Improved Diffuse Foreground Subtraction with the ILC Method: CMB Map and Angular Power Spectrum Using Planck and WMAP Observations

NASA Astrophysics Data System (ADS)

Sudevan, Vipin; Aluri, Pavan K.; Yadav, Sarvesh Kumar; Saha, Rajib; Souradeep, Tarun

2017-06-01

We report an improved technique for diffuse foreground minimization from Cosmic Microwave Background (CMB) maps using a new multiphase iterative harmonic space internal-linear-combination (HILC) approach. Our method nullifies a foreground leakage that was present in the old and usual iterative HILC method. In phase 1 of the multiphase technique, we obtain an initial cleaned map using the single iteration HILC approach over the desired portion of the sky. In phase 2, we obtain a final CMB map using the iterative HILC approach; however, now, to nullify the leakage, during each iteration, some of the regions of the sky that are not being cleaned in the current iteration are replaced by the corresponding cleaned portions of the phase 1 map. We bring all input frequency maps to a common and maximum possible beam and pixel resolution at the beginning of the analysis, which significantly reduces data redundancy, memory usage, and computational cost, and avoids, during the HILC weight calculation, the deconvolution of partial sky harmonic coefficients by the azimuthally symmetric beam and pixel window functions, which in a strict mathematical sense, are not well defined. Using WMAP 9 year and Planck 2015 frequency maps, we obtain foreground-cleaned CMB maps and a CMB angular power spectrum for the multipole range 2≤slant {\\ell }≤slant 2500. Our power spectrum matches the published Planck results with some differences at different multipole ranges. We validate our method by performing Monte Carlo simulations. Finally, we show that the weights for HILC foreground minimization have the intrinsic characteristic that they also tend to produce a statistically isotropic CMB map.

A comparison of multiprocessor scheduling methods for iterative data flow architectures

NASA Technical Reports Server (NTRS)

Storch, Matthew

1993-01-01

A comparative study is made between the Algorithm to Architecture Mapping Model (ATAMM) and three other related multiprocessing models from the published literature. The primary focus of all four models is the non-preemptive scheduling of large-grain iterative data flow graphs as required in real-time systems, control applications, signal processing, and pipelined computations. Important characteristics of the models such as injection control, dynamic assignment, multiple node instantiations, static optimum unfolding, range-chart guided scheduling, and mathematical optimization are identified. The models from the literature are compared with the ATAMM for performance, scheduling methods, memory requirements, and complexity of scheduling and design procedures.

A Modularized Efficient Framework for Non-Markov Time Series Estimation

NASA Astrophysics Data System (ADS)

Schamberg, Gabriel; Ba, Demba; Coleman, Todd P.

2018-06-01

We present a compartmentalized approach to finding the maximum a-posteriori (MAP) estimate of a latent time series that obeys a dynamic stochastic model and is observed through noisy measurements. We specifically consider modern signal processing problems with non-Markov signal dynamics (e.g. group sparsity) and/or non-Gaussian measurement models (e.g. point process observation models used in neuroscience). Through the use of auxiliary variables in the MAP estimation problem, we show that a consensus formulation of the alternating direction method of multipliers (ADMM) enables iteratively computing separate estimates based on the likelihood and prior and subsequently "averaging" them in an appropriate sense using a Kalman smoother. As such, this can be applied to a broad class of problem settings and only requires modular adjustments when interchanging various aspects of the statistical model. Under broad log-concavity assumptions, we show that the separate estimation problems are convex optimization problems and that the iterative algorithm converges to the MAP estimate. As such, this framework can capture non-Markov latent time series models and non-Gaussian measurement models. We provide example applications involving (i) group-sparsity priors, within the context of electrophysiologic specrotemporal estimation, and (ii) non-Gaussian measurement models, within the context of dynamic analyses of learning with neural spiking and behavioral observations.

Generalized logistic map and its application in chaos based cryptography

NASA Astrophysics Data System (ADS)

Lawnik, M.

2017-12-01

The logistic map is commonly used in, for example, chaos based cryptography. However, its properties do not render a safe construction of encryption algorithms. Thus, the scope of the paper is a proposal of generalization of the logistic map by means of a wellrecognized family of chaotic maps. In the next step, an analysis of Lyapunov exponent and the distribution of the iterative variable are studied. The obtained results confirm that the analyzed model can safely and effectively replace a classic logistic map for applications involving chaotic cryptography.

Application of a simple cerebellar model to geologic surface mapping

USGS Publications Warehouse

Hagens, A.; Doveton, J.H.

1991-01-01

Neurophysiological research into the structure and function of the cerebellum has inspired computational models that simulate information processing associated with coordination and motor movement. The cerebellar model arithmetic computer (CMAC) has a design structure which makes it readily applicable as an automated mapping device that "senses" a surface, based on a sample of discrete observations of surface elevation. The model operates as an iterative learning process, where cell weights are continuously modified by feedback to improve surface representation. The storage requirements are substantially less than those of a conventional memory allocation, and the model is extended easily to mapping in multidimensional space, where the memory savings are even greater. ?? 1991.

Fluence map optimization (FMO) with dose-volume constraints in IMRT using the geometric distance sorting method.

PubMed

Lan, Yihua; Li, Cunhua; Ren, Haozheng; Zhang, Yong; Min, Zhifang

2012-10-21

A new heuristic algorithm based on the so-called geometric distance sorting technique is proposed for solving the fluence map optimization with dose-volume constraints which is one of the most essential tasks for inverse planning in IMRT. The framework of the proposed method is basically an iterative process which begins with a simple linear constrained quadratic optimization model without considering any dose-volume constraints, and then the dose constraints for the voxels violating the dose-volume constraints are gradually added into the quadratic optimization model step by step until all the dose-volume constraints are satisfied. In each iteration step, an interior point method is adopted to solve each new linear constrained quadratic programming. For choosing the proper candidate voxels for the current dose constraint adding, a so-called geometric distance defined in the transformed standard quadratic form of the fluence map optimization model was used to guide the selection of the voxels. The new geometric distance sorting technique can mostly reduce the unexpected increase of the objective function value caused inevitably by the constraint adding. It can be regarded as an upgrading to the traditional dose sorting technique. The geometry explanation for the proposed method is also given and a proposition is proved to support our heuristic idea. In addition, a smart constraint adding/deleting strategy is designed to ensure a stable iteration convergence. The new algorithm is tested on four cases including head-neck, a prostate, a lung and an oropharyngeal, and compared with the algorithm based on the traditional dose sorting technique. Experimental results showed that the proposed method is more suitable for guiding the selection of new constraints than the traditional dose sorting method, especially for the cases whose target regions are in non-convex shapes. It is a more efficient optimization technique to some extent for choosing constraints than the dose sorting method. By integrating a smart constraint adding/deleting scheme within the iteration framework, the new technique builds up an improved algorithm for solving the fluence map optimization with dose-volume constraints.

Post-game analysis: An initial experiment for heuristic-based resource management in concurrent systems

NASA Technical Reports Server (NTRS)

Yan, Jerry C.

1987-01-01

In concurrent systems, a major responsibility of the resource management system is to decide how the application program is to be mapped onto the multi-processor. Instead of using abstract program and machine models, a generate-and-test framework known as 'post-game analysis' that is based on data gathered during program execution is proposed. Each iteration consists of (1) (a simulation of) an execution of the program; (2) analysis of the data gathered; and (3) the proposal of a new mapping that would have a smaller execution time. These heuristics are applied to predict execution time changes in response to small perturbations applied to the current mapping. An initial experiment was carried out using simple strategies on 'pipeline-like' applications. The results obtained from four simple strategies demonstrated that for this kind of application, even simple strategies can produce acceptable speed-up with a small number of iterations.

Iterative integral parameter identification of a respiratory mechanics model.

PubMed

Schranz, Christoph; Docherty, Paul D; Chiew, Yeong Shiong; Möller, Knut; Chase, J Geoffrey

2012-07-18

Patient-specific respiratory mechanics models can support the evaluation of optimal lung protective ventilator settings during ventilation therapy. Clinical application requires that the individual's model parameter values must be identified with information available at the bedside. Multiple linear regression or gradient-based parameter identification methods are highly sensitive to noise and initial parameter estimates. Thus, they are difficult to apply at the bedside to support therapeutic decisions. An iterative integral parameter identification method is applied to a second order respiratory mechanics model. The method is compared to the commonly used regression methods and error-mapping approaches using simulated and clinical data. The clinical potential of the method was evaluated on data from 13 Acute Respiratory Distress Syndrome (ARDS) patients. The iterative integral method converged to error minima 350 times faster than the Simplex Search Method using simulation data sets and 50 times faster using clinical data sets. Established regression methods reported erroneous results due to sensitivity to noise. In contrast, the iterative integral method was effective independent of initial parameter estimations, and converged successfully in each case tested. These investigations reveal that the iterative integral method is beneficial with respect to computing time, operator independence and robustness, and thus applicable at the bedside for this clinical application.

On the safety of ITER accelerators.

PubMed

Li, Ge

2013-01-01

Three 1 MV/40A accelerators in heating neutral beams (HNB) are on track to be implemented in the International Thermonuclear Experimental Reactor (ITER). ITER may produce 500 MWt of power by 2026 and may serve as a green energy roadmap for the world. They will generate -1 MV 1 h long-pulse ion beams to be neutralised for plasma heating. Due to frequently occurring vacuum sparking in the accelerators, the snubbers are used to limit the fault arc current to improve ITER safety. However, recent analyses of its reference design have raised concerns. General nonlinear transformer theory is developed for the snubber to unify the former snubbers' different design models with a clear mechanism. Satisfactory agreement between theory and tests indicates that scaling up to a 1 MV voltage may be possible. These results confirm the nonlinear process behind transformer theory and map out a reliable snubber design for a safer ITER.

On the safety of ITER accelerators

PubMed Central

Li, Ge

2013-01-01

Three 1 MV/40A accelerators in heating neutral beams (HNB) are on track to be implemented in the International Thermonuclear Experimental Reactor (ITER). ITER may produce 500 MWt of power by 2026 and may serve as a green energy roadmap for the world. They will generate −1 MV 1 h long-pulse ion beams to be neutralised for plasma heating. Due to frequently occurring vacuum sparking in the accelerators, the snubbers are used to limit the fault arc current to improve ITER safety. However, recent analyses of its reference design have raised concerns. General nonlinear transformer theory is developed for the snubber to unify the former snubbers' different design models with a clear mechanism. Satisfactory agreement between theory and tests indicates that scaling up to a 1 MV voltage may be possible. These results confirm the nonlinear process behind transformer theory and map out a reliable snubber design for a safer ITER. PMID:24008267

A Combined Approach to Cartographic Displacement for Buildings Based on Skeleton and Improved Elastic Beam Algorithm

PubMed Central

Liu, Yuangang; Guo, Qingsheng; Sun, Yageng; Ma, Xiaoya

2014-01-01

Scale reduction from source to target maps inevitably leads to conflicts of map symbols in cartography and geographic information systems (GIS). Displacement is one of the most important map generalization operators and it can be used to resolve the problems that arise from conflict among two or more map objects. In this paper, we propose a combined approach based on constraint Delaunay triangulation (CDT) skeleton and improved elastic beam algorithm for automated building displacement. In this approach, map data sets are first partitioned. Then the displacement operation is conducted in each partition as a cyclic and iterative process of conflict detection and resolution. In the iteration, the skeleton of the gap spaces is extracted using CDT. It then serves as an enhanced data model to detect conflicts and construct the proximity graph. Then, the proximity graph is adjusted using local grouping information. Under the action of forces derived from the detected conflicts, the proximity graph is deformed using the improved elastic beam algorithm. In this way, buildings are displaced to find an optimal compromise between related cartographic constraints. To validate this approach, two topographic map data sets (i.e., urban and suburban areas) were tested. The results were reasonable with respect to each constraint when the density of the map was not extremely high. In summary, the improvements include (1) an automated parameter-setting method for elastic beams, (2) explicit enforcement regarding the positional accuracy constraint, added by introducing drag forces, (3) preservation of local building groups through displacement over an adjusted proximity graph, and (4) an iterative strategy that is more likely to resolve the proximity conflicts than the one used in the existing elastic beam algorithm. PMID:25470727

A Maximum Likelihood Approach to Functional Mapping of Longitudinal Binary Traits

PubMed Central

Wang, Chenguang; Li, Hongying; Wang, Zhong; Wang, Yaqun; Wang, Ningtao; Wang, Zuoheng; Wu, Rongling

2013-01-01

Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits. PMID:23183762

Sparsity-constrained PET image reconstruction with learned dictionaries

NASA Astrophysics Data System (ADS)

Tang, Jing; Yang, Bao; Wang, Yanhua; Ying, Leslie

2016-09-01

PET imaging plays an important role in scientific and clinical measurement of biochemical and physiological processes. Model-based PET image reconstruction such as the iterative expectation maximization algorithm seeking the maximum likelihood solution leads to increased noise. The maximum a posteriori (MAP) estimate removes divergence at higher iterations. However, a conventional smoothing prior or a total-variation (TV) prior in a MAP reconstruction algorithm causes over smoothing or blocky artifacts in the reconstructed images. We propose to use dictionary learning (DL) based sparse signal representation in the formation of the prior for MAP PET image reconstruction. The dictionary to sparsify the PET images in the reconstruction process is learned from various training images including the corresponding MR structural image and a self-created hollow sphere. Using simulated and patient brain PET data with corresponding MR images, we study the performance of the DL-MAP algorithm and compare it quantitatively with a conventional MAP algorithm, a TV-MAP algorithm, and a patch-based algorithm. The DL-MAP algorithm achieves improved bias and contrast (or regional mean values) at comparable noise to what the other MAP algorithms acquire. The dictionary learned from the hollow sphere leads to similar results as the dictionary learned from the corresponding MR image. Achieving robust performance in various noise-level simulation and patient studies, the DL-MAP algorithm with a general dictionary demonstrates its potential in quantitative PET imaging.

