Coplanar gas-discharge display

1. The electric field strength between coplanar electrodes is calculated employing "conformal transformations." The electron multiplication factor is then computed in the nonuniform field region. These calculations have been made for different gap lengths, voltages, and also for different gases and gas pressures. The configuration results in a curved discharge path. It is found that the electron multiplication is maximum along a particular flux line and the prebreakdown discharge is expected to follow this flux line. Experimental tubes incorporating several coplanar gaps have been fabricated. Breakdown voltages have been measured for various discharge gaps and also for various gases such as xenon, helium, neon, argon, and neon-argon mixture (99.5:0.5) at different filling pressures. The variation of breakdown voltage with pressure and gap length is discussed. The observed discharge paths are curved and this is in agreement with theoretical results. A few experimental single-digit coplanar gas-discharge displays (CGDD's) with digit height of 5 cm have been fabricated and dependence of their characteristics on various parameters, including spacing between top glass plate and bottom substrate, have been studied.

Impulse Voltage Breakdown Characteristics of Point-Plane Gaps at Low Pressures

Practical applications of vacuum as an insulator necessitated determining the low-pressure breakdown characteristics of long gap lengths of a point-plane electrode system. The breakdown voltage has been found to vary as the square root of the gap length. Further, with the point electrode as the anode, the values of the breakdown voltages obtained have been found to be larger than those obtained with a plane-parallel electrode system at a corresponding gap length. By applying the theory of the anode heating mechanism as the cause for breakdown, the results have been justified, and by utilizing a field efficiency factor which is the ratio of the average to maximum field, an empirical criterion has been developed. This criterion helps in calculating the breakdown voltage of a nonuniform gap system by the knowledge of the breakdown voltage of a plane-parallel electrode system.

Multiple contour extraction from graylevel images using an artificial neural network

For active contour modeling (ACM), we propose a novel self-organizing map (SOM)-based approach, called the batch-SOM (BSOM), that attempts to integrate the advantages of SOM- and snake-based ACMs in order to extract the desired contours from images. We employ feature points, in the form of ail edge-map (as obtained from a standard edge-detection operation), to guide the contour (as in the case of SOM-based ACMs) along with the gradient and intensity variations in a local region to ensure that the contour does not "leak" into the object boundary in case of faulty feature points (weak or broken edges). In contrast with the snake-based ACMs, however, we do not use an explicit energy functional (based on gradient or intensity) for controlling the contour movement. We extend the BSOM to handle extraction of contours of multiple objects, by splitting a single contour into as many subcontours as the objects in the image. The BSOM and its extended version are tested on synthetic binary and gray-level images with both single and multiple objects. We also demonstrate the efficacy of the BSOM on images of objects having both convex and nonconvex boundaries. The results demonstrate the superiority of the BSOM over others. Finally, we analyze the limitations of the BSOM.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Efficient decoding with generative score-spaces using the expectation semiring

State-of-the-art speech recognisers are usually based on hidden Markov models (HMMs). They model a hidden symbol sequence with a Markov process, with the observations independent given that sequence. These assumptions yield efficient algorithms, but limit the power of the model. An alternative model that allows a wide range of features, including word- and phone-level features, is a log-linear model. To handle, for example, word-level variable-length features, the original feature vectors must be segmented into words. Thus, decoding must find the optimal combination of segmentation of the utterance into words and word sequence. Features must therefore be extracted for each possible segment of audio. For many types of features, this becomes slow. In this paper, long-span features are derived from the likelihoods of word HMMs. Derivatives of the log-likelihoods, which break the Markov assumption, are appended. Previously, decoding with this model took cubic time in the length of the sequence, and longer for higher-order derivatives. This paper shows how to decode in quadratic time. © 2013 IEEE.

