An analysis on WDM components in flat gain regions of EDFA

Wavelength-division multiplexing (WDM) technology, by which multiple optical channels can be simultaneously transmitted at different wavelengths through a single optical fiber, is a useful means of making full use of the low-loss characteristics of optical fibers over a wide-wavelength region. The present day multifunction RADARs with multiple transmit receive modules requires various kinds of signal distribution for real time operation. If the signal distribution can be achieved through optical networks by using Wavelength Division Multiplexing (WDM) methods, it results in a distribution scheme with less hardware complexity and leads to the reduction in the weight of the antenna arrays In addition, being an Optical network it is free from Electromagnetic interference which is a crucial requirement in an array environment. This paper discusses about the analysis performed on various WDM components of distribution optical network for radar applications. The analysis is performed by considering the feasible constant gain regions of Erbium doped fiber amplifier (EDFA) in Matlab environment. This will help the user in the selection of suitable components for WDM based optical distribution networks.

Stability analysis of aperiodic messages scheduled in the dynamic segment of flex ray protocol

In a cyber physical system like vehicles number of signals to be communicated in a network system has an increasing trend. More and more mechanical and hydraulic parts are replaced by electronic control units and infotainment and multimedia applications has increased in vehicles. Safety critical hard real time messages and aperiodic messages communicated between electronic control units have been increased in recent times. Flexray is a high bandwidth protocol consisting of static segment for supporting hard real time messages and a dynamic segment for transmitting soft and non real time messages. In this paper, a method to obtain the stability region for the random arrival of messages in each electronic control units which is scheduled in the dynamic segment of Flexray protocol is presented. Number of mini slots available in the dynamic segment of Flexray restricts the arrival rate of tasks to the micro controllers or the number of micro controllers connected to the Flexray bus. Stability region of mathematical model of the system is compared with the Flexray protocol simulation results.

Assimilation of endmember variability in spectral for urban land cover extraction mixture analysis

Variable Endmember Constrained Least Square (VECLS) technique is proposed to account endmember variability in the linear mixture model by incorporating the variance for each class, the signals of which varies from pixel to pixel due to change in urban land cover (LC) structures. VECLS is first tested with a computer simulated three class endmember considering four bands having small, medium and large variability with three different spatial resolutions. The technique is next validated with real datasets of IKONOS, Landsat ETM+ and MODIS. The results show that correlation between actual and estimated proportion is higher by an average of 0.25 for the artificial datasets compared to a situation where variability is not considered. With IKONOS, Landsat ETM+ and MODIS data, the average correlation increased by 0.15 for 2 and 3 classes and by 0.19 for 4 classes, when compared to single endmember per class. (C) 2013 COSPAR. Published by Elsevier Ltd. All rights reserved.

Formulation of a mathematical approach to regional frequency analysis

Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

Connectivity analysis of multichannel EEG signals using recurrence based phase synchronization technique

Real world biological systems such as the human brain are inherently nonlinear and difficult to model. However, most of the previous studies have either employed linear models or parametric nonlinear models for investigating brain function. In this paper, a novel application of a nonlinear measure of phase synchronization based on recurrences, correlation between probabilities of recurrence (CPR), to study connectivity in the brain has been proposed. Being non-parametric, this method makes very few assumptions, making it suitable for investigating brain function in a data-driven way. CPR's utility with application to multichannel electroencephalographic (EEG) signals has been demonstrated. Brain connectivity obtained using thresholded CPR matrix of multichannel EEG signals showed clear differences in the number and pattern of connections in brain connectivity between (a) epileptic seizure and pre-seizure and (b) eyes open and eyes closed states. Corresponding brain headmaps provide meaningful insights about synchronization in the brain in those states. K-means clustering of connectivity parameters of CPR and linear correlation obtained from global epileptic seizure and pre-seizure showed significantly larger cluster centroid distances for CPR as opposed to linear correlation, thereby demonstrating the superior ability of CPR for discriminating seizure from pre-seizure. The headmap in the case of focal epilepsy clearly enables us to identify the focus of the epilepsy which provides certain diagnostic value. (C) 2013 Elsevier Ltd. All rights reserved.