Quantification of 2D elemental distribution maps of intermediate-thick biological sections by low energy synchrotron μ-X-ray fluorescence spectrometry

NASA Astrophysics Data System (ADS)

Kump, P.; Vogel-Mikuš, K.

2018-05-01

Two fundamental-parameter (FP) based models for quantification of 2D elemental distribution maps of intermediate-thick biological samples by synchrotron low energy μ-X-ray fluorescence spectrometry (SR-μ-XRF) are presented and applied to the elemental analysis in experiments with monochromatic focused photon beam excitation at two low energy X-ray fluorescence beamlines—TwinMic, Elettra Sincrotrone Trieste, Italy, and ID21, ESRF, Grenoble, France. The models assume intermediate-thick biological samples composed of measured elements, the sources of the measurable spectral lines, and by the residual matrix, which affects the measured intensities through absorption. In the first model a fixed residual matrix of the sample is assumed, while in the second model the residual matrix is obtained by the iteration refinement of elemental concentrations and an adjusted residual matrix. The absorption of the incident focused beam in the biological sample at each scanned pixel position, determined from the output of a photodiode or a CCD camera, is applied as a control in the iteration procedure of quantification.

Integration of magnetic field and electron reflection data to improve Mars internal magnetic field model definition at 185 km altitude

NASA Astrophysics Data System (ADS)

Mozzoni, D. T.; Cain, J. C.; Lillis, R. J.

2012-12-01

Because no further projects are planned to better define the global magnetic field about Mars, it is important to utilize present the Mars Global Surveyor (MGS) Magnetometer/Electron Reflectometer (MAG/ER) data to its fullest. Challenges in deriving an accurate model include the fact that the mapping orbit of MGS was limited to two local times, and also had a narrow distribution of data ranging from only southern latitudes below 350 km to only northern latitudes over 400 km. The aerobraking and science phasing orbit data below 350 km down to near 100 km was nearly all on the sunlit side with its strong distortions from the solar wind and embedded ionospheric currents. The improvement reported herein is from the addition of the projected total field evaluated at 185 km above the areoid. These data are derived from extrapolation of the pitch angle distributions of ER data to the reflection altitudes and adjustment to a common data altitude. Crucial to this analysis is the angular distribution of the magnetic field itself below MGS. Thus it was an iterative process whereby the 185 km data sets were recalculated based on the last iterative solutions from the magnetic field models derived including these data. The statistical improvements at the ER mapped altitudes after 5 iterations was to reduce the initial 2.0 nT sigma differences with a Gaussian spread of 20 nT to 0.5 nT and a spread of 12 nT. Unfortunately, many areas of very high field especially provided no data as they were on closed field lines. However, the iterative solutions also improved the 185 km scalar maps significantly from the original based on linear field line estimates, up to several hundred nT. The next step planned is to utilize the concept suggested by Connerney to use along-track gradients, especially those at lowest altitudes on the dayside, to input to the model sets. Preliminary tests indicate the possibility of added improvements in the missing ER data areas once this technique is perfected.

Hybrid cloud and cluster computing paradigms for life science applications

PubMed Central

2010-01-01

Background Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Results Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. Conclusions The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. Methods We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments. PMID:21210982

Hybrid cloud and cluster computing paradigms for life science applications.

PubMed

Qiu, Judy; Ekanayake, Jaliya; Gunarathne, Thilina; Choi, Jong Youl; Bae, Seung-Hee; Li, Hui; Zhang, Bingjing; Wu, Tak-Lon; Ruan, Yang; Ekanayake, Saliya; Hughes, Adam; Fox, Geoffrey

2010-12-21

Clouds and MapReduce have shown themselves to be a broadly useful approach to scientific computing especially for parallel data intensive applications. However they have limited applicability to some areas such as data mining because MapReduce has poor performance on problems with an iterative structure present in the linear algebra that underlies much data analysis. Such problems can be run efficiently on clusters using MPI leading to a hybrid cloud and cluster environment. This motivates the design and implementation of an open source Iterative MapReduce system Twister. Comparisons of Amazon, Azure, and traditional Linux and Windows environments on common applications have shown encouraging performance and usability comparisons in several important non iterative cases. These are linked to MPI applications for final stages of the data analysis. Further we have released the open source Twister Iterative MapReduce and benchmarked it against basic MapReduce (Hadoop) and MPI in information retrieval and life sciences applications. The hybrid cloud (MapReduce) and cluster (MPI) approach offers an attractive production environment while Twister promises a uniform programming environment for many Life Sciences applications. We used commercial clouds Amazon and Azure and the NSF resource FutureGrid to perform detailed comparisons and evaluations of different approaches to data intensive computing. Several applications were developed in MPI, MapReduce and Twister in these different environments.

Improved cryoEM-Guided Iterative Molecular Dynamics–Rosetta Protein Structure Refinement Protocol for High Precision Protein Structure Prediction

PubMed Central

2016-01-01

Many excellent methods exist that incorporate cryo-electron microscopy (cryoEM) data to constrain computational protein structure prediction and refinement. Previously, it was shown that iteration of two such orthogonal sampling and scoring methods – Rosetta and molecular dynamics (MD) simulations – facilitated exploration of conformational space in principle. Here, we go beyond a proof-of-concept study and address significant remaining limitations of the iterative MD–Rosetta protein structure refinement protocol. Specifically, all parts of the iterative refinement protocol are now guided by medium-resolution cryoEM density maps, and previous knowledge about the native structure of the protein is no longer necessary. Models are identified solely based on score or simulation time. All four benchmark proteins showed substantial improvement through three rounds of the iterative refinement protocol. The best-scoring final models of two proteins had sub-Ångstrom RMSD to the native structure over residues in secondary structure elements. Molecular dynamics was most efficient in refining secondary structure elements and was thus highly complementary to the Rosetta refinement which is most powerful in refining side chains and loop regions. PMID:25883538

A complete solution of cartographic displacement based on elastic beams model and Delaunay triangulation

NASA Astrophysics Data System (ADS)

Liu, Y.; Guo, Q.; Sun, Y.

2014-04-01

In map production and generalization, it is inevitable to arise some spatial conflicts, but the detection and resolution of these spatial conflicts still requires manual operation. It is become a bottleneck hindering the development of automated cartographic generalization. Displacement is the most useful contextual operator that is often used for resolving the conflicts arising between two or more map objects. Automated generalization researches have reported many approaches of displacement including sequential approaches and optimization approaches. As an excellent optimization approach on the basis of energy minimization principles, elastic beams model has been used in resolving displacement problem of roads and buildings for several times. However, to realize a complete displacement solution, techniques of conflict detection and spatial context analysis should be also take into consideration. So we proposed a complete solution of displacement based on the combined use of elastic beams model and constrained Delaunay triangulation (CDT) in this paper. The solution designed as a cyclic and iterative process containing two phases: detection phase and displacement phase. In detection phase, CDT of map is use to detect proximity conflicts, identify spatial relationships and structures, and construct auxiliary structure, so as to support the displacement phase on the basis of elastic beams. In addition, for the improvements of displacement algorithm, a method for adaptive parameters setting and a new iterative strategy are put forward. Finally, we implemented our solution on a testing map generalization platform, and successfully tested it against 2 hand-generated test datasets of roads and buildings respectively.

Surface registration technique for close-range mapping applications

NASA Astrophysics Data System (ADS)

Habib, Ayman F.; Cheng, Rita W. T.

2006-08-01

Close-range mapping applications such as cultural heritage restoration, virtual reality modeling for the entertainment industry, and anatomical feature recognition for medical activities require 3D data that is usually acquired by high resolution close-range laser scanners. Since these datasets are typically captured from different viewpoints and/or at different times, accurate registration is a crucial procedure for 3D modeling of mapped objects. Several registration techniques are available that work directly with the raw laser points or with extracted features from the point cloud. Some examples include the commonly known Iterative Closest Point (ICP) algorithm and a recently proposed technique based on matching spin-images. This research focuses on developing a surface matching algorithm that is based on the Modified Iterated Hough Transform (MIHT) and ICP to register 3D data. The proposed algorithm works directly with the raw 3D laser points and does not assume point-to-point correspondence between two laser scans. The algorithm can simultaneously establish correspondence between two surfaces and estimates the transformation parameters relating them. Experiment with two partially overlapping laser scans of a small object is performed with the proposed algorithm and shows successful registration. A high quality of fit between the two scans is achieved and improvement is found when compared to the results obtained using the spin-image technique. The results demonstrate the feasibility of the proposed algorithm for registering 3D laser scanning data in close-range mapping applications to help with the generation of complete 3D models.

MO-DE-207A-08: Four-Dimensional Cone-Beam CT Iterative Reconstruction with Time-Ordered Chain Graph Model for Non-Periodic Organ Motion and Deformation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nakano, M; Haga, A; Hanaoka, S

2016-06-15

Purpose: The purpose of this study is to propose a new concept of four-dimensional (4D) cone-beam CT (CBCT) reconstruction for non-periodic organ motion using the Time-ordered Chain Graph Model (TCGM), and to compare the reconstructed results with the previously proposed methods, the total variation-based compressed sensing (TVCS) and prior-image constrained compressed sensing (PICCS). Methods: CBCT reconstruction method introduced in this study consisted of maximum a posteriori (MAP) iterative reconstruction combined with a regularization term derived from a concept of TCGM, which includes a constraint coming from the images of neighbouring time-phases. The time-ordered image series were concurrently reconstructed in themore » MAP iterative reconstruction framework. Angular range of projections for each time-phase was 90 degrees for TCGM and PICCS, and 200 degrees for TVCS. Two kinds of projection data, an elliptic-cylindrical digital phantom data and two clinical patients’ data, were used for reconstruction. The digital phantom contained an air sphere moving 3 cm along longitudinal axis, and temporal resolution of each method was evaluated by measuring the penumbral width of reconstructed moving air sphere. The clinical feasibility of non-periodic time-ordered 4D CBCT reconstruction was also examined using projection data of prostate cancer patients. Results: The results of reconstructed digital phantom shows that the penumbral widths of TCGM yielded the narrowest result; PICCS and TCGM were 10.6% and 17.4% narrower than that of TVCS, respectively. This suggests that the TCGM has the better temporal resolution than the others. Patients’ CBCT projection data were also reconstructed and all three reconstructed results showed motion of rectal gas and stool. The result of TCGM provided visually clearer and less blurring images. Conclusion: The present study demonstrates that the new concept for 4D CBCT reconstruction, TCGM, combined with MAP iterative reconstruction framework enables time-ordered image reconstruction with narrower time-window.« less

Iterative optimization method for design of quantitative magnetization transfer imaging experiments.

