Interferometer for use in wave-front testing with a cross slit

A simple and novel interferometric setup for wave-front testing that uses a cross slit is described. In this method, the test beam illuminates a cross slit placed at the front focal plane of a Fourier lens. It selects two orthogonal slices from the test beam, and the interference of these two beams is observed at a slightly defocused plane near the back focal plane. Fringes of different conical forms (circular, elliptical, or hyperbolic) so obtained can be used for testing a coherent wave front in general. The theory, supported by some experimental results, is presented. An application of the method to the study of the nature of asymmetry in the beam profile of a semiconductor diode laser beam is demonstrated.     

Effect of ash on maximum thickness of plastic layer of coals

A study of the effect of ash yield on the maximum thickness of the plastic layer (MTPL) of some coking coals (as measured by the Sapozhnikov plastometer) has revealed that with an increase in the former the latter in general decre?es. A rectilinear relation approximately exists between the ash percentage (dry basis) and log MTPL values of coals. For the samples studied, a multiple correlation incorporating the rank factor was found to be unnecessary. Higher Fe₂O₃ and SO₃ contents from the coal were found to be associated with higher MTPL values.     

Behavior-change trials to assess the feasibility of improving complementary feeding practices and micronutrient intake of infants in rural Bangladesh

This study used simple rapid-assessment techniques to test the feasibility of increasing the consumption of complementary foods by infants by asking mothers to increase meal quantity or frequency or by altering the viscosity/energy density of the food. The feasibility of using micronutrient supplements either added directly to food or administered as liquid drops was also examined. The study was conducted in rural Bangladesh and involved four separate short-term behavioral change trials. Depending on the trial, fieldworkers recruited 30 to 45 infants 6 to 12 months of age. Following recommendations to increase the amount of food provided to infants, the mean intakes from single meals increased from 40 +/- 23 g on day 1 to 64 +/- 30 g on day 7 (p < 0.05). In a second trial, the mean meal frequency increased from 2.2 +/- 1.3 on day 1 to 4.1 +/- 1.3 on day 7 (p < 0.05). Provision of high-energy-density diets, prepared by decreasing viscosity with alpha-amylase or by hand-mashing rice and dhal into a paste before feeding, increased single-meal energy consumption from 54 +/- 35 kcal to 79 +/- 52 kcal or 75 +/- 37 kcal (p < 0.05), respectively. Both types of micronutrient supplements were well accepted and used according to recommendations. In conclusion, it was possible to change short-term child-feeding behaviors to promote increased food intake, mealfrequency, energy density, and micronutrient consumption. Because each of these interventions lasted for only about 1 week, however, the long-term sustainability of these changes is not known. Moreover, the effect of increased feeding of complementary foods on intakes of breastmilk and total daily consumption of energy and nutrients requires further study.     

A higher-order spectral element for wave propagation analysis in functionally graded materials

Summary. A new higher-order spectral element (SE) is developed for wave propagation analysis of a functionally graded material (FGM) beam in the presence of thermal and mechanical loading. The element is based on first order shear deformation theory (FSDT) and takes into account the depthwise contraction due to Poissons ratio. A new method of element formulation is employed, which is the most general one and devoid of all previous cumbersome wavenumber and wave amplitude computation. The beam can be subjected to temperature variation in depth direction. This variation is found by solving the one-dimensional heat conduction equation uncoupled from the elasticity equation. The effect of the computed temperature field is subsequently superimposed on the mechanical loading in the form of an equivalent nodal load. Numerical examples are directed towards highlighting the effect of the Poissons contraction on the structural response and stress wave. The spectrum and the dispersion relation are studied in detail. The stress field generated by the element and its difference from the FSDT stress field is outlined. The response of an FGM beam to thermo-mechanical loading is analysed and the effect of thermal loading on the overall response is elicited.     

Polarization-based compensation of astigmatism

One approach to aberration compensation of an imaging system is to introduce a suitable phase mask at the aperture plane of an imaging system. We utilize this principle for the compensation of astigmatism. A suitable polarization mask used on the aperture plane together with a polarizer-retarder combination at the input of the imaging system provides the compensating polarization-induced phase steps at different quadrants of the apertures masked by different polarizers. The aberrant phase can be considerably compensated by the proper choice of a polarization mask and suitable selection of the polarization parameters involved. The results presented here bear out our theoretical expectation.     