A Low-Cost System for Measurement and Spectral Analysis of Motor Acoustic Noise

Workplace noise has become one of the major issues in industry not only because of workers’ health but also due to safety. Electric motors, particularly, inverter fed induction motors emit objectionably high levels of noise. This has led to the emergence of a research area, concerned with measurement and mitigation of the acoustic noise. This paper presents a lowcost option for measurement and spectral analysis of acoustic noise emitted by electric motors. The system consists of an electret microphone, amplifier and filter. It makes use of the windows sound card and associated software for data acquisition and analysis. The measurement system is calibrated using a professional sound level meter. Acoustic noise measurements are made on an induction motor drive using the proposed system as per relevant international standards. These measurements are seen to match closely with those of a professional meter.

DEFINING alpha-HELIX GEOMETRY BY C-alpha ATOM TRACE vs (phi-psi) TORSION ANGLES: A COMPARATIVE ANALYSIS

A regular secondary structure is described by a well defined set of values for the backbone dihedral angles (phi,psi and omega) in a polypeptide chain. However in real protein structures small local variations give rise to distortions from the ideal structures, which can lead to considerable variation in higher order organization. Protein structure analysis and accurate assignment of various structural elements, especially their terminii, are important first step in protein structure prediction and design. Various algorithms are available for assigning secondary structure elements in proteins but some lacunae still exist. In this study, results of a recently developed in-house program ASSP have been compared with those from STRIDE, in identification of alpha-helical regions in both globular and membrane proteins. It is found that, while a combination of hydrogen bond patterns and backbone torsional angles (phi-psi) are generally used to define secondary structure elements, the geometry of the C-alpha atom trace by itself is sufficient to define the parameters of helical structures in proteins. It is also possible to differentiate the various helical structures by their C-alpha trace and identify the deviations occurring both at mid-positions as well as at the terminii of alpha-helices, which often lead to occurrence of 3(10) and pi-helical fragments in both globular and membrane proteins.

Decentralized demand-supply matching using community microgrids and consumer demand response: A scenario analysis

Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demand response can be suitable decentralized options to augment the centralized grid based systems and plug the demand-supply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demand supply matching within a community, and, (2) determine which of these options can suitably plug the existing demand-supply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demand response by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs. (C) 2014 Elsevier Ltd. All rights reserved.

Finite Element Analysis of Stress Evolution in Al-Si Alloy

A 2D multi-particle model is carried out to understand the effect of microstructural variations and loading conditions on the stress evolution in Al-Si alloy under compression. A total of six parameters are varied to create 26 idealized microstructures: particle size, shape, orientation, matrix temper, strain rate, and temperature. The effect of these parameters is investigated to understand the fracture of Si particles and the yielding of Al matrix. The Si particles are modeled as a linear elastic solid and the Al matrix is modeled as an elasto-plastic solid. The results of the study demonstrate that the increase in particle size decreases the yield strength of the alloy. The particles with high aspect ratio and oriented at 0A degrees and 90A degrees to the loading axis show higher stress values. This implies that the particle shape and orientation are dominant factors in controlling particle fracture. The heat treatment of the alloy is found to increase the stress levels of both particles and matrix. Stress calculations also show that higher particle fracture and matrix yielding is expected at higher strain rate deformation. Particle fracture decreases with increase in temperature and the Al matrix plays an important role in controlling the properties of the alloy at higher temperatures. Further, this strain rate and temperature dependence is more pronounced in the heat-treated microstructure. These predictions are consistent with the experimentally observed Si particle fracture in real microstructure.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Path Sensitive Cache Analysis Using Cache Miss Paths

Cache analysis plays a very important role in obtaining precise Worst Case Execution Time (WCET) estimates of programs for real-time systems. While Abstract Interpretation based approaches are almost universally used for cache analysis, they fail to take advantage of its unique requirement: it is not necessary to find the guaranteed cache behavior that holds across all executions of a program. We only need the cache behavior along one particular program path, which is the path with the maximum execution time. In this work, we introduce the concept of cache miss paths, which allows us to use the worst-case path information to improve the precision of AI-based cache analysis. We use Abstract Interpretation to determine the cache miss paths, and then integrate them in the IPET formulation. An added advantage is that this further allows us to use infeasible path information for cache analysis. Experimentally, our approach gives more precise WCETs as compared to AI-based cache analysis, and we also provide techniques to trade-off analysis time with precision to provide scalability.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