Asymptotic layer-type model of high pressure direct current glow discharge in electronegative gases

Here a self-consistent one-dimensional continuum model is presented for a narrow gap plane-parallel dc glow discharge. The governing equations consist of continuity and momentum equations for positive and negative ions and electrons coupled with Poisson's equation. A singular perturbation method is developed for the analysis of high pressure dc glow discharge. The kinetic processes of the ionization, electron attachment, and ion-ion recombination are included in the model. Explicit results are obtained for the asymptotic limits: delta=(r(D)/L)(2)--> 0, omega=(r(S)/L)(2)--> 0, where r(D) is the Debye radius, r(S) is recombination length, and L is the gap length. The discharge gap divides naturally into four layers with multiple space scales: anode fall region, positive column, transitional region, cathode fall region and diffusion layer adjacent to the cathode surface, its formation is discussed. The effects of the gas pressure, gap spacing and dc voltage on the electrical properties of the layers and its dimension are investigated. (C) 2000 American Institute of Physics. [S0021-8979(00)00813-6].

Asymptotic modeling of short plane-parallel high-pressure glow discharge

Here a self-consistent continuum model is presented for a narrow gap plane-parallel dc glow discharge. The set of governing equations consisting of continuity and momentum equations for positive ions, fast (emitted by the cathode) and slow electrons (generated by fast electron impact ionization) coupled with Poisson's equation is treated by the technique of matched asymptotic expansions. Explicit results are obtained in the asymptotic limit: (chi delta) much less than 1, where chi = e Phi(a)/kT, delta = (r(D)/L)(2) (Phi(a) is the applied voltage, r(D) is the Debye radius) and pL much greater than 1(Hg mm cm), where p is the gas pressure and L is the gap length. In the case of high pressure, the electron energy relaxation length is much smaller than the gap length, and so the local field approximation is valid. The discharge space divides naturally into a cathode fall sheath, a quasineutral plasma region, and an anode fall sheath. The electric potential distribution obtained for each region in a (semi)analytical form is asymptotically matched to the adjoining regions in the region of overlap. The effects of the gas pressure, gap length, and applied voltage on the length of each region are investigated. (C) 2000 American Institute of Physics. [S1070-664X(00)01302-1].

Intercellular calcium waves in primary cultured rat mesenteric smooth muscle cells are mediated by connexin43.

Intercellular Ca(2+) wave propagation between vascular smooth muscle cells (SMCs) is associated with the propagation of contraction along the vessel. Here, we characterize the involvement of gap junctions (GJs) in Ca(2+) wave propagation between SMCs at the cellular level. Gap junctional communication was assessed by the propagation of intercellular Ca(2+) waves and the transfer of Lucifer Yellow in A7r5 cells, primary rat mesenteric SMCs (pSMCs), and 6B5N cells, a clone of A7r5 cells expressing higher connexin43 (Cx43) to Cx40 ratio. Mechanical stimulation induced an intracellular Ca(2+) wave in pSMC and 6B5N cells that propagated to neighboring cells, whereas Ca(2+) waves in A7r5 cells failed to progress to neighboring cells. We demonstrate that Cx43 forms the functional GJs that are involved in mediating intercellular Ca(2+) waves and that co-expression of Cx40 with Cx43, depending on their expression ratio, may interfere with Cx43 GJ formation, thus altering junctional communication.

A Meta-Analysis of Trabecular Bone Score in Fracture Risk Prediction and Its Relationship to FRAX.