PubMed

Levesque, Ives R; Sled, John G; Pike, G Bruce

2011-09-01

Quantitative magnetization transfer imaging (QMTI) using spoiled gradient echo sequences with pulsed off-resonance saturation can be a time-consuming technique. A method is presented for selection of an optimum experimental design for quantitative magnetization transfer imaging based on the iterative reduction of a discrete sampling of the Z-spectrum. The applicability of the technique is demonstrated for human brain white matter imaging at 1.5 T and 3 T, and optimal designs are produced to target specific model parameters. The optimal number of measurements and the signal-to-noise ratio required for stable parameter estimation are also investigated. In vivo imaging results demonstrate that this optimal design approach substantially improves parameter map quality. The iterative method presented here provides an advantage over free form optimal design methods, in that pragmatic design constraints are readily incorporated. In particular, the presented method avoids clustering and repeated measures in the final experimental design, an attractive feature for the purpose of magnetization transfer model validation. The iterative optimal design technique is general and can be applied to any method of quantitative magnetization transfer imaging. Copyright © 2011 Wiley-Liss, Inc.

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles.

PubMed

He, Bo; Liu, Yang; Dong, Diya; Shen, Yue; Yan, Tianhong; Nian, Rui

2015-08-13

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well.

High-order computer-assisted estimates of topological entropy

NASA Astrophysics Data System (ADS)

Grote, Johannes

The concept of Taylor Models is introduced, which offers highly accurate C0-estimates for the enclosures of functional dependencies, combining high-order Taylor polynomial approximation of functions and rigorous estimates of the truncation error, performed using verified interval arithmetic. The focus of this work is on the application of Taylor Models in algorithms for strongly nonlinear dynamical systems. A method to obtain sharp rigorous enclosures of Poincare maps for certain types of flows and surfaces is developed and numerical examples are presented. Differential algebraic techniques allow the efficient and accurate computation of polynomial approximations for invariant curves of certain planar maps around hyperbolic fixed points. Subsequently we introduce a procedure to extend these polynomial curves to verified Taylor Model enclosures of local invariant manifolds with C0-errors of size 10-10--10 -14, and proceed to generate the global invariant manifold tangle up to comparable accuracy through iteration in Taylor Model arithmetic. Knowledge of the global manifold structure up to finite iterations of the local manifold pieces enables us to find all homoclinic and heteroclinic intersections in the generated manifold tangle. Combined with the mapping properties of the homoclinic points and their ordering we are able to construct a subshift of finite type as a topological factor of the original planar system to obtain rigorous lower bounds for its topological entropy. This construction is fully automatic and yields homoclinic tangles with several hundred homoclinic points. As an example rigorous lower bounds for the topological entropy of the Henon map are computed, which to the best knowledge of the authors yield the largest such estimates published so far.

[Impact to Z-score Mapping of Hyperacute Stroke Images by Computed Tomography in Adaptive Statistical Iterative Reconstruction].

PubMed

Watanabe, Shota; Sakaguchi, Kenta; Hosono, Makoto; Ishii, Kazunari; Murakami, Takamichi; Ichikawa, Katsuhiro

The purpose of this study was to evaluate the effect of a hybrid-type iterative reconstruction method on Z-score mapping of hyperacute stroke in unenhanced computed tomography (CT) images. We used a hybrid-type iterative reconstruction [adaptive statistical iterative reconstruction (ASiR)] implemented in a CT system (Optima CT660 Pro advance, GE Healthcare). With 15 normal brain cases, we reconstructed CT images with a filtered back projection (FBP) and ASiR with a blending factor of 100% (ASiR100%). Two standardized normal brain data were created from normal databases of FBP images (FBP-NDB) and ASiR100% images (ASiR-NDB), and standard deviation (SD) values in basal ganglia were measured. The Z-score mapping was performed for 12 hyperacute stroke cases by using FBP-NDB and ASiR-NDB, and compared Z-score value on hyperacute stroke area and normal area between FBP-NDB and ASiR-NDB. By using ASiR-NDB, the SD value of standardized brain was decreased by 16%. The Z-score value of ASiR-NDB on hyperacute stroke area was significantly higher than FBP-NDB (p<0.05). Therefore, the use of images reconstructed with ASiR100% for Z-score mapping had potential to improve the accuracy of Z-score mapping.

A model reduction approach to numerical inversion for a parabolic partial differential equation

NASA Astrophysics Data System (ADS)

Borcea, Liliana; Druskin, Vladimir; Mamonov, Alexander V.; Zaslavsky, Mikhail

2014-12-01

We propose a novel numerical inversion algorithm for the coefficients of parabolic partial differential equations, based on model reduction. The study is motivated by the application of controlled source electromagnetic exploration, where the unknown is the subsurface electrical resistivity and the data are time resolved surface measurements of the magnetic field. The algorithm presented in this paper considers inversion in one and two dimensions. The reduced model is obtained with rational interpolation in the frequency (Laplace) domain and a rational Krylov subspace projection method. It amounts to a nonlinear mapping from the function space of the unknown resistivity to the small dimensional space of the parameters of the reduced model. We use this mapping as a nonlinear preconditioner for the Gauss-Newton iterative solution of the inverse problem. The advantage of the inversion algorithm is twofold. First, the nonlinear preconditioner resolves most of the nonlinearity of the problem. Thus the iterations are less likely to get stuck in local minima and the convergence is fast. Second, the inversion is computationally efficient because it avoids repeated accurate simulations of the time-domain response. We study the stability of the inversion algorithm for various rational Krylov subspaces, and assess its performance with numerical experiments.

Development of 3D Oxide Fuel Mechanics Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spencer, B. W.; Casagranda, A.; Pitts, S. A.

This report documents recent work to improve the accuracy and robustness of the mechanical constitutive models used in the BISON fuel performance code. These developments include migration of the fuel mechanics models to be based on the MOOSE Tensor Mechanics module, improving the robustness of the smeared cracking model, implementing a capability to limit the time step size based on material model response, and improving the robustness of the return mapping iterations used in creep and plasticity models.

Ecology and space: A case study in mapping harmful invasive species

USGS Publications Warehouse

David T. Barnett,; Jarnevich, Catherine S.; Chong, Geneva W.; Stohlgren, Thomas J.; Sunil Kumar,; Holcombe, Tracy R.; Brunn, Stanley D.; Dodge, Martin

2017-01-01

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass (Bromus tectorum) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Fusion of range camera and photogrammetry: a systematic procedure for improving 3-D models metric accuracy.

PubMed

Guidi, G; Beraldin, J A; Ciofi, S; Atzeni, C

2003-01-01

The generation of three-dimensional (3-D) digital models produced by optical technologies in some cases involves metric errors. This happens when small high-resolution 3-D images are assembled together in order to model a large object. In some applications, as for example 3-D modeling of Cultural Heritage, the problem of metric accuracy is a major issue and no methods are currently available for enhancing it. The authors present a procedure by which the metric reliability of the 3-D model, obtained through iterative alignments of many range maps, can be guaranteed to a known acceptable level. The goal is the integration of the 3-D range camera system with a close range digital photogrammetry technique. The basic idea is to generate a global coordinate system determined by the digital photogrammetric procedure, measuring the spatial coordinates of optical targets placed around the object to be modeled. Such coordinates, set as reference points, allow the proper rigid motion of few key range maps, including a portion of the targets, in the global reference system defined by photogrammetry. The other 3-D images are normally aligned around these locked images with usual iterative algorithms. Experimental results on an anthropomorphic test object, comparing the conventional and the proposed alignment method, are finally reported.

Integrable mappings and the notion of anticonfinement

NASA Astrophysics Data System (ADS)

Mase, T.; Willox, R.; Ramani, A.; Grammaticos, B.

2018-06-01

We examine the notion of anticonfinement and the role it has to play in the singularity analysis of discrete systems. A singularity is said to be anticonfined if singular values continue to arise indefinitely for the forward and backward iterations of a mapping, with only a finite number of iterates taking regular values in between. We show through several concrete examples that the behaviour of some anticonfined singularities is strongly related to the integrability properties of the discrete mappings in which they arise, and we explain how to use this information to decide on the integrability or non-integrability of the mapping.

An Iterative Learning Algorithm to Map Oil Palm Plantations from Synthetic Aperture Radar and Crowdsourcing

NASA Astrophysics Data System (ADS)

Pinto, N.; Zhang, Z.; Perger, C.; Aguilar-Amuchastegui, N.; Almeyda Zambrano, A. M.; Broadbent, E. N.; Simard, M.; Banerjee, S.

2017-12-01

The oil palm Elaeis spp. grows exclusively in the tropics and provides 30% of the world's vegetable oil. While oil palm-derived biodiesel can reduce carbon emissions from fossil fuels, plantation establishment may be associated with peat fires and deforestation. The ability to monitor plantation establishment and their expansion over carbon-rich tropical forests is critical for quantifying the net impact of oil palm commodities on carbon fluxes. Our objective is to develop a robust methodology to map oil palm plantations in tropical biomes, based on Synthetic Aperture Radar (SAR) from Sentinel-1, ALOS/PALSAR2, and UAVSAR. The C- and L-band signal from these instruments are sensitive to vegetation parameters such as canopy volume, trunk shape, and trunk spatial arrangement, that are critical to differentiate crops from forests and native palms. Based on Bayesian statistics, the learning algorithm employed here adapts to growing knowledge as sites and trainning points are added. We will present an iterative approach wherein a model is initially built at the site with the most training points - in our case, Costa Rica. Model posteriors from Costa Rica, depicting polarimetric signatures of oil palm plantations, are then used as priors in a classification exercise taking place in South Kalimantan. Results are evaluated by local researchers using the LACO Wiki interface. All validation points, including missclassified sites, are used in an additional iteration to improve model results to >90% overall accuracy. We report on the impact of plantation age on polarimetric signatures, and we also compare model performance with and without L-band data.

Simultaneous Localization and Mapping with Iterative Sparse Extended Information Filter for Autonomous Vehicles

PubMed Central

He, Bo; Liu, Yang; Dong, Diya; Shen, Yue; Yan, Tianhong; Nian, Rui

2015-01-01

In this paper, a novel iterative sparse extended information filter (ISEIF) was proposed to solve the simultaneous localization and mapping problem (SLAM), which is very crucial for autonomous vehicles. The proposed algorithm solves the measurement update equations with iterative methods adaptively to reduce linearization errors. With the scalability advantage being kept, the consistency and accuracy of SEIF is improved. Simulations and practical experiments were carried out with both a land car benchmark and an autonomous underwater vehicle. Comparisons between iterative SEIF (ISEIF), standard EKF and SEIF are presented. All of the results convincingly show that ISEIF yields more consistent and accurate estimates compared to SEIF and preserves the scalability advantage over EKF, as well. PMID:26287194

Correction of phase velocity bias caused by strong directional noise sources in high-frequency ambient noise tomography: a case study in Karamay, China

NASA Astrophysics Data System (ADS)

Wang, K.; Luo, Y.; Yang, Y.

2016-12-01

We collect two months of ambient noise data recorded by 35 broadband seismic stations in a 9×11 km area near Karamay, China, and do cross-correlation of noise data between all station pairs. Array beamforming analysis of the ambient noise data shows that ambient noise sources are unevenly distributed and the most energetic ambient noise mainly comes from azimuths of 40o-70o. As a consequence of the strong directional noise sources, surface wave waveforms of the cross-correlations at 1-5 Hz show clearly azimuthal dependence, and direct dispersion measurements from cross-correlations are strongly biased by the dominant noise energy. This bias renders that the dispersion measurements from cross-correlations do not accurately reflect the interstation velocities of surface waves propagating directly from one station to the other, that is, the cross-correlation functions do not retrieve Empirical Green's Functions accurately. To correct the bias caused by unevenly distributed noise sources, we adopt an iterative inversion procedure. The iterative inversion procedure, based on plane-wave modeling, includes three steps: (1) surface wave tomography, (2) estimation of ambient noise energy and (3) phase velocities correction. First, we use synthesized data to test efficiency and stability of the iterative procedure for both homogeneous and heterogeneous media. The testing results show that: (1) the amplitudes of phase velocity bias caused by directional noise sources are significant, reaching 2% and 10% for homogeneous and heterogeneous media, respectively; (2) phase velocity bias can be corrected by the iterative inversion procedure and the convergences of inversion depend on the starting phase velocity map and the complexity of the media. By applying the iterative approach to the real data in Karamay, we further show that phase velocity maps converge after ten iterations and the phase velocity map based on corrected interstation dispersion measurements are more consistent with results from geology surveys than those based on uncorrected ones. As ambient noise in high frequency band (>1Hz) is mostly related to human activities or climate events, both of which have strong directivity, the iterative approach demonstrated here helps improve the accuracy and resolution of ANT in imaging shallow earth structures.

