A Revision Control System for Image Editing in Collaborative Multimedia Design

Revision control is a vital component in the collaborative development of artifacts such as software code and multimedia. While revision control has been widely deployed for text files, very few attempts to control the versioning of binary files can be found in the literature. This can be inconvenient for graphics applications that use a significant amount of binary data, such as images, videos, meshes, and animations. Existing strategies such as storing whole files for individual revisions or simple binary deltas, respectively consume significant storage and obscure semantic information. To overcome these limitations, in this paper we present a revision control system for digital images that stores revisions in form of graphs. Besides, being integrated with Git, our revision control system also facilitates artistic creation processes in common image editing and digital painting workflows. A preliminary user study demonstrates the usability of the proposed system.Comment: pp. 512-517 (6 pages

Image-based quantitative analysis of gold immunochromatographic strip via cellular neural network approach

"(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works."Gold immunochromatographic strip assay provides a rapid, simple, single-copy and on-site way to detect the presence or absence of the target analyte. This paper aims to develop a method for accurately segmenting the test line and control line of the gold immunochromatographic strip (GICS) image for quantitatively determining the trace concentrations in the specimen, which can lead to more functional information than the traditional qualitative or semi-quantitative strip assay. The canny operator as well as the mathematical morphology method is used to detect and extract the GICS reading-window. Then, the test line and control line of the GICS reading-window are segmented by the cellular neural network (CNN) algorithm, where the template parameters of the CNN are designed by the switching particle swarm optimization (SPSO) algorithm for improving the performance of the CNN. It is shown that the SPSO-based CNN offers a robust method for accurately segmenting the test and control lines, and therefore serves as a novel image methodology for the interpretation of GICS. Furthermore, quantitative comparison is carried out among four algorithms in terms of the peak signal-to-noise ratio. It is concluded that the proposed CNN algorithm gives higher accuracy and the CNN is capable of parallelism and analog very-large-scale integration implementation within a remarkably efficient time

MR imaging–derived oxygen-hemoglobin dissociation curves and fetal-placental oxygen-hemoglobin affinities

PURPOSE: To generate magnetic resonance (MR) imaging–derived, oxygen-hemoglobin dissociation curves and to map fetal-placental oxygen-hemoglobin affinity in pregnant mice noninvasively by combining blood oxygen level–dependent (BOLD) T2* and oxygen-weighted T1 contrast mechanisms under different respiration challenges. MATERIALS AND METHODS: All procedures were approved by the Weizmann Institutional Animal Care and Use Committee. Pregnant mice were analyzed with MR imaging at 9.4 T on embryonic days 14.5 (eight dams and 58 fetuses; imprinting control region ICR strain) and 17.5 (21 dams and 158 fetuses) under respiration challenges ranging from hyperoxia to hypoxia (10 levels of oxygenation, 100%–10%; total imaging time, 100 minutes). A shorter protocol with normoxia to hyperoxia was also performed (five levels of oxygenation, 20%–100%; total imaging time, 60 minutes). Fast spin-echo anatomic images were obtained, followed by sequential acquisition of three-dimensional gradient-echo T2*- and T1-weighted images. Automated registration was applied to align regions of interest of the entire placenta, fetal liver, and maternal liver. Results were compared by using a two-tailed unpaired Student t test. R1 and R2* values were derived for each tissue. MR imaging–based oxygen-hemoglobin dissociation curves were constructed by nonlinear least square fitting of 1 minus the change in R2*divided by R2*at baseline as a function of R1 to a sigmoid-shaped curve. The apparent P50 (oxygen tension at which hemoglobin is 50% saturated) value was derived from the curves, calculated as the R1 scaled value (x) at which the change in R2* divided by R2*at baseline scaled (y) equals 0.5. RESULTS: The apparent P50 values were significantly lower in fetal liver than in maternal liver for both gestation stages (day 14.5: 21% ± 5 [P = .04] and day 17.5: 41% ± 7 [P < .0001]). The placenta showed a reduction of 18% ± 4 in mean apparent P50 values from day 14.5 to day 17.5 (P = .003). Reproduction of the MR imaging–based oxygen-hemoglobin dissociation curves with a shorter protocol that excluded the hypoxic periods was demonstrated. CONCLUSION: MR imaging–based oxygen-hemoglobin dissociation curves and oxygen-hemoglobin affinity information were derived for pregnant mice by using 9.4-T MR imaging, which suggests a potential to overcome the need for direct sampling of fetal or maternal blood. Online supplemental material is available for this article

Atomic-scale confinement of optical fields

In the presence of matter there is no fundamental limit preventing confinement of visible light even down to atomic scales. Achieving such confinement and the corresponding intensity enhancement inevitably requires simultaneous control over atomic-scale details of material structures and over the optical modes that such structures support. By means of self-assembly we have obtained side-by-side aligned gold nanorod dimers with robust atomically-defined gaps reaching below 0.5 nm. The existence of atomically-confined light fields in these gaps is demonstrated by observing extreme Coulomb splitting of corresponding symmetric and anti-symmetric dimer eigenmodes of more than 800 meV in white-light scattering experiments. Our results open new perspectives for atomically-resolved spectroscopic imaging, deeply nonlinear optics, ultra-sensing, cavity optomechanics as well as for the realization of novel quantum-optical devices