Evaluation of the performance of backpropagation and radial basis function neural networks in predicting the drill flank wear

This study compares the performance of backpropagation neural network (BPNN) and radial basis function network (RBFN) in predicting the flank wear of high speed steel drill bits for drilling holes on mild steel and copper work pieces. The validation of the methodology is carried out following a series of experiments performed over a wide range of cutting conditions in which the effect of various process parameters, such as drill diameter, feed-rate, spindle speed, etc. on drill wear has been considered. Subsequently, the data, divided suitably into training and testing samples, have been used to effectively train both the backpropagation and radial basis function neural networks, and the individual performance of the two networks is then analyzed. It is observed that the performance of the RBFN fails to match that of the BPNN when the network complexity and the amount of data available are the constraining factors. However, when a simpler training procedure and reduced computational times are required, then RBFN is the preferred choice.     

Distributed Intelligent Energy Management System for a Single-Phase High-Frequency AC Microgrid

In this paper, a single-phase high-frequency AC (HFAC) microgrid is shown as a novel solution towards integrating renewable energy sources in a distributed generation system. Better utilization of the Microgrid is achieved by solving power flow and power quality issues using p-q theory-based active filtering called universal active power line conditioner and unified power quality conditioner, respectively. A distributed intelligent energy management system (DIEMS) is implemented to optimize operating costs. As the optimization greatly depends on the power generation and the power output from renewable sources strongly depends on the weather, the forecast of power generation is required for DIEMS. A Fuzzy ARTMAP neural network is used to predict hourly day-type outputs based on which generation can be forecasted. Depending on the forecast, an optimization scheme is developed utilizing linear programming along with heuristics. The results obtained show the successful implementation of HFAC Microgrid with adequate power flow and power quality control, as well as the optimization of operation cost by the DIEMS with Fuzzy ARTMAP-based day-type forecasting. The improvement in the battery life is also achieved due to optimization of storage charge states using the proposed DIEMS     

A Novel Approach to Improve the Speech Intelligibility Using Fractional Delta-amplitude Modulation Spectrogram

Abstract

Speech enhancement is an interesting research area that aims at improving the quality and intelligibility of the speech that is affected by the additive noises, such as airport noise, train noise, restaurant noise, and so on. The presence of these background noises degrades the comfort of listening of the end user. This article proposes a speech enhancement method that uses a novel feature extraction which removes the noise spectrum from the noisy speech signal using a novel fractional delta-AMS (amplitude modulation spectrogram) feature extraction and the D-matrix feature extraction method. The fractional delta-AMS feature extraction strategy is the modification of the delta-AMS with the fractional calculus that increases the sharpness of the feature extraction. The extracted features from the frames are used to determine the optimal mask of all the frames of the noisy speech signal and the mask is employed for training the deep belief neural networks (DBN). The two metrics root mean square error (RMSE) and perceptual evaluation of speech quality (PESQ) are used to evaluate the method. The proposed method yields a better value of PESQ at all level of noise and RMSE decreases with increased noise level.     

Resource augmentation for uniprocessor and multiprocessor partitioned scheduling of sporadic real-time tasks

Although the earliest-deadline-first (EDF) policy is known to be optimal for preemptive real-time task scheduling in uniprocessor systems, the schedulability analysis problem has recently been shown to be $\mathit{co}\mathcal{NP}$ -hard. Therefore, approximation algorithms, and in particular, approximations based on resource augmentation have attracted a lot of attention for both uniprocessor and multiprocessor systems. Resource augmentation based approximations assume a certain speedup of the processor(s). Using the notion of approximate demand bound function (dbf), in this paper we show that for uniprocessor systems the resource augmentation factor is at most $\frac{2e-1}{e} \approx1.6322$ , where e is the Euler number. We approximate the dbf using a linear approximation when the analysis interval length of interest is larger than the relative deadline of the task. For identical multiprocessor systems with M processors and constrained-deadline task sets, we show that the deadline-monotonic partitioning (that has been proposed by Baruah and Fisher) with the approximate dbf leads to an approximation factor of $\frac{3e-1}{e}-\frac{1}{M} \approx 2.6322-\frac{1}{M}$ with respect to resource augmentation. We also show that the corresponding factor is $3-\frac{1}{M}$ for arbitrary-deadline task sets. The best known results so far were $3-\frac{1}{M}$ for constrained-deadline tasks and $4-\frac {2}{M}$ for arbitrary-deadline ones. Our tighter analysis exploits the structure of the approximate dbf directly and uses the processor utilization violations (which were ignored in all previous analysis) for analyzing resource augmentation factors. We also provide concrete input instances to show that the lower bound on the resource augmentation factor for uniprocessor systems—using the above approximate dbf—is 1.5, and the corresponding bound is 2.5 for identical multiprocessor systems with an arbitrary order of fitting and a large number of processors. Further, we also provide a polynomial-time approximation scheme (PTAS) to derive near-optimal solutions under the assumption that the ratio of the maximum relative deadline to the minimum relative deadline of tasks is a constant, which is a more relaxed assumption compared to the assumptions required for deriving such a PTAS in the past.