Comparison of 10 Multi-Sensor Image Fusion Paradigms for IKONOS Images

Fusion of multi-sensor imaging data enables a synergetic interpretation of complementary information obtained by sensors of different spectral ranges. Multi-sensor data of diverse spectral, spatial and temporal resolutions require advanced numerical techniques for analysis and interpretation. This paper reviews ten advanced pixel based image fusion techniques – Component substitution (COS), Local mean and variance matching, Modified IHS (Intensity Hue Saturation), Fast Fourier Transformed-enhanced IHS, Laplacian Pyramid, Local regression, Smoothing filter (SF), Sparkle, SVHC and Synthetic Variable Ratio. The above techniques were tested on IKONOS data (Panchromatic band at 1 m spatial resolution and Multispectral 4 bands at 4 m spatial resolution). Evaluation of the fused results through various accuracy measures, revealed that SF and COS methods produce images closest to corresponding multi-sensor would observe at the highest resolution level (1 m).

Control technique for non-linear and unbalance compensation of an integrated magnetics-based three-phase series-shunt-compensated uninterruptible power supply

Handling unbalanced and non-linear loads in a three-phase AC power supply has always been a difficult issue. This has been addressed in the literature by either using fast controllers in the fundamental rotating reference frame or using separate controllers in reference frames specific to the harmonics. In the former case, the controller needs to be fast and in the latter case, besides the need for many controllers, negative-sequence components need to be extracted from the measured signal. This study proposes a control scheme for harmonic and unbalance compensation of a three-phase uninterruptible power supply wherein the problems mentioned above are addressed. The control takes place in the fundamental positive-sequence reference frame using only a set of feedback and feed-forward compensators. The harmonic components are extracted by a process of frame transformations and used as feed-forward compensation terms in the positive-sequence fundamental reference frame. This study uses a method wherein the measured signal itself is used for fundamental negative-sequence compensation. As the feed-forward compensator handles the high-bandwidth components, the feedback compensator can be a simple low-bandwidth one. This control algorithm is explained and validated experimentally.

Control technique for non-linear and unbalance compensation of an integrated magnetics-based three-phase series-shunt-compensated uninterruptible power supply

Handling unbalanced and non-linear loads in a three-phase AC power supply has always been a difficult issue. This has been addressed in the literature by either using fast controllers in the fundamental rotating reference frame or using separate controllers in reference frames specific to the harmonics. In the former case, the controller needs to be fast and in the lattercase, besides the need for many controllers, negative-sequence components need to be extracted from the measured signal.This study proposes a control scheme for harmonic and unbalance compensation of a three-phase uninterruptible power supply wherein the problems mentioned above are addressed. The control takes place in the fundamental positive-sequence reference frame using only a set of feedback and feed-forward compensators. The harmonic components are extracted by process of frame transformations and used as feed-forward compensation terms in the positive-sequence fundamental reference frame. This study uses a method wherein the measured signal itself is used for fundamental negative-sequence compensation. As the feed-forward compensator handles the high-bandwidth components, the feedback compensator can be a simple low-bandwidth one. This control algorithm is explained and validated experimentally.

Estimation of Series Capacitance of a Transformer Winding Based on Frequency-Response Data: An Indirect Measurement Approach

A novel procedure to determine the series capacitance of a transformer winding, based on frequency-response measurements, is reported. It is based on converting the measured driving-point impedance magnitude response into a rational function and thereafter exploiting the ratio of a specific coefficient in the numerator and denominator polynomial, which leads to the direct estimation of series capacitance. The theoretical formulations are derived for a mutually coupled ladder-network model, followed by sample calculations. The results obtained are accurate and its feasibility is demonstrated by experiments on model-coil and on actual, single, isolated transformer windings (layered, continuous disc, and interleaved disc). The authors believe that the proposed method is the closest one can get to indirectly measuring series capacitance.

Time Series Classification for Online Tamil Handwritten Character Recognition – A Kernel Based Approach

In this paper, we consider the problem of time series classification. Using piecewise linear interpolation various novel kernels are obtained which can be used with Support vector machines for designing classifiers capable of deciding the class of a given time series. The approach is general and is applicable in many scenarios. We apply the method to the task of Online Tamil handwritten character recognition with promising results.