Developement of real time diagnostics and feedback algorithms for JET in view of the next step

Real time control of many plasma parameters will be an essential aspect in the development of reliable high performance operation of Next Step Tokamaks. The main prerequisites for any feedback scheme are the precise real-time determination of the quantities to be controlled, requiring top quality and highly reliable diagnostics, and the availability of robust control algorithms. A new set of real time diagnostics was recently implemented on JET to prove the feasibility of determining, with high accuracy and time resolution, the most important plasma quantities. With regard to feedback algorithms, new model&#8211;based controllers were developed to allow a more robust control of several plasma parameters. Both diagnostics and algorithms were successfully used in several experiments, ranging from H-mode plasmas to configuration with ITBs. Since elaboration of computationally heavy measurements is often required, significant attention was devoted to non-algorithmic methods like Digital or Cellular Neural/Nonlinear Networks. The real time hardware and software adopted architectures are also described with particular attention to their relevance to ITER.Comment: 12th International Congress on Plasma Physics, 25-29 October 2004, Nice (France

All-Optical Reinforcement Learning in Solitonic X-Junctions

L'etologia ha dimostrato che gruppi di animali o colonie possono eseguire calcoli complessi distribuendo semplici processi decisionali ai membri del gruppo. Ad esempio, le colonie di formiche possono ottimizzare le traiettorie verso il cibo eseguendo sia un rinforzo (o una cancellazione) delle tracce di feromone sia spostarsi da una traiettoria ad un'altra con feromone più forte. Questa procedura delle formiche possono essere implementati in un hardware fotonico per riprodurre l'elaborazione del segnale stigmergico. Presentiamo qui innovative giunzioni a X completamente integrate realizzate utilizzando guide d'onda solitoniche in grado di fornire entrambi i processi decisionali delle formiche. Le giunzioni a X proposte possono passare da comportamenti simmetrici (50/50) ad asimmetrici (80/20) utilizzando feedback ottici, cancellando i canali di uscita inutilizzati o rinforzando quelli usati.Ethology has shown that animal groups or colonies can perform complex calculation distributing simple decision-making processes to the group members. For example ant colonies can optimize the trajectories towards the food by performing both a reinforcement (or a cancellation) of the pheromone traces and a switch from one path to another with stronger pheromone. Such ant's processes can be implemented in a photonic hardware to reproduce stigmergic signal processing. We present innovative, completely integrated X-junctions realized using solitonic waveguides which can provide both ant's decision-making processes. The proposed X-junctions can switch from symmetric (50/50) to asymmetric behaviors (80/20) using optical feedbacks, vanishing unused output channels or reinforcing the used ones

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment.METHODS: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested.RESULTS: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed.CONCLUSIONS: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies

Distributed-memory large deformation diffeomorphic 3D image registration

We present a parallel distributed-memory algorithm for large deformation diffeomorphic registration of volumetric images that produces large isochoric deformations (locally volume preserving). Image registration is a key technology in medical image analysis. Our algorithm uses a partial differential equation constrained optimal control formulation. Finding the optimal deformation map requires the solution of a highly nonlinear problem that involves pseudo-differential operators, biharmonic operators, and pure advection operators both forward and back- ward in time. A key issue is the time to solution, which poses the demand for efficient optimization methods as well as an effective utilization of high performance computing resources. To address this problem we use a preconditioned, inexact, Gauss-Newton- Krylov solver. Our algorithm integrates several components: a spectral discretization in space, a semi-Lagrangian formulation in time, analytic adjoints, different regularization functionals (including volume-preserving ones), a spectral preconditioner, a highly optimized distributed Fast Fourier Transform, and a cubic interpolation scheme for the semi-Lagrangian time-stepping. We demonstrate the scalability of our algorithm on images with resolution of up to $1024^3$ on the "Maverick" and "Stampede" systems at the Texas Advanced Computing Center (TACC). The critical problem in the medical imaging application domain is strong scaling, that is, solving registration problems of a moderate size of $256^3$---a typical resolution for medical images. We are able to solve the registration problem for images of this size in less than five seconds on 64 x86 nodes of TACC's "Maverick" system.Comment: accepted for publication at SC16 in Salt Lake City, Utah, USA; November 201

Evaluation of a ground-based sky camera system for use in surface irradiance measurement

This paper describes the evaluation of a ground-based sky camera system for studying the effect of clouds on the level of the ambient ultraviolet radiation. The system has been developed for research in the characterization of the effect of clouds around the sun. It is the first sky camera system to be used for the assessment of cloud conditions in the vicinity of the sun, rather than a whole-sky assessment. The system features a sun-tracking sky camera with an integrated measurement of horizontally received radiation at the same location. The image-processing algorithm uses solar radiation readings to reduce reflections from the sun on the camera system being mistaken for cloud in the images. Cloud amount was estimated in an angular region of between 12.5°and 37.5° around the sun. The algorithm also estimates the amount of solar obstruction by cloud (sun not covered, partially or totally covered). The system was evaluated during September 1997 at Toowoomba, Australia (27.6°S latitude). Compared to manual assessment of 592 images, 76.5% were identified correctly by the algorithm for the degree of solar obstruction and 81.9% for cloud amount. The behavior of ultraviolet radiation levels with cloud conditions is discussed