Real-Time Stress Measurements in Germanium Thin Film Electrodes during Electrochemical Lithiation/Delithiation Cycling

An in situ study of stress evolution and mechanical behavior of germanium as a lithium-ion battery electrode material is presented. Thin films of germanium are cycled in a half-cell configuration with lithium metal foil as counter/reference electrode, with 1M LiPF6 in ethylene carbonate, diethyl carbonate, dimethyl carbonate solution (1:1:1, wt%) as electrolyte. Real-time stress evolution in the germanium thin-film electrodes during electrochemical lithiation/delithiation is measured by monitoring the substrate curvature using the multi-beam optical sensing method. Upon lithiation a-Ge undergoes extensive plastic deformation, with a peak compressive stress reaching as high as -0.76 +/- 0.05 GPa (mean +/- standard deviation). The compressive stress decreases with lithium concentration reaching a value of approximately -0.3 GPa at the end of lithiation. Upon delithiation the stress quickly became tensile and follows a trend that mirrors the behavior on compressive side; the average peak tensile stress of the lithiated Ge samples was approximately 0.83 GPa. The peak tensile stress data along with the SEM analysis was used to estimate a lower bound fracture resistance of lithiated Ge, which is approximately 5.3 J/m(2). It was also observed that the lithiated Ge is rate sensitive, i.e., stress depends on how fast or slow the charging is carried out. (C) The Author(s) 2015. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 License (CC BY, http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse of the work in any medium, provided the original work is properly cited. All rights reserved.

Life-cycle analysis of energy and greenhouse gas emissions of automotive fuels in India: Part 2-Well-to-wheels analysis

In this second of the two-part study, the results of the Tank-to-Wheels study reported in the first part are combined with Well-to-Tank results in this paper to provide a comprehensive Well-to-Wheels energy consumption and greenhouse gas emissions evaluation of automotive fuels in India. The results indicate that liquid fuels derived from petroleum have Well-to-Tank efficiencies in the range of 75-85% with liquefied petroleum gas being the most efficient fuel in the Well-to-Tank stage with 85% efficiency. Electricity has the lowest efficiency of 20% which is mainly attributed due to its dependence on coal and 25.4% losses during transmission and distribution. The complete Well-to-Wheels results show diesel vehicles to be the most efficient among all configurations, specifically the diesel-powered split hybrid electric vehicle. Hydrogen engine configurations are the least efficient due to low efficiency of production of hydrogen from natural gas. Hybridizing electric vehicles reduces the Well-to-Wheels greenhouse gas emissions substantially with split hybrid configuration being the most efficient. Electric vehicles do not offer any significant improvement over gasoline-powered configurations; however a shift towards renewable sources for power generation and reduction in losses during transmission and distribution can make it a feasible option in the future. (C) 2015 Elsevier Ltd. All rights reserved.

Thermal Strain Analysis of a Flip-Chip Package by a Modified Hybrid Method

介绍一种可用于微电子封装局部应变场分析的实验/计算混合方法,该方法结合了有限元的整体/局部模型和实时的激光云纹干涉技术,利用激光云纹干涉技术所测得的应变场来校核有限元整体模型的计算结果,并用整体模型的结果作为局部模型的边界条件,对实验难以确定的封装结构局部位置的应力、应变场进行分析.用这种方法对可控坍塌倒装封装结构在热载荷作用下焊球内的应变场分布进行了分析,结果表明该方法能够提供封装结构内应力-应变场分布的准确和可靠的结果,为微电子封装的可靠性分析提供重要的依据. For the reliability analysis of electronic packages, strains in very localized areas, such as an interconnection or a corner, need to be determined. In this paper, a modified hybrid method of global/local modeling and real time moire interferometry is presented. In this method, a simplified, coarsely meshed global model is developed to get rough information about the deformation of the microelectronic package. In order to make sure the global model has been reasonably simplified and the material properties ...