Trabecular bone score (TBS) is a gray-level textural index of bone microarchitecture derived from lumbar spine dual-energy X-ray absorptiometry (DXA) images. TBS is a bone mineral density (BMD)-independent predictor of fracture risk. The objective of this meta-analysis was to determine whether TBS predicted fracture risk independently of FRAX probability and to examine their combined performance by adjusting the FRAX probability for TBS. We utilized individual-level data from 17,809 men and women in 14 prospective population-based cohorts. Baseline evaluation included TBS and the FRAX risk variables, and outcomes during follow-up (mean 6.7 years) comprised major osteoporotic fractures. The association between TBS, FRAX probabilities, and the risk of fracture was examined using an extension of the Poisson regression model in each cohort and for each sex and expressed as the gradient of risk (GR; hazard ratio per 1 SD change in risk variable in direction of increased risk). FRAX probabilities were adjusted for TBS using an adjustment factor derived from an independent cohort (the Manitoba Bone Density Cohort). Overall, the GR of TBS for major osteoporotic fracture was 1.44 (95% confidence interval [CI] 1.35-1.53) when adjusted for age and time since baseline and was similar in men and women (p > 0.10). When additionally adjusted for FRAX 10-year probability of major osteoporotic fracture, TBS remained a significant, independent predictor for fracture (GR = 1.32, 95% CI 1.24-1.41). The adjustment of FRAX probability for TBS resulted in a small increase in the GR (1.76, 95% CI 1.65-1.87 versus 1.70, 95% CI 1.60-1.81). A smaller change in GR for hip fracture was observed (FRAX hip fracture probability GR 2.25 vs. 2.22). TBS is a significant predictor of fracture risk independently of FRAX. The findings support the use of TBS as a potential adjustment for FRAX probability, though the impact of the adjustment remains to be determined in the context of clinical assessment guidelines. © 2015 American Society for Bone and Mineral Research.

Segmentation d’images intravasculaires ultrasonores

L'imagerie intravasculaire ultrasonore (IVUS) est une technologie médicale par cathéter qui produit des images de coupe des vaisseaux sanguins. Elle permet de quantifier et d'étudier la morphologie de plaques d'athérosclérose en plus de visualiser la structure des vaisseaux sanguins (lumière, intima, plaque, média et adventice) en trois dimensions. Depuis quelques années, cette méthode d'imagerie est devenue un outil de choix en recherche aussi bien qu'en clinique pour l'étude de la maladie athérosclérotique. L'imagerie IVUS est par contre affectée par des artéfacts associés aux caractéristiques des capteurs ultrasonores, par la présence de cônes d'ombre causés par les calcifications ou des artères collatérales, par des plaques dont le rendu est hétérogène ou par le chatoiement ultrasonore (speckle) sanguin. L'analyse automatisée de séquences IVUS de grande taille représente donc un défi important. Une méthode de segmentation en trois dimensions (3D) basée sur l'algorithme du fast-marching à interfaces multiples est présentée. La segmentation utilise des attributs des régions et contours des images IVUS. En effet, une nouvelle fonction de vitesse de propagation des interfaces combinant les fonctions de densité de probabilité des tons de gris des composants de la paroi vasculaire et le gradient des intensités est proposée. La segmentation est grandement automatisée puisque la lumière du vaisseau est détectée de façon entièrement automatique. Dans une procédure d'initialisation originale, un minimum d'interactions est nécessaire lorsque les contours initiaux de la paroi externe du vaisseau calculés automatiquement sont proposés à l'utilisateur pour acceptation ou correction sur un nombre limité d'images de coupe longitudinale. La segmentation a été validée à l'aide de séquences IVUS in vivo provenant d'artères fémorales provenant de différents sous-groupes d'acquisitions, c'est-à-dire pré-angioplastie par ballon, post-intervention et à un examen de contrôle 1 an suivant l'intervention. Les résultats ont été comparés avec des contours étalons tracés manuellement par différents experts en analyse d'images IVUS. Les contours de la lumière et de la paroi externe du vaisseau détectés selon la méthode du fast-marching sont en accord avec les tracés manuels des experts puisque les mesures d'aire sont similaires et les différences point-à-point entre les contours sont faibles. De plus, la segmentation par fast-marching 3D s'est effectuée en un temps grandement réduit comparativement à l'analyse manuelle. Il s'agit de la première étude rapportée dans la littérature qui évalue la performance de la segmentation sur différents types d'acquisition IVUS. En conclusion, la segmentation par fast-marching combinant les informations des distributions de tons de gris et du gradient des intensités des images est précise et efficace pour l'analyse de séquences IVUS de grandes tailles. Un outil de segmentation robuste pourrait devenir largement répandu pour la tâche ardue et fastidieuse qu'est l'analyse de ce type d'images.