Magnetic arm-switch-based three-phase series-shunt compensated quality AC power supply

This study presents a novel magnetic arm-switch-based integrated magnetic circuit for a three-phase series-shunt compensated uninterruptible power supply (UPS). The magnetic circuit acts as a common interacting field for a number of energy ports, viz., series inverter, shunt inverter, grid and load. The magnetic arm-switching technique ensures equivalent series or shunt connection between the inverters. In normal grid mode (stabiliser mode), the series inverter is used for series voltage correction and the shunt one for current correction. The inverters and the load are effectively connected in parallel when the grid power is not available. These inverters are then used to share the load power. The operation of the inverters in parallel is ensured by the magnetic arm-switching technique. This study also includes modelling of the magnetic circuit. A graphical technique called bond graph is used to model the system. In this model, the magnetic circuit is represented in terms of gyrator-capacitors. Therefore the model is also termed as gyrator-capacitor model. The model is used to extract the dynamic equations that are used to simulate the system using MATLAB/SIMULINK. This study also discusses a synchronously rotating reference frame-based control technique that is used for the control of the series and shunt inverters in different operating modes. Finally, the gyrator-capacitor model is validated by comparing the simulated and experimental results.

A stochastic dynamical system for image segmentation

Image segmentation is formulated as a stochastic process whose invariant distribution is concentrated at points of the desired region. By choosing multiple seed points, different regions can be segmented. The algorithm is based on the theory of time-homogeneous Markov chains and has been largely motivated by the technique of simulated annealing. The method proposed here has been found to perform well on real-world clean as well as noisy images while being computationally far less expensive than stochastic optimisation techniques

Image Encryption with Space-filling Curves

Conventional encryption techniques are usually applicable for text data and often unsuited for encrypting multimedia objects for two reasons. Firstly, the huge sizes associated with multimedia objects make conventional encryption computationally costly. Secondly, multimedia objects come with massive redundancies which are useful in avoiding encryption of the objects in their entirety. Hence a class of encryption techniques devoted to encrypting multimedia objects like images have been developed. These techniques make use of the fact that the data comprising multimedia objects like images could in general be seggregated into two disjoint components, namely salient and non-salient. While the former component contributes to the perceptual quality of the object, the latter only adds minor details to it. In the context of images, the salient component is often much smaller in size than the non-salient component. Encryption effort is considerably reduced if only the salient component is encrypted while leaving the other component unencrypted. A key challenge is to find means to achieve a desirable seggregation so that the unencrypted component does not reveal any information about the object itself. In this study, an image encryption approach that uses fractal structures known as space-filling curves- in order to reduce the encryption overload is presented. In addition, the approach also enables a high quality lossy compression of images.

Particle image velocimetry and infrared thermography in a levitated droplet with nanosilica suspensions

Preferential accumulation and agglomeration kinetics of nanoparticles suspended in an acoustically levitated water droplet under radiative heating has been studied. Particle image velocimetry performed to map the internal flow field shows a single cell recirculation with increasing strength for decreasing viscosities. Infrared thermography and high speed imaging show details of the heating process for various concentrations of nanosilica droplets. Initial stage of heating is marked by fast vaporization of liquid and sharp temperature rise. Following this stage, aggregation of nanoparticles is seen resulting in various structure formations. At low concentrations, a bowl structure of the droplet is dominant, maintained at a constant temperature. At high concentrations, viscosity of the solution increases, leading to rotation about the levitator axis due to the dominance of centrifugal motion. Such complex fluid motion inside the droplet due to acoustic streaming eventually results in the formation of a ring structure. This horizontal ring eventually reorients itself due to an imbalance of acoustic forces on the ring, exposing larger area for laser absorption and subsequent sharp temperature rise.

Three-Component Self-Assembly of a Series of Triply Interlocked Pd12 Coordination Prisms and Their Non-Interlocked Pd6 Analogues