Tubular Crystals and Helical Arrays: Structural Determination of HIV-1 Capsid Assemblies Using Iterative Helical Real-Space Reconstruction

PubMed Central

Zhang, Peijun; Meng, Xin; Zhao, Gongpu

2013-01-01

Helical structures are important in many different life forms and are well-suited for structural studies by cryo-EM. A unique feature of helical objects is that a single projection image contains all the views needed to perform a three-dimensional (3D) crystallographic reconstruction. Here, we use HIV-1 capsid assemblies to illustrate the detailed approaches to obtain 3D density maps from helical objects. Mature HIV-1 particles contain a conical- or tubular-shaped capsid that encloses the viral RNA genome and performs essential functions in the virus life cycle. The capsid is composed of capsid protein (CA) oligomers which are helically arranged on the surface. The N-terminal domain (NTD) of CA is connected to its C-terminal domain (CTD) through a flexible hinge. Structural analysis of two- and three-dimensional crystals provided molecular models of the capsid protein (CA) and its oligomer forms. We determined the 3D density map of helically assembled HIV-1 CA hexamers at 16 Å resolution using an iterative helical real-space reconstruction method. Docking of atomic models of CA-NTD and CA-CTD dimer into the electron density map indicated that the CTD dimer interface is retained in the assembled CA. Furthermore, molecular docking revealed an additional, novel CTD trimer interface. PMID:23132072

An Iterative Interplanetary Scintillation (IPS) Analysis Using Time-dependent 3-D MHD Models as Kernels

NASA Astrophysics Data System (ADS)

Jackson, B. V.; Yu, H. S.; Hick, P. P.; Buffington, A.; Odstrcil, D.; Kim, T. K.; Pogorelov, N. V.; Tokumaru, M.; Bisi, M. M.; Kim, J.; Yun, J.

2017-12-01

The University of California, San Diego has developed an iterative remote-sensing time-dependent three-dimensional (3-D) reconstruction technique which provides volumetric maps of density, velocity, and magnetic field. We have applied this technique in near real time for over 15 years with a kinematic model approximation to fit data from ground-based interplanetary scintillation (IPS) observations. Our modeling concept extends volumetric data from an inner boundary placed above the Alfvén surface out to the inner heliosphere. We now use this technique to drive 3-D MHD models at their inner boundary and generate output 3-D data files that are fit to remotely-sensed observations (in this case IPS observations), and iterated. These analyses are also iteratively fit to in-situ spacecraft measurements near Earth. To facilitate this process, we have developed a traceback from input 3-D MHD volumes to yield an updated boundary in density, temperature, and velocity, which also includes magnetic-field components. Here we will show examples of this analysis using the ENLIL 3D-MHD and the University of Alabama Multi-Scale Fluid-Kinetic Simulation Suite (MS-FLUKSS) heliospheric codes. These examples help refine poorly-known 3-D MHD variables (i.e., density, temperature), and parameters (gamma) by fitting heliospheric remotely-sensed data between the region near the solar surface and in-situ measurements near Earth.

A novel color image encryption scheme using alternate chaotic mapping structure

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Zhao, Yuanyuan; Zhang, Huili; Guo, Kang

2016-07-01

This paper proposes an color image encryption algorithm using alternate chaotic mapping structure. Initially, we use the R, G and B components to form a matrix. Then one-dimension logistic and two-dimension logistic mapping is used to generate a chaotic matrix, then iterate two chaotic mappings alternately to permute the matrix. For every iteration, XOR operation is adopted to encrypt plain-image matrix, then make further transformation to diffuse the matrix. At last, the encrypted color image is obtained from the confused matrix. Theoretical analysis and experimental results has proved the cryptosystem is secure and practical, and it is suitable for encrypting color images.

Strong Convergence for a Finite Family of Generalized Asymptotically Nonexpansive Mappings

NASA Astrophysics Data System (ADS)

Ma, Zhi-Hong; Chen, Ru-Dond

The purpose of this paper is to show the convergence theorems for generalized asymptotically nonexpansive mappings and asymptotically nonexpansive mappings in Banach spaces by using a new iteration which is a natural generalization of the implicit iteration. In the meantime, we give the necessary and sufficient conditions of the strong convergence to approximate a common fixed point and modify some flaw in the results of Thakur [11]. As one will see, the results presented in this paper are an extension of the corresponding results [8,11].

Multiresolution saliency map based object segmentation

NASA Astrophysics Data System (ADS)

Yang, Jian; Wang, Xin; Dai, ZhenYou

2015-11-01

Salient objects' detection and segmentation are gaining increasing research interest in recent years. A saliency map can be obtained from different models presented in previous studies. Based on this saliency map, the most salient region (MSR) in an image can be extracted. This MSR, generally a rectangle, can be used as the initial parameters for object segmentation algorithms. However, to our knowledge, all of those saliency maps are represented in a unitary resolution although some models have even introduced multiscale principles in the calculation process. Furthermore, some segmentation methods, such as the well-known GrabCut algorithm, need more iteration time or additional interactions to get more precise results without predefined pixel types. A concept of a multiresolution saliency map is introduced. This saliency map is provided in a multiresolution format, which naturally follows the principle of the human visual mechanism. Moreover, the points in this map can be utilized to initialize parameters for GrabCut segmentation by labeling the feature pixels automatically. Both the computing speed and segmentation precision are evaluated. The results imply that this multiresolution saliency map-based object segmentation method is simple and efficient.

Learning to read aloud: A neural network approach using sparse distributed memory

NASA Technical Reports Server (NTRS)

Joglekar, Umesh Dwarkanath

1989-01-01

An attempt to solve a problem of text-to-phoneme mapping is described which does not appear amenable to solution by use of standard algorithmic procedures. Experiments based on a model of distributed processing are also described. This model (sparse distributed memory (SDM)) can be used in an iterative supervised learning mode to solve the problem. Additional improvements aimed at obtaining better performance are suggested.

Study on monostable and bistable reaction-diffusion equations by iteration of travelling wave maps

NASA Astrophysics Data System (ADS)

Yi, Taishan; Chen, Yuming

2017-12-01

In this paper, based on the iterative properties of travelling wave maps, we develop a new method to obtain spreading speeds and asymptotic propagation for monostable and bistable reaction-diffusion equations. Precisely, for Dirichlet problems of monostable reaction-diffusion equations on the half line, by making links between travelling wave maps and integral operators associated with the Dirichlet diffusion kernel (the latter is NOT invariant under translation), we obtain some iteration properties of the Dirichlet diffusion and some a priori estimates on nontrivial solutions of Dirichlet problems under travelling wave transformation. We then provide the asymptotic behavior of nontrivial solutions in the space-time region for Dirichlet problems. These enable us to develop a unified method to obtain results on heterogeneous steady states, travelling waves, spreading speeds, and asymptotic spreading behavior for Dirichlet problem of monostable reaction-diffusion equations on R+ as well as of monostable/bistable reaction-diffusion equations on R.

Iterative framework radiation hybrid mapping

USDA-ARS?s Scientific Manuscript database

Building comprehensive radiation hybrid maps for large sets of markers is a computationally expensive process, since the basic mapping problem is equivalent to the traveling salesman problem. The mapping problem is also susceptible to noise, and as a result, it is often beneficial to remove markers ...

Numerical solution of Euler's equation by perturbed functionals

NASA Technical Reports Server (NTRS)

Dey, S. K.

1985-01-01

A perturbed functional iteration has been developed to solve nonlinear systems. It adds at each iteration level, unique perturbation parameters to nonlinear Gauss-Seidel iterates which enhances its convergence properties. As convergence is approached these parameters are damped out. Local linearization along the diagonal has been used to compute these parameters. The method requires no computation of Jacobian or factorization of matrices. Analysis of convergence depends on properties of certain contraction-type mappings, known as D-mappings. In this article, application of this method to solve an implicit finite difference approximation of Euler's equation is studied. Some representative results for the well known shock tube problem and compressible flows in a nozzle are given.

Quantitative susceptibility mapping of human brain at 3T: a multisite reproducibility study.

PubMed

Lin, P-Y; Chao, T-C; Wu, M-L

2015-03-01

Quantitative susceptibility mapping of the human brain has demonstrated strong potential in examining iron deposition, which may help in investigating possible brain pathology. This study assesses the reproducibility of quantitative susceptibility mapping across different imaging sites. In this study, the susceptibility values of 5 regions of interest in the human brain were measured on 9 healthy subjects following calibration by using phantom experiments. Each of the subjects was imaged 5 times on 1 scanner with the same procedure repeated on 3 different 3T systems so that both within-site and cross-site quantitative susceptibility mapping precision levels could be assessed. Two quantitative susceptibility mapping algorithms, similar in principle, one by using iterative regularization (iterative quantitative susceptibility mapping) and the other with analytic optimal solutions (deterministic quantitative susceptibility mapping), were implemented, and their performances were compared. Results show that while deterministic quantitative susceptibility mapping had nearly 700 times faster computation speed, residual streaking artifacts seem to be more prominent compared with iterative quantitative susceptibility mapping. With quantitative susceptibility mapping, the putamen, globus pallidus, and caudate nucleus showed smaller imprecision on the order of 0.005 ppm, whereas the red nucleus and substantia nigra, closer to the skull base, had a somewhat larger imprecision of approximately 0.01 ppm. Cross-site errors were not significantly larger than within-site errors. Possible sources of estimation errors are discussed. The reproducibility of quantitative susceptibility mapping in the human brain in vivo is regionally dependent, and the precision levels achieved with quantitative susceptibility mapping should allow longitudinal and multisite studies such as aging-related changes in brain tissue magnetic susceptibility. © 2015 by American Journal of Neuroradiology.

Cochrane Qualitative and Implementation Methods Group guidance series-paper 2: methods for question formulation, searching, and protocol development for qualitative evidence synthesis.

PubMed

Harris, Janet L; Booth, Andrew; Cargo, Margaret; Hannes, Karin; Harden, Angela; Flemming, Kate; Garside, Ruth; Pantoja, Tomas; Thomas, James; Noyes, Jane

2018-05-01

This paper updates previous Cochrane guidance on question formulation, searching, and protocol development, reflecting recent developments in methods for conducting qualitative evidence syntheses to inform Cochrane intervention reviews. Examples are used to illustrate how decisions about boundaries for a review are formed via an iterative process of constructing lines of inquiry and mapping the available information to ascertain whether evidence exists to answer questions related to effectiveness, implementation, feasibility, appropriateness, economic evidence, and equity. The process of question formulation allows reviewers to situate the topic in relation to how it informs and explains effectiveness, using the criterion of meaningfulness, appropriateness, feasibility, and implementation. Questions related to complex questions and interventions can be structured by drawing on an increasingly wide range of question frameworks. Logic models and theoretical frameworks are useful tools for conceptually mapping the literature to illustrate the complexity of the phenomenon of interest. Furthermore, protocol development may require iterative question formulation and searching. Consequently, the final protocol may function as a guide rather than a prescriptive route map, particularly in qualitative reviews that ask more exploratory and open-ended questions. Copyright © 2017 Elsevier Inc. All rights reserved.

An accelerated photo-magnetic imaging reconstruction algorithm based on an analytical forward solution and a fast Jacobian assembly method

NASA Astrophysics Data System (ADS)

Nouizi, F.; Erkol, H.; Luk, A.; Marks, M.; Unlu, M. B.; Gulsen, G.