Fiabilité et changement minimal détectable de mesures obtenues à partir d'images enregistrées par ultrasonographie afin de caractériser l'intégrité du tendon d'Achille

Problématique : La quantification de l’intégrité du tendon d’Achille (TA) représente un défi en réadaptation. L’adoption de mesures quantitatives du TA, extraites à partir d’une image ultrasonographique (QUS), pourrait remédier à cette lacune. Objectifs : 1) Évaluer la fiabilité test-retest et la précision de mesures QUS du TA; 2) Déterminer le meilleur protocole de collecte de mesures QUS à employer en pratique clinique. Méthodologie : Un total de 23 TAs présentant des symptômes d’une tendinopathie achilléenne et 63 TAs asymptomatiques ont été évalués. Pour chaque TA, 8 images ont été enregistrées (2 visites * 2 évaluatrices * 2 images). Différents types de mesures QUS ont été prises : géométriques (épaisseur, largeur, aire), dérivées d’un histogramme des niveaux de gris et dérivées d’une matrice de co-occurrence. Une étude de généralisabilité a quantifié la fiabilité et la précision de chaque mesure QUS et une étude de décision a fait ressortir les meilleurs protocoles de prise de mesures. Résultats : Les mesures géométriques ont démontré une excellente fiabilité et précision. Les mesures dérivées de l’histogramme des niveaux de gris ont démontré une fiabilité et précision médiocres. Les mesures dérivées d’une matrice de co-occurrence ont démontré une fiabilité modérée à excellente et une précision variable. En pratique clinique, il est recommandé de moyenner les résultats de trois images collectées par un évaluateur lors d’une visite. Conclusion : L’utilisation des mesures QUS géométriques permet de quantifier l’intégrité du TA (clinique et recherche). Davantage d’études sur les mesures QUS dérivées d’une matrice de co-occurrence s’avèrent nécessaires.

Neural Network based studies on Spectroscopic Analysis and Image Processing

International School of Photonics, Cochin University of Science and Technology

A Study of Morphological Operators with Applications

The present work deals with the A study of morphological opertors with applications. Morphology is now a.necessary tool for engineers involved with imaging applications. Morphological operations have been viewed as filters the properties of which have been well studied (Heijmans, 1994). Another well-known class of non-linear filters is the class of rank order filters (Pitas and Venetsanopoulos, 1990). Soft morphological filters are a combination of morphological and weighted rank order filters (Koskinen, et al., 1991, Kuosmanen and Astola, 1995). They have been introduced to improve the behaviour of traditional morphological filters in noisy environments. The idea was to slightly relax the typical morphological definitions in such a way that a degree of robustness is achieved, while most of the desirable properties of typical morphological operations are maintained. Soft morphological filters are less sensitive to additive noise and to small variations in object shape than typical morphological filters. They can remove positive and negative impulse noise, preserving at the same time small details in images. Currently, Mathematical Morphology allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory of fuzzy sets.Fuzzy sets have proved to be strongly advantageous when representing in accuracies, not only regarding the spatial localization of objects in an image but also the membership of a certain pixel to a given class. Such inaccuracies are inherent to real images either because of the presence of indefinite limits between the structures or objects to be segmented within the image due to noisy acquisitions or directly because they are inherent to the image formation methods.

CBIR Using Local and Global Properties of Image Sub-blocks

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation and finding the corner density in each partition. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). Euclidean distance measure is used for computing the distance between the features of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods

A Sub-block Based Image Retrieval Using Modified Integrated Region Matching.

This paper proposes a content based image retrieval (CBIR) system using the local colour and texture features of selected image sub-blocks and global colour and shape features of the image. The image sub-blocks are roughly identified by segmenting the image into partitions of different configuration, finding the edge density in each partition using edge thresholding, morphological dilation. The colour and texture features of the identified regions are computed from the histograms of the quantized HSV colour space and Gray Level Co- occurrence Matrix (GLCM) respectively. A combined colour and texture feature vector is computed for each region. The shape features are computed from the Edge Histogram Descriptor (EHD). A modified Integrated Region Matching (IRM) algorithm is used for finding the minimum distance between the sub-blocks of the query and target image. Experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods