Optimal placement of Distributed Generation for a projected load increase using Relative Electrical Distance approach

There is a lot of pressure on all the developed and second world countries to produce low emission power and distributed generation (DG) is found to be one of the most viable ways to achieve this. DG generally makes use of renewable energy sources like wind, micro turbines, photovoltaic, etc., which produce power with minimum green house gas emissions. While installing a DG it is important to define its size and optimal location enabling minimum network expansion and line losses. In this paper, a methodology to locate the optimal site for a DG installation, with the objective to minimize the net transmission losses, is presented. The methodology is based on the concept of relative electrical distance (RED) between the DG and the load points. This approach will help to identify the new DG location(s), without the necessity to conduct repeated power flows. To validate this methodology case studies are carried out on a 20 node, 66kV system, a part of Karnataka Transco and results are presented.

A tracking-based general framework to image halftoning

Existing approches to digital halftoning of image are based primarily on thresholding. We propose a general framework fot image halftoning whcrc some function uf the output halftone tracks another function of the input gray-tone.This appcoach is shown lo unify most existing algorithms and to provide useful insights. Further, the new intcrpretation allows us to remedy problems in existing aigorithrms such as the error dlffusion, and sohsequently to achieve halftones haavmg superior quality. The proposed method is very general nature is an advantage since it offers a wide choice of three Cilters and a update rule. An intercstmg product of this framework is that equally good, or better, half-tones are possible ro be obtained by thresholding a noise proccess instead of the image itself.

An Accurate Fractional Period Delay Generation System

An all-digital technique is proposed for generating an accurate delay irrespective of the inaccuracies of a controllable delay line. A subsampling technique-based delay measurement unit (DMU) capable of measuring delays accurately for the full period range is used as the feedback element to build accurate fractional period delays based on input digital control bits. The proposed delay generation system periodically measures and corrects the error and maintains it at the minimum value without requiring any special calibration phase. Up to 40x improvement in accuracy is demonstrated for a commercial programmable delay generator chip. The time-precision trade-off feature of the DMU is utilized to reduce the locking time. Loop dynamics are adjusted to stabilize the delay after the minimum error is achieved, thus avoiding additional jitter. Measurement results from a high-end oscilloscope also validate the effectiveness of the proposed system in improving accuracy.

Efficient generation and guiding of megaampere relativistic electron current by silicon nanowires

We demonstrate 30 times enhanced flux of relativistic electrons by a silicon nanowire coated target excited by 30 fs, 800 nm laser pulses at an intensity of 3 x 10(18) W cm(-2). A measurement of the megaampere electron current via induced megagauss magnetic field supports the enhancement feature observed in the electron energy spectrum. The relativistic electrons generated at the front of nanowire coated surface are shown to travel efficiently over 500 mu m in the insulating substrate. The enhanced hot electron temperature is explained using a simple model and is supported by recent simulations. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4729010]

Large mass splittings for fourth generation fermions allowed by LHC Higgs boson exclusion

In the context of the standard model with a fourth generation, we explore the allowed mass spectra in the fourth-generation quark and lepton sectors as functions of the Higgs mass. Using the constraints from unitarity and oblique parameters, we show that a heavy Higgs allows large mass splittings in these sectors, opening up new decay channels involving W emission. Assuming that the hints for a light Higgs do not yet constitute an evidence, we work in a scenario where a heavy Higgs is viable. A Higgs heavier than similar to 800 GeV would in fact necessitate either a heavy quark decay channel t' -> b'W/b' -> t'W or a heavy lepton decay channel tau' -> nu'W as long as the mixing between the third and fourth generations is small. This mixing tends to suppress the mass splittings and hence the W-emission channels. The possibility of the W-emission channel could substantially change the search strategies of fourth-generation fermions at the LHC and impact the currently reported mass limits.

Linearization and Reconstruction of Non-linear Diffuse Optical Tomographic Image

Diffuse optical tomography (DOT) is one of the ways to probe highly scattering media such as tissue using low-energy near infra-red light (NIR) to reconstruct a map of the optical property distribution. The interaction of the photons in biological tissue is a non-linear process and the phton transport through the tissue is modelled using diffusion theory. The inversion problem is often solved through iterative methods based on nonlinear optimization for the minimization of a data-model misfit function. The solution of the non-linear problem can be improved by modeling and optimizing the cost functional. The cost functional is f(x) = x(T)Ax - b(T)x + c and after minimization, the cost functional reduces to Ax = b. The spatial distribution of optical parameter can be obtained by solving the above equation iteratively for x. As the problem is non-linear, ill-posed and ill-conditioned, there will be an error or correction term for x at each iteration. A linearization strategy is proposed for the solution of the nonlinear ill-posed inverse problem by linear combination of system matrix and error in solution. By propagating the error (e) information (obtained from previous iteration) to the minimization function f(x), we can rewrite the minimization function as f(x; e) = (x + e)(T) A(x + e) - b(T)(x + e) + c. The revised cost functional is f(x; e) = f(x) + e(T)Ae. The self guided spatial weighted prior (e(T)Ae) error (e, error in estimating x) information along the principal nodes facilitates a well resolved dominant solution over the region of interest. The local minimization reduces the spreading of inclusion and removes the side lobes, thereby improving the contrast, localization and resolution of reconstructed image which has not been possible with conventional linear and regularization algorithm.