2016-10-01

We previously introduced photo-magnetic imaging (PMI), an imaging technique that illuminates the medium under investigation with near-infrared light and measures the induced temperature increase using magnetic resonance thermometry (MRT). Using a multiphysics solver combining photon migration and heat diffusion, PMI models the spatiotemporal distribution of temperature variation and recovers high resolution optical absorption images using these temperature maps. In this paper, we present a new fast non-iterative reconstruction algorithm for PMI. This new algorithm uses analytic methods during the resolution of the forward problem and the assembly of the sensitivity matrix. We validate our new analytic-based algorithm with the first generation finite element method (FEM) based reconstruction algorithm previously developed by our team. The validation is performed using, first synthetic data and afterwards, real MRT measured temperature maps. Our new method accelerates the reconstruction process 30-fold when compared to a single iteration of the FEM-based algorithm.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor.

PubMed

Kim, Heegwang; Park, Jinho; Park, Hasil; Paik, Joonki

2017-12-09

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system.

Iterative Refinement of Transmission Map for Stereo Image Defogging Using a Dual Camera Sensor

PubMed Central

Park, Jinho; Park, Hasil

2017-01-01

Recently, the stereo imaging-based image enhancement approach has attracted increasing attention in the field of video analysis. This paper presents a dual camera-based stereo image defogging algorithm. Optical flow is first estimated from the stereo foggy image pair, and the initial disparity map is generated from the estimated optical flow. Next, an initial transmission map is generated using the initial disparity map. Atmospheric light is then estimated using the color line theory. The defogged result is finally reconstructed using the estimated transmission map and atmospheric light. The proposed method can refine the transmission map iteratively. Experimental results show that the proposed method can successfully remove fog without color distortion. The proposed method can be used as a pre-processing step for an outdoor video analysis system and a high-end smartphone with a dual camera system. PMID:29232826

Method for removing atomic-model bias in macromolecular crystallography

DOEpatents

Terwilliger, Thomas C [Santa Fe, NM

2006-08-01

Structure factor bias in an electron density map for an unknown crystallographic structure is minimized by using information in a first electron density map to elicit expected structure factor information. Observed structure factor amplitudes are combined with a starting set of crystallographic phases to form a first set of structure factors. A first electron density map is then derived and features of the first electron density map are identified to obtain expected distributions of electron density. Crystallographic phase probability distributions are established for possible crystallographic phases of reflection k, and the process is repeated as k is indexed through all of the plurality of reflections. An updated electron density map is derived from the crystallographic phase probability distributions for each one of the reflections. The entire process is then iterated to obtain a final set of crystallographic phases with minimum bias from known electron density maps.

Structure-aware depth super-resolution using Gaussian mixture model

NASA Astrophysics Data System (ADS)

Kim, Sunok; Oh, Changjae; Kim, Youngjung; Sohn, Kwanghoon

2015-03-01

This paper presents a probabilistic optimization approach to enhance the resolution of a depth map. Conventionally, a high-resolution color image is considered as a cue for depth super-resolution under the assumption that the pixels with similar color likely belong to similar depth. This assumption might induce a texture transferring from the color image into the depth map and an edge blurring artifact to the depth boundaries. In order to alleviate these problems, we propose an efficient depth prior exploiting a Gaussian mixture model in which an estimated depth map is considered to a feature for computing affinity between two pixels. Furthermore, a fixed-point iteration scheme is adopted to address the non-linearity of a constraint derived from the proposed prior. The experimental results show that the proposed method outperforms state-of-the-art methods both quantitatively and qualitatively.

An Iterative Maximum a Posteriori Estimation of Proficiency Level to Detect Multiple Local Likelihood Maxima

ERIC Educational Resources Information Center

Magis, David; Raiche, Gilles

2010-01-01

In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its…

A new approach for predicting drought-related vegetation stress: Integrating satellite, climate, and biophysical data over the U.S. central plains

USGS Publications Warehouse

Tadesse, Tsegaye; Brown, Jesslyn F.; Hayes, M.J.

2005-01-01

Droughts are normal climate episodes, yet they are among the most expensive natural disasters in the world. Knowledge about the timing, severity, and pattern of droughts on the landscape can be incorporated into effective planning and decision-making. In this study, we present a data mining approach to modeling vegetation stress due to drought and mapping its spatial extent during the growing season. Rule-based regression tree models were generated that identify relationships between satellite-derived vegetation conditions, climatic drought indices, and biophysical data, including land-cover type, available soil water capacity, percent of irrigated farm land, and ecological type. The data mining method builds numerical rule-based models that find relationships among the input variables. Because the models can be applied iteratively with input data from previous time periods, the method enables to provide predictions of vegetation conditions farther into the growing season based on earlier conditions. Visualizing the model outputs as mapped information (called VegPredict) provides a means to evaluate the model. We present prototype maps for the 2002 drought year for Nebraska and South Dakota and discuss potential uses for these maps.

Accelerated Brain DCE-MRI Using Iterative Reconstruction With Total Generalized Variation Penalty for Quantitative Pharmacokinetic Analysis: A Feasibility Study.

PubMed

Wang, Chunhao; Yin, Fang-Fang; Kirkpatrick, John P; Chang, Zheng

2017-08-01

To investigate the feasibility of using undersampled k-space data and an iterative image reconstruction method with total generalized variation penalty in the quantitative pharmacokinetic analysis for clinical brain dynamic contrast-enhanced magnetic resonance imaging. Eight brain dynamic contrast-enhanced magnetic resonance imaging scans were retrospectively studied. Two k-space sparse sampling strategies were designed to achieve a simulated image acquisition acceleration factor of 4. They are (1) a golden ratio-optimized 32-ray radial sampling profile and (2) a Cartesian-based random sampling profile with spatiotemporal-regularized sampling density constraints. The undersampled data were reconstructed to yield images using the investigated reconstruction technique. In quantitative pharmacokinetic analysis on a voxel-by-voxel basis, the rate constant K trans in the extended Tofts model and blood flow F B and blood volume V B from the 2-compartment exchange model were analyzed. Finally, the quantitative pharmacokinetic parameters calculated from the undersampled data were compared with the corresponding calculated values from the fully sampled data. To quantify each parameter's accuracy calculated using the undersampled data, error in volume mean, total relative error, and cross-correlation were calculated. The pharmacokinetic parameter maps generated from the undersampled data appeared comparable to the ones generated from the original full sampling data. Within the region of interest, most derived error in volume mean values in the region of interest was about 5% or lower, and the average error in volume mean of all parameter maps generated through either sampling strategy was about 3.54%. The average total relative error value of all parameter maps in region of interest was about 0.115, and the average cross-correlation of all parameter maps in region of interest was about 0.962. All investigated pharmacokinetic parameters had no significant differences between the result from original data and the reduced sampling data. With sparsely sampled k-space data in simulation of accelerated acquisition by a factor of 4, the investigated dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic parameters can accurately estimate the total generalized variation-based iterative image reconstruction method for reliable clinical application.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Cosmic Microwave Background Mapmaking with a Messenger Field

NASA Astrophysics Data System (ADS)

Huffenberger, Kevin M.; Næss, Sigurd K.

2018-01-01

We apply a messenger field method to solve the linear minimum-variance mapmaking equation in the context of Cosmic Microwave Background (CMB) observations. In simulations, the method produces sky maps that converge significantly faster than those from a conjugate gradient descent algorithm with a diagonal preconditioner, even though the computational cost per iteration is similar. The messenger method recovers large scales in the map better than conjugate gradient descent, and yields a lower overall χ2. In the single, pencil beam approximation, each iteration of the messenger mapmaking procedure produces an unbiased map, and the iterations become more optimal as they proceed. A variant of the method can handle differential data or perform deconvolution mapmaking. The messenger method requires no preconditioner, but a high-quality solution needs a cooling parameter to control the convergence. We study the convergence properties of this new method and discuss how the algorithm is feasible for the large data sets of current and future CMB experiments.

Data Assimilation on a Quantum Annealing Computer: Feasibility and Scalability

NASA Astrophysics Data System (ADS)

Nearing, G. S.; Halem, M.; Chapman, D. R.; Pelissier, C. S.

2014-12-01

Data assimilation is one of the ubiquitous and computationally hard problems in the Earth Sciences. In particular, ensemble-based methods require a large number of model evaluations to estimate the prior probability density over system states, and variational methods require adjoint calculations and iteration to locate the maximum a posteriori solution in the presence of nonlinear models and observation operators. Quantum annealing computers (QAC) like the new D-Wave housed at the NASA Ames Research Center can be used for optimization and sampling, and therefore offers a new possibility for efficiently solving hard data assimilation problems. Coding on the QAC is not straightforward: a problem must be posed as a Quadratic Unconstrained Binary Optimization (QUBO) and mapped to a spherical Chimera graph. We have developed a method for compiling nonlinear 4D-Var problems on the D-Wave that consists of five steps: Emulating the nonlinear model and/or observation function using radial basis functions (RBF) or Chebyshev polynomials. Truncating a Taylor series around each RBF kernel. Reducing the Taylor polynomial to a quadratic using ancilla gadgets. Mapping the real-valued quadratic to a fixed-precision binary quadratic. Mapping the fully coupled binary quadratic to a partially coupled spherical Chimera graph using ancilla gadgets. At present the D-Wave contains 512 qbits (with 1024 and 2048 qbit machines due in the next two years); this machine size allows us to estimate only 3 state variables at each satellite overpass. However, QAC's solve optimization problems using a physical (quantum) system, and therefore do not require iterations or calculation of model adjoints. This has the potential to revolutionize our ability to efficiently perform variational data assimilation, as the size of these computers grows in the coming years.

Cube Kohonen self-organizing map (CKSOM) model with new equations in organizing unstructured data.

PubMed

Lim, Seng Poh; Haron, Habibollah

2013-09-01

Surface reconstruction by using 3-D data is used to represent the surface of an object and perform important tasks. The type of data used is important and can be described as either structured or unstructured. For unstructured data, there is no connectivity information between data points. As a result, incorrect shapes will be obtained during the imaging process. Therefore, the data should be reorganized by finding the correct topology so that the correct shape can be obtained. Previous studies have shown that the Kohonen self-organizing map (KSOM) could be used to solve data organizing problems. However, 2-D Kohonen maps are limited because they are unable to cover the whole surface of closed 3-D surface data. Furthermore, the neurons inside the 3-D KSOM structure should be removed in order to create a correct wireframe model. This is because only the outside neurons are used to represent the surface of an object. The aim of this paper is to use KSOM to organize unstructured data for closed surfaces. KSOM isused in this paper by testing its ability to organize medical image data because KSOM is mostly used in constructing engineering field data. Enhancements are added to the model by introducing class number and the index vector, and new equations are created. Various grid sizes and maximum iterations are tested in the experiments. Based on the results, the number of redundancies is found to be directly proportional to the grid size. When we increase the maximum iterations, the surface of the image becomes smoother. An area formula is used and manual calculations are performed to validate the results. This model is implemented and images are created using Dev C++ and GNUPlot.

Mapreduce is Good Enough? If All You Have is a Hammer, Throw Away Everything That's Not a Nail!

PubMed

Lin, Jimmy

2013-03-01

Hadoop is currently the large-scale data analysis "hammer" of choice, but there exist classes of algorithms that aren't "nails" in the sense that they are not particularly amenable to the MapReduce programming model. To address this, researchers have proposed MapReduce extensions or alternative programming models in which these algorithms can be elegantly expressed. This article espouses a very different position: that MapReduce is "good enough," and that instead of trying to invent screwdrivers, we should simply get rid of everything that's not a nail. To be more specific, much discussion in the literature surrounds the fact that iterative algorithms are a poor fit for MapReduce. The simple solution is to find alternative, noniterative algorithms that solve the same problem. This article captures my personal experiences as an academic researcher as well as a software engineer in a "real-world" production analytics environment. From this combined perspective, I reflect on the current state and future of "big data" research.

An interpretation model of GPR point data in tunnel geological prediction

NASA Astrophysics Data System (ADS)

He, Yu-yao; Li, Bao-qi; Guo, Yuan-shu; Wang, Teng-na; Zhu, Ya

2017-02-01

GPR (Ground Penetrating Radar) point data plays an absolutely necessary role in the tunnel geological prediction. However, the research work on the GPR point data is very little and the results does not meet the actual requirements of the project. In this paper, a GPR point data interpretation model which is based on WD (Wigner distribution) and deep CNN (convolutional neural network) is proposed. Firstly, the GPR point data is transformed by WD to get the map of time-frequency joint distribution; Secondly, the joint distribution maps are classified by deep CNN. The approximate location of geological target is determined by observing the time frequency map in parallel; Finally, the GPR point data is interpreted according to the classification results and position information from the map. The simulation results show that classification accuracy of the test dataset (include 1200 GPR point data) is 91.83% at the 200 iteration. Our model has the advantages of high accuracy and fast training speed, and can provide a scientific basis for the development of tunnel construction and excavation plan.

