data available on many geotechnical projects in Bangalore, an attempt was made to develop a relationship between Vs (m/s) and (N1)60cs. The measured shear wave velocity at 38 locations close to SPT boreholes was used to generate the correlation between the corrected N values and shear wave velocity. A power fit model correlation was developed with a regression coefficient (R2) of 0.84. This relationship between shear wave velocity and corrected SPT N values correlates well with the Japan Road Association equations.

On the DC Conductivity of HV DC Cable Insulation - Cautions in using the Empirical Models

The electrical conduction in insulating materials is a complex process and several theories have been suggested in the literature. Many phenomenological empirical models are in use in the DC cable literature. However, the impact of using different models for cable insulation has not been investigated until now, but for the claims of relative accuracy. The steady state electric field in the DC cable insulation is known to be a strong function of DC conductivity. The DC conductivity, in turn, is a complex function of electric field and temperature. As a result, under certain conditions, the stress at cable screen is higher than that at the conductor boundary. The paper presents detailed investigations on using different empirical conductivity models suggested in the literature for HV DC cable applications. It has been expressly shown that certain models give rise to erroneous results in electric field and temperature computations. It is pointed out that the use of these models in the design or evaluation of cables will lead to errors.

ZnO nanocrystalline thin films: a correlation of microstructural, optoelectronic properties

The compositional, structural, microstructural, dc electrical conductivity and optical properties of undoped zinc oxide films prepared by the sol-gel process using a spin-coating technique were investigated. The ZnO films were obtained by 5 cycle spin-coated and dried zinc oxide films followed by annealing in air at 600 A degrees C. The films deposited on the platinum coated silicon substrate were crystallized in a hexagonal wurtzite form. The energy-dispersive X-ray (EDX) spectrometry shows Zn and O elements in the products with an approximate molar ratio. TEM image of ZnO thin film shows that a grain of about 60-80 nm in size is really an aggregate of many small crystallites of around 10-20 nm. Electron diffraction pattern shows that the ZnO films exhibited hexagonal structure. The SEM micrograph showed that the films consist in nanocrystalline grains randomly distributed with voids in different regions. The dc conductivity found in the range of 10(-5)-10(-6) (Omega cm)(-1). The optical study showed that the spectra for all samples give the transparency in the visible range.

New empirical expressions to correlate solubilities of solids in supercritical carbon dioxide

Supercritical processes are gaining importance in the last few years in the food, environmental and pharmaceutical product processing. The design of any supercritical process needs accurate experimental data on solubilities of solids in the supercritical fluids (SCFs). The empirical equations are quite successful in correlating the solubilities of solid compounds in SCF both in the presence and absence of cosolvents. In this work, existing solvate complex models are discussed and a new set of empirical equations is proposed. These equations correlate the solubilities of solids in supercritical carbon dioxide (both in the presence and absence of cosolvents) as a function of temperature, density of supercritical carbon dioxide and the mole fraction of cosolvent. The accuracy of the proposed models was evaluated by correlating 15 binary and 18 ternary systems. The proposed models provided the best overall correlations. (C) 2009 Elsevier BA/. All rights reserved.

Microarchitecture sensitive empirical models for compiler optimizations.

This paper proposes the use of empirical modeling techniques for building microarchitecture sensitive models for compiler optimizations. The models we build relate program performance to settings of compiler optimization flags, associated heuristics and key microarchitectural parameters. Unlike traditional analytical modeling methods, this relationship is learned entirely from data obtained by measuring performance at a small number of carefully selected compiler/microarchitecture configurations. We evaluate three different learning techniques in this context viz. linear regression, adaptive regression splines and radial basis function networks. We use the generated models to a) predict program performance at arbitrary compiler/microarchitecture configurations, b) quantify the significance of complex interactions between optimizations and the microarchitecture, and c) efficiently search for'optimal' settings of optimization flags and heuristics for any given microarchitectural configuration. Our evaluation using benchmarks from the SPEC CPU2000 suits suggests that accurate models (< 5% average error in prediction) can be generated using a reasonable number of simulations. We also find that using compiler settings prescribed by a model-based search can improve program performance by as much as 19% (with an average of 9.5%) over highly optimized binaries.

What does “futility” mean? An empirical study of doctors’ perceptions

Objective(s) To describe how doctors define and use the terms “futility” and “futile treatment” in end-of-life care. Design, Setting, Participants A qualitative study using semi-structured interviews with 96 doctors across a range of specialties who treat adults at the end of life. Doctors were recruited from three large Australian teaching hospitals and were interviewed from May to July 2013. Results Doctors’ conceptions of futility focused on the quality and chance of patient benefit. Aspects of benefit included physiological effect, weighing benefits and burdens, and quantity and quality of life. Quality and length of life were linked, but many doctors discussed instances when benefit was determined by quality of life alone. Most doctors described the assessment of chance of success in achieving patient benefit as a subjective exercise. Despite a broad conceptual consensus about what futility means, doctors noted variability in how the concept was applied in clinical decision-making. Over half the doctors also identified treatment that is futile but nevertheless justified, such as short-term treatment as part of supporting the family of a dying person. Conclusions There is an overwhelming preference for a qualitative approach to assessing futility, which brings with it variation in clinical decision-making. “Patient benefit” is at the heart of doctors’ definitions of futility. Determining patient benefit requires discussions with patients and families about their values and goals as well as the burdens and benefits of further treatment.