Template-assisted formation of multicomponent Pd6 coordination prisms and formation of their self-templated triply interlocked Pd12 analogues in the absence of an external template have been established in a single step through Pd?N/Pd?O coordination. Treatment of cis-[Pd(en)(NO3)2] with K3tma and linear pillar 4,4'-bpy (en=ethylenediamine, H3tma=benzene-1,3,5-tricarboxylic acid, 4,4'-bpy=4,4'-bipyridine) gave intercalated coordination cage [{Pd(en)}6(bpy)3(tma)2]2[NO3]12 (1) exclusively, whereas the same reaction in the presence of H3tma as an aromatic guest gave a H3tma-encapsulating non-interlocked discrete Pd6 molecular prism [{Pd(en)}6(bpy)3(tma)2(H3tma)2][NO3]6 (2). Though the same reaction using cis-[Pd(NO3)2(pn)] (pn=propane-1,2-diamine) instead of cis-[Pd(en)(NO3)2] gave triply interlocked coordination cage [{Pd(pn)}6(bpy)3(tma)2]2[NO3]12 (3) along with non-interlocked Pd6 analogue [{Pd(pn)}6(bpy)3(tma)2](NO3)6 (3'), and the presence of H3tma as a guest gave H3tma-encapsulating molecular prism [{Pd(pn)}6(bpy)3(tma)2(H3tma)2][NO3]6 (4) exclusively. In solution, the amount of 3' decreases as the temperature is decreased, and in the solid state 3 is the sole product. Notably, an analogous reaction using the relatively short pillar pz (pz=pyrazine) instead of 4,4'-bpy gave triply interlocked coordination cage [{Pd(pn)}6(pz)3(tma)2]2[NO3]12 (5) as the single product. Interestingly, the same reaction using slightly more bulky cis-[Pd(NO3)2(tmen)] (tmen=N,N,N',N'-tetramethylethylene diamine) instead of cis-[Pd(NO3)2(pn)] gave non-interlocked [{Pd(tmen)}6(pz)3(tma)2][NO3]6 (6) exclusively. Complexes 1, 3, and 5 represent the first examples of template-free triply interlocked molecular prisms obtained through multicomponent self-assembly. Formation of the complexes was supported by IR and multinuclear NMR (1H and 13C) spectroscopy. Formation of guest-encapsulating complexes (2 and 4) was confirmed by 2D DOSY and ROESY NMR spectroscopic analyses, whereas for complexes 1, 3, 5, and 6 single-crystal X-ray diffraction techniques unambiguously confirmed their formation. The gross geometries of H3tma-encapsulating complexes 2 and 4 were obtained by universal force field (UFF) simulations.

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.

Homo- or Heterosynthon? A Crystallographic Study on a Series of New Cocrystals Derived from Pyrazinecarboxamide and Various Carboxylic Acids Equipped with Additional Hydrogen Bonding Sites

Four new cocrystals of a well studied active pharmaceutical ingredient (API), namely, pyrazinecarboxamide (PZA), with various monocarboxylic acids equipped with additional hydrogen bonding sites such as vanillic acid (VA), gallic acid (GA), 1-hydroxy-2-naphthoic acid (1HNA), and indole-2-carboxylic acid (I2CA) have been successfully prepared and characterized by FTIR, H-1 NMR, differential scanning calorimetry (DSC), and single crystal and powder X-ray diffraction (SXRD and PXRD, respectively) techniques. In the majority of the cases, preferential occurrence amide amide and acid acid homosynthons has been observed. Since the heterosynthon is energetically preferred to homosynthon, such unusual occurrence of homosynthon in these cocrystals is intriguing.

Structure and deformation correlation of closed-cell aluminium foam subject to uniaxial compression

We report the results of an experimental and numerical study conducted on a closed-cell aluminium foam that was subjected to uniaxial compression with lateral constraint. X-ray computed tomography was utilized to gain access into the three-dimensional (3-D) structure of the foam and some aspects of the deformation mechanisms. A series of advanced 3-D image analyses are conducted on the 3-D images aimed at characterizing the strain localization regions. We identify the morphological/geometrical features that are responsible for the collapse of the cells and the strain localization. A novel mathematical approach based on a Minkowski tensor analysis along with the mean intercept length technique were utilized to search for signatures of anisotropy across the foam sample and its evolution as a function of loading. Our results show that regions with higher degrees of anisotropy in the undeformed foam have a tendency to initiate the onset of cell collapse. Furthermore, we show that strain hardening occurs predominantly in regions with large cells and high anisotropy. We combine the finite element method with the tomographic images to simulate the mechanical response of the foam. We predict further deformation in regions where the foam is already deformed. Crown Copyright (C) 2012 Published by Elsevier Ltd. on behalf of Acta Materialia Inc. All rights reserved.

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.

Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called `early warning signals', and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data.