Optimal health and disease management using spatial uncertainty: a geographic characterization of emergent artemisinin-resistant Plasmodium falciparum distributions in Southeast Asia.

PubMed

Grist, Eric P M; Flegg, Jennifer A; Humphreys, Georgina; Mas, Ignacio Suay; Anderson, Tim J C; Ashley, Elizabeth A; Day, Nicholas P J; Dhorda, Mehul; Dondorp, Arjen M; Faiz, M Abul; Gething, Peter W; Hien, Tran T; Hlaing, Tin M; Imwong, Mallika; Kindermans, Jean-Marie; Maude, Richard J; Mayxay, Mayfong; McDew-White, Marina; Menard, Didier; Nair, Shalini; Nosten, Francois; Newton, Paul N; Price, Ric N; Pukrittayakamee, Sasithon; Takala-Harrison, Shannon; Smithuis, Frank; Nguyen, Nhien T; Tun, Kyaw M; White, Nicholas J; Witkowski, Benoit; Woodrow, Charles J; Fairhurst, Rick M; Sibley, Carol Hopkins; Guerin, Philippe J

2016-10-24

Artemisinin-resistant Plasmodium falciparum malaria parasites are now present across much of mainland Southeast Asia, where ongoing surveys are measuring and mapping their spatial distribution. These efforts require substantial resources. Here we propose a generic 'smart surveillance' methodology to identify optimal candidate sites for future sampling and thus map the distribution of artemisinin resistance most efficiently. The approach uses the 'uncertainty' map generated iteratively by a geostatistical model to determine optimal locations for subsequent sampling. The methodology is illustrated using recent data on the prevalence of the K13-propeller polymorphism (a genetic marker of artemisinin resistance) in the Greater Mekong Subregion. This methodology, which has broader application to geostatistical mapping in general, could improve the quality and efficiency of drug resistance mapping and thereby guide practical operations to eliminate malaria in affected areas.

Variable Sampling Mapping

NASA Technical Reports Server (NTRS)

Smith, Jeffrey, S.; Aronstein, David L.; Dean, Bruce H.; Lyon, Richard G.

2012-01-01

The performance of an optical system (for example, a telescope) is limited by the misalignments and manufacturing imperfections of the optical elements in the system. The impact of these misalignments and imperfections can be quantified by the phase variations imparted on light traveling through the system. Phase retrieval is a methodology for determining these variations. Phase retrieval uses images taken with the optical system and using a light source of known shape and characteristics. Unlike interferometric methods, which require an optical reference for comparison, and unlike Shack-Hartmann wavefront sensors that require special optical hardware at the optical system's exit pupil, phase retrieval is an in situ, image-based method for determining the phase variations of light at the system s exit pupil. Phase retrieval can be used both as an optical metrology tool (during fabrication of optical surfaces and assembly of optical systems) and as a sensor used in active, closed-loop control of an optical system, to optimize performance. One class of phase-retrieval algorithms is the iterative transform algorithm (ITA). ITAs estimate the phase variations by iteratively enforcing known constraints in the exit pupil and at the detector, determined from modeled or measured data. The Variable Sampling Mapping (VSM) technique is a new method for enforcing these constraints in ITAs. VSM is an open framework for addressing a wide range of issues that have previously been considered detrimental to high-accuracy phase retrieval, including undersampled images, broadband illumination, images taken at or near best focus, chromatic aberrations, jitter or vibration of the optical system or detector, and dead or noisy detector pixels. The VSM is a model-to-data mapping procedure. In VSM, fully sampled electric fields at multiple wavelengths are modeled inside the phase-retrieval algorithm, and then these fields are mapped to intensities on the light detector, using the properties of the detector and optical system, for comparison with measured data. Ultimately, this model-to-data mapping procedure enables a more robust and accurate way of incorporating the exit-pupil and image detector constraints, which are fundamental to the general class of ITA phase retrieval algorithms.

Reliability of functional MR imaging with word-generation tasks for mapping Broca's area.

PubMed

Brannen, J H; Badie, B; Moritz, C H; Quigley, M; Meyerand, M E; Haughton, V M

2001-10-01

Functional MR (fMR) imaging of word generation has been used to map Broca's area in some patients selected for craniotomy. The purpose of this study was to measure the reliability, precision, and accuracy of word-generation tasks to identify Broca's area. The Brodmann areas activated during performance of word-generation tasks were tabulated in 34 consecutive patients referred for fMR imaging mapping of language areas. In patients performing two iterations of the letter word-generation tasks, test-retest reliability was quantified by using the concurrence ratio (CR), or the number of voxels activated by each iteration in proportion to the average number of voxels activated from both iterations of the task. Among patients who also underwent category or antonym word generation or both, the similarity of the activation from each task was assessed with the CR. In patients who underwent electrocortical stimulation (ECS) mapping of speech function during craniotomy while awake, the sites with speech function were compared with the locations of activation found during fMR imaging of word generation. In 31 of 34 patients, activation was identified in the inferior frontal gyri or middle frontal gyri or both in Brodmann areas 9, 44, 45, or 46, unilaterally or bilaterally, with one or more of the tasks. Activation was noted in the same gyri when the patient performed a second iteration of the letter word-generation task or second task. The CR for pixel precision in a single section averaged 49%. In patients who underwent craniotomy while awake, speech areas located with ECS coincided with areas of the brain activated during a word-generation task. fMR imaging with word-generation tasks produces technically satisfactory maps of Broca's area, which localize the area accurately and reliably.

AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting.

PubMed

Cline, Christopher C; Chen, Xiao; Mailhe, Boris; Wang, Qiu; Pfeuffer, Josef; Nittka, Mathias; Griswold, Mark A; Speier, Peter; Nadar, Mariappan S

2017-09-01

Existing approaches for reconstruction of multiparametric maps with magnetic resonance fingerprinting (MRF) are currently limited by their estimation accuracy and reconstruction time. We aimed to address these issues with a novel combination of iterative reconstruction, fingerprint compression, additional regularization, and accelerated dictionary search methods. The pipeline described here, accelerated iterative reconstruction for magnetic resonance fingerprinting (AIR-MRF), was evaluated with simulations as well as phantom and in vivo scans. We found that the AIR-MRF pipeline provided reduced parameter estimation errors compared to non-iterative and other iterative methods, particularly at shorter sequence lengths. Accelerated dictionary search methods incorporated into the iterative pipeline reduced the reconstruction time at little cost of quality. Copyright © 2017 Elsevier Inc. All rights reserved.

Chimera states in networks of logistic maps with hierarchical connectivities

NASA Astrophysics Data System (ADS)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

A case study in bifurcation theory

NASA Astrophysics Data System (ADS)

Khmou, Youssef

This short paper is focused on the bifurcation theory found in map functions called evolution functions that are used in dynamical systems. The most well-known example of discrete iterative function is the logistic map that puts into evidence bifurcation and chaotic behavior of the topology of the logistic function. We propose a new iterative function based on Lorentizan function and its generalized versions, based on numerical study, it is found that the bifurcation of the Lorentzian function is of second-order where it is characterized by the absence of chaotic region.

Characteristics of aperiodic sequence of slip events caused by interaction between seismic patches and that caused be self-organized stress heterogeneity

NASA Astrophysics Data System (ADS)

Kato, N.

2017-12-01

Numerical simulations of earthquake cycles are conducted to investigate the origin of complexity of earthquake recurrence. There are two main causes of the complexity. One is self-organized stress heterogeneity due to dynamical effect. The other is the effect of interaction between some fault patches. In the model, friction on the fault is assumed to obey a rate- and state-dependent friction law. Circular patches of velocity-weakening frictional property are assumed on the fault. On the remaining areas of the fault, velocity-strengthening friction is assumed. We consider three models: Single patch model, two-patch model, and three-patch model. In the first model, the dynamical effect is mainly examined. The latter two models take into consideration the effect of interaction as well as the dynamical effect. Complex multiperiodic or aperiodic sequences of slip events occur when slip behavior changes from the seismic to aseismic, and when the degree of interaction between seismic patches is intermediate. The former is observed in all the models, and the latter is observed in the two-patch model and the three-patch model. Evolution of spatial distribution of shear stress on the fault suggests that aperiodicity at the transition from seismic to aseismic slip is caused by self-organized stress heterogeneity. The iteration maps of recurrence intervals of slip events in aperiodic sequences are examined, and they are approximately expressed by simple curves for aperiodicity at the transition from seismic to aseismic slip. In contrast, the iteration maps for aperiodic sequences caused by interaction between seismic patches are scattered and they are not expressed by simple curves. This result suggests that complex sequences caused by different mechanisms may be distinguished.

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

USGS Publications Warehouse

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Kumar, Sunil; Swallow, Aaron; Luizza, Matthew; Chignell, Steve

2017-01-01

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

NASA Astrophysics Data System (ADS)

West, Amanda M.; Evangelista, Paul H.; Jarnevich, Catherine S.; Kumar, Sunil; Swallow, Aaron; Luizza, Matthew W.; Chignell, Stephen M.

2017-07-01

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

Music Regions and Mental Maps: Teaching Cultural Geography

ERIC Educational Resources Information Center

Shobe, Hunter; Banis, David

2010-01-01

Music informs understandings of place and is an excellent vehicle for teaching cultural geography. A study was developed of geography students' perception of where music genres predominate in the United States. Its approach, involving mental map exercises, reveals the usefulness and importance of maps as an iterative process in teaching cultural…

Multiscale Reconstruction for Magnetic Resonance Fingerprinting

PubMed Central

Pierre, Eric Y.; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A.

2015-01-01

Purpose To reduce acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. Methods An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in-vivo data using the highly-undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. Results The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD) and B0 field variations in the brain was achieved in vivo for a 256×256 matrix for a total acquisition time of 10.2s, representing a 3-fold reduction in acquisition time. Conclusions The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. PMID:26132462

Climate model simulations of the mid-Pliocene: Earth's last great interval of global warmth

USGS Publications Warehouse

Dolan, A.M.; Haywood, A.M.; Dowsett, H.J.

2012-01-01

Pliocene Model Intercomparison Project Workshop; Reston, Virginia, 2–4 August 2011 The Pliocene Model Intercomparison Project (PlioMIP), supported by the U.S. Geological Survey's (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) project and Powell Center, is an integral part of a third iteration of the Paleoclimate Modelling Intercomparison Project (PMIP3). PlioMIP's aim is to systematically compare structurally different climate models. This is done in the context of the mid-Pliocene (~3.3–3.0 million years ago), a geological interval when the global annual mean temperature was similar to predictions for the next century.

Perl Modules for Constructing Iterators

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2009-01-01

The Iterator Perl Module provides a general-purpose framework for constructing iterator objects within Perl, and a standard API for interacting with those objects. Iterators are an object-oriented design pattern where a description of a series of values is used in a constructor. Subsequent queries can request values in that series. These Perl modules build on the standard Iterator framework and provide iterators for some other types of values. Iterator::DateTime constructs iterators from DateTime objects or Date::Parse descriptions and ICal/RFC 2445 style re-currence descriptions. It supports a variety of input parameters, including a start to the sequence, an end to the sequence, an Ical/RFC 2445 recurrence describing the frequency of the values in the series, and a format description that can refine the presentation manner of the DateTime. Iterator::String constructs iterators from string representations. This module is useful in contexts where the API consists of supplying a string and getting back an iterator where the specific iteration desired is opaque to the caller. It is of particular value to the Iterator::Hash module which provides nested iterations. Iterator::Hash constructs iterators from Perl hashes that can include multiple iterators. The constructed iterators will return all the permutations of the iterations of the hash by nested iteration of embedded iterators. A hash simply includes a set of keys mapped to values. It is a very common data structure used throughout Perl programming. The Iterator:: Hash module allows a hash to include strings defining iterators (parsed and dispatched with Iterator::String) that are used to construct an overall series of hash values.

Enhancing sparsity of Hermite polynomial expansions by iterative rotations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xiu; Lei, Huan; Baker, Nathan A.