An approach to multi-temporal MODIS image analysis using image classification and segmentation

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation for extracting water-covered regions. Analysis of MODIS satellite images is applied in three stages: before flood, during flood and after flood. Water regions are extracted from the MODIS images using image classification (based on spectral information) and image segmentation (based on spatial information). Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as Support Vector Machines (SVMs) and Artificial Neural Networks (ANNs) separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification (SVM and ANN) and region-based image segmentation is an accurate and reliable approach for the extraction of water-covered regions. (c) 2012 COSPAR. Published by Elsevier Ltd. All rights reserved.

Fast image reconstruction for fluorescence microscopy

Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

Prior image-constrained l(1)-norm-based reconstruction method for effective usage of structural information in diffuse optical tomography

A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

Effective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using l(1)-norm-based linear image reconstruction method

Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

Multilevel dodecagonal space-vector generation for induction motor drives by cascading three-level and two-level inverters

This study proposes an inverter circuit topology capable of generating multilevel dodecagonal (12-sided polygon) voltage space vectors by the cascaded connection of two-level and three-level inverters. By the proper selection of DC-link voltages and resultant switching states for the inverters, voltage space vectors whose tips lie on three concentric dodecagons, are obtained. A rectifier circuit for the inverter is also proposed, which significantly improves the power factor. The topology offers advantages such as the complete elimination of the fifth and seventh harmonics in phase voltages and an extension of the linear modulation range. In this study, a simple method for the calculation of pulse width modulation timing was presented along with extensive simulation and experimental results in order to validate the proposed concept.

Generation and analysis of drought stressed subtracted expressed sequence tags from safflower (Carthamus tinctorius L.)

Drought is the most crucial environmental factor that limits productivity of many crop plants. Exploring novel genes and gene combinations is of primary importance in plant drought tolerance research. Stress tolerant genotypes/species are known to express novel stress responsive genes with unique functional significance. Hence, identification and characterization of stress responsive genes from these tolerant species might be a reliable option to engineer the drought tolerance. Safflower has been found to be a relatively drought tolerant crop and thus, it has been the choice of study to characterize the genes expressed under drought stress. In the present study, we have evaluated differential drought tolerance of two cultivars of safflower namely, A1 and Nira using selective physiological marker traits and we have identified cultivar A1 as relatively drought tolerant. To identify the drought responsive genes, we have constructed a stress subtracted cDNA library from cultivar A1 following subtractive hybridization. Analysis of similar to 1,300 cDNA clones resulted in the identification of 667 unique drought responsive ESTs. Protein homology search revealed that 521 (78 %) out of 667 ESTs showed significant similarity to known sequences in the database and majority of them previously identified as drought stress-related genes and were found to be involved in a variety of cellular functions ranging from stress perception to cellular protection. Remaining 146 (22 %) ESTs were not homologous to known sequences in the database and therefore, they were considered to be unique and novel drought responsive genes of safflower. Since safflower is a stress-adapted oil-seed crop this observation has great relevance. In addition, to validate the differential expression of the identified genes, expression profiles of selected clones were analyzed using dot blot (reverse northern), and northern blot analysis. We showed that these clones were differentially expressed under different abiotic stress conditions. The implications of the analyzed genes in abiotic stress tolerance are discussed in our study.

Cobalt(II), Nickel(II) and Copper(II) complexes of a tetradentate Schiff base as photosensitizers: Quantum yield of O-1(2) generation and its promising role in anti-tumor activity

In the present investigation, a Schiff base N'(1),N'(3)-bis(E)-(5-bromo-2-hydroxyphenyl)methylidene]benzene-1,3-d icarbohydrazide and its metal complexes have been synthesized and characterized. The DNA-binding studies were performed using absorption spectroscopy, emission spectra, viscosity measurements and thermal denatuaration studies. The experimental evidence indicated that, the Co(II), Ni(II) and Cu(II) complexes interact with calf thymus DNA through intercalation with an intrinsic binding constant K-b of 2.6 x 10(4) M-1, 5.7 x 10(4) M-1 and 4.5 x 10(4) M-1, respectively and they exhibited potent photo-damage abilities on pUC19 DNA, through singlet oxygen generation with quantum yields of 0.32, 0.27 and 0.30 respectively. The cytotoxic activity of the complexes resulted that they act as a potent photosensitizers for photochemical reactions. (C) 2012 Elsevier B.V. All rights reserved.

Common Ground Method of Current Injection in Electrical Impedance Tomography

Surface electrodes are essentially required to be switched for boundary data collection in electrical impedance tomography (Ell). Parallel digital data bits are required to operate the multiplexers used, generally, for electrode switching in ELT. More the electrodes in an EIT system more the digital data bits are needed. For a sixteen electrode system. 16 parallel digital data bits are required to operate the multiplexers in opposite or neighbouring current injection method. In this paper a common ground current injection is proposed for EIT and the resistivity imaging is studied. Common ground method needs only two analog multiplexers each of which need only 4 digital data bits and hence only 8 digital bits are required to switch the 16 surface electrodes. Results show that the USB based data acquisition system sequentially generate digital data required for multiplexers operating in common ground current injection method. The profile of the boundary data collected from practical phantom show that the multiplexers are operating in the required sequence in common ground current injection protocol. The voltage peaks obtained for all the inhomogeneity configurations are found at the accurate positions in the boundary data matrix which proved the sequential operation of multiplexers. Resistivity images reconstructed from the boundary data collected from the practical phantom with different configurations also show that the entire digital data generation module is functioning properly. Reconstructed images and their image parameters proved that the boundary data are successfully acquired by the DAQ system which in turn indicates a sequential and proper operation of multiplexers.