2016-02-01

Compressive sensing has become a powerful addition to uncertainty quantification in recent years. This paper identifies new bases for random variables through linear mappings such that the representation of the quantity of interest is more sparse with new basis functions associated with the new random variables. This sparsity increases both the efficiency and accuracy of the compressive sensing-based uncertainty quantification method. Specifically, we consider rotation- based linear mappings which are determined iteratively for Hermite polynomial expansions. We demonstrate the effectiveness of the new method with applications in solving stochastic partial differential equations and high-dimensional (O(100)) problems.

Conjecture Mapping to Optimize the Educational Design Research Process

ERIC Educational Resources Information Center

Wozniak, Helen

2015-01-01

While educational design research promotes closer links between practice and theory, reporting its outcomes from iterations across multiple contexts is often constrained by the volumes of data generated, and the context bound nature of the research outcomes. Reports tend to focus on a single iteration of implementation without further research to…

Intelligent model-based OPC

NASA Astrophysics Data System (ADS)

Huang, W. C.; Lai, C. M.; Luo, B.; Tsai, C. K.; Chih, M. H.; Lai, C. W.; Kuo, C. C.; Liu, R. G.; Lin, H. T.

2006-03-01

Optical proximity correction is the technique of pre-distorting mask layouts so that the printed patterns are as close to the desired shapes as possible. For model-based optical proximity correction, a lithographic model to predict the edge position (contour) of patterns on the wafer after lithographic processing is needed. Generally, segmentation of edges is performed prior to the correction. Pattern edges are dissected into several small segments with corresponding target points. During the correction, the edges are moved back and forth from the initial drawn position, assisted by the lithographic model, to finally settle on the proper positions. When the correction converges, the intensity predicted by the model in every target points hits the model-specific threshold value. Several iterations are required to achieve the convergence and the computation time increases with the increase of the required iterations. An artificial neural network is an information-processing paradigm inspired by biological nervous systems, such as how the brain processes information. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. A neural network can be a powerful data-modeling tool that is able to capture and represent complex input/output relationships. The network can accurately predict the behavior of a system via the learning procedure. A radial basis function network, a variant of artificial neural network, is an efficient function approximator. In this paper, a radial basis function network was used to build a mapping from the segment characteristics to the edge shift from the drawn position. This network can provide a good initial guess for each segment that OPC has carried out. The good initial guess reduces the required iterations. Consequently, cycle time can be shortened effectively. The optimization of the radial basis function network for this system was practiced by genetic algorithm, which is an artificially intelligent optimization method with a high probability to obtain global optimization. From preliminary results, the required iterations were reduced from 5 to 2 for a simple dumbbell-shape layout.

A Control Algorithm for Chaotic Physical Systems

DTIC Science & Technology

1991-10-01

revision expands the grid to cover the entire area of any attractor that is present. 5 Map Selection The final choices of the state- space mapping process...interval h?; overrange R0 ; control parameter interval AkO and range [kbro, khigh]; iteration depth. "* State- space mapping : 1. Set up grid by expanding

The Strategic Design Inquiry: A Formal Methodology For Approaching, Designing, Integrating, And Articulating National Strategy

DTIC Science & Technology

2014-04-01

15 Figure 4: Example cognitive map ... map , aligning planning efforts throughout the government. Even after strategy implementation, SDI calls for continuing, iterative learning and...the design before total commitment to it. Capturing this analysis on a cognitive map allows strategists to articulate a design to government

System Integration Issues in Digital Photogrammetric Mapping

DTIC Science & Technology

1992-01-01

elevation models, and/or rectified imagery/ orthophotos . Imagery exported from the DSPW can be either in a tiled image format or standard raster format...data. In the near future, correlation using "window shaping" operations along with an iterative orthophoto refinements methodology (Norvelle, 1992) is...components of TIES. The IDS passes tiled image data and ASCII header data to the DSPW. The tiled image file contains only image data. The ASCII header

Topographic mapping on large-scale tidal flats with an iterative approach on the waterline method

NASA Astrophysics Data System (ADS)

Kang, Yanyan; Ding, Xianrong; Xu, Fan; Zhang, Changkuan; Ge, Xiaoping

2017-05-01

Tidal flats, which are both a natural ecosystem and a type of landscape, are of significant importance to ecosystem function and land resource potential. Morphologic monitoring of tidal flats has become increasingly important with respect to achieving sustainable development targets. Remote sensing is an established technique for the measurement of topography over tidal flats; of the available methods, the waterline method is particularly effective for constructing a digital elevation model (DEM) of intertidal areas. However, application of the waterline method is more limited in large-scale, shifting tidal flats areas, where the tides are not synchronized and the waterline is not a quasi-contour line. For this study, a topographical map of the intertidal regions within the Radial Sand Ridges (RSR) along the Jiangsu Coast, China, was generated using an iterative approach on the waterline method. A series of 21 multi-temporal satellite images (18 HJ-1A/B CCD and three Landsat TM/OLI) of the RSR area collected at different water levels within a five month period (31 December 2013-28 May 2014) was used to extract waterlines based on feature extraction techniques and artificial further modification. These 'remotely-sensed waterlines' were combined with the corresponding water levels from the 'model waterlines' simulated by a hydrodynamic model with an initial generalized DEM of exposed tidal flats. Based on the 21 heighted 'remotely-sensed waterlines', a DEM was constructed using the ANUDEM interpolation method. Using this new DEM as the input data, it was re-entered into the hydrodynamic model, and a new round of water level assignment of waterlines was performed. A third and final output DEM was generated covering an area of approximately 1900 km2 of tidal flats in the RSR. The water level simulation accuracy of the hydrodynamic model was within 0.15 m based on five real-time tide stations, and the height accuracy (root mean square error) of the final DEM was 0.182 m based on six transects of measured data. This study aimed at construction of an accurate DEM for a large-scale, high-variable zone within a short timespan based on an iterative way of the waterline method.

Stochastic DT-MRI connectivity mapping on the GPU.

PubMed

McGraw, Tim; Nadar, Mariappan

2007-01-01

We present a method for stochastic fiber tract mapping from diffusion tensor MRI (DT-MRI) implemented on graphics hardware. From the simulated fibers we compute a connectivity map that gives an indication of the probability that two points in the dataset are connected by a neuronal fiber path. A Bayesian formulation of the fiber model is given and it is shown that the inversion method can be used to construct plausible connectivity. An implementation of this fiber model on the graphics processing unit (GPU) is presented. Since the fiber paths can be stochastically generated independently of one another, the algorithm is highly parallelizable. This allows us to exploit the data-parallel nature of the GPU fragment processors. We also present a framework for the connectivity computation on the GPU. Our implementation allows the user to interactively select regions of interest and observe the evolving connectivity results during computation. Results are presented from the stochastic generation of over 250,000 fiber steps per iteration at interactive frame rates on consumer-grade graphics hardware.

Multiscale reconstruction for MR fingerprinting.

PubMed

Pierre, Eric Y; Ma, Dan; Chen, Yong; Badve, Chaitra; Griswold, Mark A

2016-06-01

To reduce the acquisition time needed to obtain reliable parametric maps with Magnetic Resonance Fingerprinting. An iterative-denoising algorithm is initialized by reconstructing the MRF image series at low image resolution. For subsequent iterations, the method enforces pixel-wise fidelity to the best-matching dictionary template then enforces fidelity to the acquired data at slightly higher spatial resolution. After convergence, parametric maps with desirable spatial resolution are obtained through template matching of the final image series. The proposed method was evaluated on phantom and in vivo data using the highly undersampled, variable-density spiral trajectory and compared with the original MRF method. The benefits of additional sparsity constraints were also evaluated. When available, gold standard parameter maps were used to quantify the performance of each method. The proposed approach allowed convergence to accurate parametric maps with as few as 300 time points of acquisition, as compared to 1000 in the original MRF work. Simultaneous quantification of T1, T2, proton density (PD), and B0 field variations in the brain was achieved in vivo for a 256 × 256 matrix for a total acquisition time of 10.2 s, representing a three-fold reduction in acquisition time. The proposed iterative multiscale reconstruction reliably increases MRF acquisition speed and accuracy. Magn Reson Med 75:2481-2492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Assessment of Preconditioner for a USM3D Hierarchical Adaptive Nonlinear Method (HANIM) (Invited)

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Diskin, Boris; Thomas, James L.; Frink, Neal T.

2016-01-01

Enhancements to the previously reported mixed-element USM3D Hierarchical Adaptive Nonlinear Iteration Method (HANIM) framework have been made to further improve robustness, efficiency, and accuracy of computational fluid dynamic simulations. The key enhancements include a multi-color line-implicit preconditioner, a discretely consistent symmetry boundary condition, and a line-mapping method for the turbulence source term discretization. The USM3D iterative convergence for the turbulent flows is assessed on four configurations. The configurations include a two-dimensional (2D) bump-in-channel, the 2D NACA 0012 airfoil, a three-dimensional (3D) bump-in-channel, and a 3D hemisphere cylinder. The Reynolds Averaged Navier Stokes (RANS) solutions have been obtained using a Spalart-Allmaras turbulence model and families of uniformly refined nested grids. Two types of HANIM solutions using line- and point-implicit preconditioners have been computed. Additional solutions using the point-implicit preconditioner alone (PA) method that broadly represents the baseline solver technology have also been computed. The line-implicit HANIM shows superior iterative convergence in most cases with progressively increasing benefits on finer grids.

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Direct Reconstruction of CT-Based Attenuation Correction Images for PET With Cluster-Based Penalties

NASA Astrophysics Data System (ADS)

Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Kinahan, Paul E.

2017-03-01

Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.

Mechanical perturbation control of cardiac alternans

NASA Astrophysics Data System (ADS)

Hazim, Azzam; Belhamadia, Youssef; Dubljevic, Stevan

2018-05-01

Cardiac alternans is a disturbance in heart rhythm that is linked to the onset of lethal cardiac arrhythmias. Mechanical perturbation control has been recently used to suppress alternans in cardiac tissue of relevant size. In this control strategy, cardiac tissue mechanics are perturbed via active tension generated by the heart's electrical activity, which alters the tissue's electric wave profile through mechanoelectric coupling. We analyze the effects of mechanical perturbation on the dynamics of a map model that couples the membrane voltage and active tension systems at the cellular level. Therefore, a two-dimensional iterative map of the heart beat-to-beat dynamics is introduced, and a stability analysis of the system of coupled maps is performed in the presence of a mechanical perturbation algorithm. To this end, a bidirectional coupling between the membrane voltage and active tension systems in a single cardiac cell is provided, and a discrete form of the proposed control algorithm, that can be incorporated in the coupled maps, is derived. In addition, a realistic electromechanical model of cardiac tissue is employed to explore the feasibility of suppressing alternans at cellular and tissue levels. Electrical activity is represented in two detailed ionic models, the Luo-Rudy 1 and the Fox models, while two active contractile tension models, namely a smooth variant of the Nash-Panfilov model and the Niederer-Hunter-Smith model, are used to represent mechanical activity in the heart. The Mooney-Rivlin passive elasticity model is employed to describe passive mechanical behavior of the myocardium.

Generalized Smooth Transition Map Between Tent and Logistic Maps

NASA Astrophysics Data System (ADS)

Sayed, Wafaa S.; Fahmy, Hossam A. H.; Rezk, Ahmed A.; Radwan, Ahmed G.

There is a continuous demand on novel chaotic generators to be employed in various modeling and pseudo-random number generation applications. This paper proposes a new chaotic map which is a general form for one-dimensional discrete-time maps employing the power function with the tent and logistic maps as special cases. The proposed map uses extra parameters to provide responses that fit multiple applications for which conventional maps were not enough. The proposed generalization covers also maps whose iterative relations are not based on polynomials, i.e. with fractional powers. We introduce a framework for analyzing the proposed map mathematically and predicting its behavior for various combinations of its parameters. In addition, we present and explain the transition map which results in intermediate responses as the parameters vary from their values corresponding to tent map to those corresponding to logistic map case. We study the properties of the proposed map including graph of the map equation, general bifurcation diagram and its key-points, output sequences, and maximum Lyapunov exponent. We present further explorations such as effects of scaling, system response with respect to the new parameters, and operating ranges other than transition region. Finally, a stream cipher system based on the generalized transition map validates its utility for image encryption applications. The system allows the construction of more efficient encryption keys which enhances its sensitivity and other cryptographic properties.

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Ultra-low-dose computed tomographic angiography with model-based iterative reconstruction compared with standard-dose imaging after endovascular aneurysm repair: a prospective pilot study.

PubMed

Naidu, Sailen G; Kriegshauser, J Scott; Paden, Robert G; He, Miao; Wu, Qing; Hara, Amy K

2014-12-01

An ultra-low-dose radiation protocol reconstructed with model-based iterative reconstruction was compared with our standard-dose protocol. This prospective study evaluated 20 men undergoing surveillance-enhanced computed tomography after endovascular aneurysm repair. All patients underwent standard-dose and ultra-low-dose venous phase imaging; images were compared after reconstruction with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction. Objective measures of aortic contrast attenuation and image noise were averaged. Images were subjectively assessed (1 = worst, 5 = best) for diagnostic confidence, image noise, and vessel sharpness. Aneurysm sac diameter and endoleak detection were compared. Quantitative image noise was 26% less with ultra-low-dose model-based iterative reconstruction than with standard-dose adaptive statistical iterative reconstruction and 58% less than with ultra-low-dose adaptive statistical iterative reconstruction. Average subjective noise scores were not different between ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction (3.8 vs. 4.0, P = .25). Subjective scores for diagnostic confidence were better with standard-dose adaptive statistical iterative reconstruction than with ultra-low-dose model-based iterative reconstruction (4.4 vs. 4.0, P = .002). Vessel sharpness was decreased with ultra-low-dose model-based iterative reconstruction compared with standard-dose adaptive statistical iterative reconstruction (3.3 vs. 4.1, P < .0001). Ultra-low-dose model-based iterative reconstruction and standard-dose adaptive statistical iterative reconstruction aneurysm sac diameters were not significantly different (4.9 vs. 4.9 cm); concordance for the presence of endoleak was 100% (P < .001). Compared with a standard-dose technique, an ultra-low-dose model-based iterative reconstruction protocol provides comparable image quality and diagnostic assessment at a 73% lower radiation dose.

Rate-Dependent Homogenization Based Continuum Plasticity Damage Model for Dendritic Cast Aluminum Alloys

DTIC Science & Technology

2011-01-01

0.25 s−1 to 0.75 s−1 The return mapping algorithm consists of an initial elastic predictor step, where the elastic response is assumed and the stresses...18 different loadings are used. The parameters F, G, H are solved by an iterative algorithm with C = 3. The step is repeated for different values of...a. REPORT unclassified b. ABSTRACT unclassified c . THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 c⃝

Mapping 2000 2010 Impervious Surface Change in India Using Global Land Survey Landsat Data

NASA Technical Reports Server (NTRS)

Wang, Panshi; Huang, Chengquan; Brown De Colstoun, Eric C.

2017-01-01

Understanding and monitoring the environmental impacts of global urbanization requires better urban datasets. Continuous field impervious surface change (ISC) mapping using Landsat data is an effective way to quantify spatiotemporal dynamics of urbanization. It is well acknowledged that Landsat-based estimation of impervious surface is subject to seasonal and phenological variations. The overall goal of this paper is to map 200-02010 ISC for India using Global Land Survey datasets and training data only available for 2010. To this end, a method was developed that could transfer the regression tree model developed for mapping 2010 impervious surface to 2000 using an iterative training and prediction (ITP) approach An independent validation dataset was also developed using Google Earth imagery. Based on the reference ISC from the validation dataset, the RMSE of predicted ISC was estimated to be 18.4%. At 95% confidence, the total estimated ISC for India between 2000 and 2010 is 2274.62 +/- 7.84 sq km.

Effective electron-density map improvement and structure validation on a Linux multi-CPU web cluster: The TB Structural Genomics Consortium Bias Removal Web Service.

PubMed

Reddy, Vinod; Swanson, Stanley M; Segelke, Brent; Kantardjieff, Katherine A; Sacchettini, James C; Rupp, Bernhard

2003-12-01

Anticipating a continuing increase in the number of structures solved by molecular replacement in high-throughput crystallography and drug-discovery programs, a user-friendly web service for automated molecular replacement, map improvement, bias removal and real-space correlation structure validation has been implemented. The service is based on an efficient bias-removal protocol, Shake&wARP, and implemented using EPMR and the CCP4 suite of programs, combined with various shell scripts and Fortran90 routines. The service returns improved maps, converted data files and real-space correlation and B-factor plots. User data are uploaded through a web interface and the CPU-intensive iteration cycles are executed on a low-cost Linux multi-CPU cluster using the Condor job-queuing package. Examples of map improvement at various resolutions are provided and include model completion and reconstruction of absent parts, sequence correction, and ligand validation in drug-target structures.

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard.

PubMed

Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

2015-08-01

management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process.

Local Improvement Results for Anderson Acceleration with Inaccurate Function Evaluations

DOE PAGES

Toth, Alex; Ellis, J. Austin; Evans, Tom; ...

2017-10-26

Here, we analyze the convergence of Anderson acceleration when the fixed point map is corrupted with errors. We also consider uniformly bounded errors and stochastic errors with infinite tails. We prove local improvement results which describe the performance of the iteration up to the point where the accuracy of the function evaluation causes the iteration to stagnate. We illustrate the results with examples from neutronics.

Local Improvement Results for Anderson Acceleration with Inaccurate Function Evaluations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toth, Alex; Ellis, J. Austin; Evans, Tom

Here, we analyze the convergence of Anderson acceleration when the fixed point map is corrupted with errors. We also consider uniformly bounded errors and stochastic errors with infinite tails. We prove local improvement results which describe the performance of the iteration up to the point where the accuracy of the function evaluation causes the iteration to stagnate. We illustrate the results with examples from neutronics.

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

Final Report on ITER Task Agreement 81-08

DOE Office of Scientific and Technical Information (OSTI.GOV)

Richard L. Moore

As part of an ITER Implementing Task Agreement (ITA) between the ITER US Participant Team (PT) and the ITER International Team (IT), the INL Fusion Safety Program was tasked to provide the ITER IT with upgrades to the fusion version of the MELCOR 1.8.5 code including a beryllium dust oxidation model. The purpose of this model is to allow the ITER IT to investigate hydrogen production from beryllium dust layers on hot surfaces inside the ITER vacuum vessel (VV) during in-vessel loss-of-cooling accidents (LOCAs). Also included in the ITER ITA was a task to construct a RELAP5/ATHENA model of themore » ITER divertor cooling loop to model the draining of the loop during a large ex-vessel pipe break followed by an in-vessel divertor break and compare the results to a simular MELCOR model developed by the ITER IT. This report, which is the final report for this agreement, documents the completion of the work scope under this ITER TA, designated as TA 81-08.« less

Localization and Mapping Using a Non-Central Catadioptric Camera System

NASA Astrophysics Data System (ADS)

Khurana, M.; Armenakis, C.

2018-05-01

This work details the development of an indoor navigation and mapping system using a non-central catadioptric omnidirectional camera and its implementation for mobile applications. Omnidirectional catadioptric cameras find their use in navigation and mapping of robotic platforms, owing to their wide field of view. Having a wider field of view, or rather a potential 360° field of view, allows the system to "see and move" more freely in the navigation space. A catadioptric camera system is a low cost system which consists of a mirror and a camera. Any perspective camera can be used. A platform was constructed in order to combine the mirror and a camera to build a catadioptric system. A calibration method was developed in order to obtain the relative position and orientation between the two components so that they can be considered as one monolithic system. The mathematical model for localizing the system was determined using conditions based on the reflective properties of the mirror. The obtained platform positions were then used to map the environment using epipolar geometry. Experiments were performed to test the mathematical models and the achieved location and mapping accuracies of the system. An iterative process of positioning and mapping was applied to determine object coordinates of an indoor environment while navigating the mobile platform. Camera localization and 3D coordinates of object points obtained decimetre level accuracies.

PROGRESS TOWARDS NEXT GENERATION, WAVEFORM BASED THREE-DIMENSIONAL MODELS AND METRICS TO IMPROVE NUCLEAR EXPLOSION MONITORING IN THE MIDDLE EAST

DOE Office of Scientific and Technical Information (OSTI.GOV)

Savage, B; Peter, D; Covellone, B

2009-07-02

Efforts to update current wave speed models of the Middle East require a thoroughly tested database of sources and recordings. Recordings of seismic waves traversing the region from Tibet to the Red Sea will be the principal metric in guiding improvements to the current wave speed model. Precise characterizations of the earthquakes, specifically depths and faulting mechanisms, are essential to avoid mapping source errors into the refined wave speed model. Errors associated with the source are manifested in amplitude and phase changes. Source depths and paths near nodal planes are particularly error prone as small changes may severely affect themore » resulting wavefield. Once sources are quantified, regions requiring refinement will be highlighted using adjoint tomography methods based on spectral element simulations [Komatitsch and Tromp (1999)]. An initial database of 250 regional Middle Eastern events from 1990-2007, was inverted for depth and focal mechanism using teleseismic arrivals [Kikuchi and Kanamori (1982)] and regional surface and body waves [Zhao and Helmberger (1994)]. From this initial database, we reinterpreted a large, well recorded subset of 201 events through a direct comparison between data and synthetics based upon a centroid moment tensor inversion [Liu et al. (2004)]. Evaluation was done using both a 1D reference model [Dziewonski and Anderson (1981)] at periods greater than 80 seconds and a 3D model [Kustowski et al. (2008)] at periods of 25 seconds and longer. The final source reinterpretations will be within the 3D model, as this is the initial starting point for the adjoint tomography. Transitioning from a 1D to 3D wave speed model shows dramatic improvements when comparisons are done at shorter periods, (25 s). Synthetics from the 1D model were created through mode summations while those from the 3D simulations were created using the spectral element method. To further assess errors in source depth and focal mechanism, comparisons between the three methods were made. These comparisons help to identify problematic stations and sources which may bias the final solution. Estimates of standard errors were generated for each event's source depth and focal mechanism to identify poorly constrained events. A final, well characterized set of sources and stations will be then used to iteratively improve the wave speed model of the Middle East. After a few iterations during the adjoint inversion process, the sources will be reexamined and relocated to further reduce mapping of source errors into structural features. Finally, efforts continue in developing the infrastructure required to 'quickly' generate event kernels at the n-th iteration and invert for a new, (n+1)-th, wave speed model of the Middle East. While development of the infrastructure proceeds, initial tests using a limited number of events shows the 3D model, while showing vast improvement compared to the 1D model, still requires substantial modifications. Employing our new, full source set and iterating the adjoint inversions at successively shorter periods will lead to significant changes and refined wave speed structures of the Middle East.« less

Random walks with shape prior for cochlea segmentation in ex vivo μCT.

PubMed

Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel Angel

2016-09-01

Cochlear implantation is a safe and effective surgical procedure to restore hearing in deaf patients. However, the level of restoration achieved may vary due to differences in anatomy, implant type and surgical access. In order to reduce the variability of the surgical outcomes, we previously proposed the use of a high-resolution model built from [Formula: see text] images and then adapted to patient-specific clinical CT scans. As the accuracy of the model is dependent on the precision of the original segmentation, it is extremely important to have accurate [Formula: see text] segmentation algorithms. We propose a new framework for cochlea segmentation in ex vivo [Formula: see text] images using random walks where a distance-based shape prior is combined with a region term estimated by a Gaussian mixture model. The prior is also weighted by a confidence map to adjust its influence according to the strength of the image contour. Random walks is performed iteratively, and the prior mask is aligned in every iteration. We tested the proposed approach in ten [Formula: see text] data sets and compared it with other random walks-based segmentation techniques such as guided random walks (Eslami et al. in Med Image Anal 17(2):236-253, 2013) and constrained random walks (Li et al. in Advances in image and video technology. Springer, Berlin, pp 215-226, 2012). Our approach demonstrated higher accuracy results due to the probability density model constituted by the region term and shape prior information weighed by a confidence map. The weighted combination of the distance-based shape prior with a region term into random walks provides accurate segmentations of the cochlea. The experiments suggest that the proposed approach is robust for cochlea segmentation.

Decentralized Feedback Controllers for Robust Stabilization of Periodic Orbits of Hybrid Systems: Application to Bipedal Walking.

PubMed

Hamed, Kaveh Akbari; Gregg, Robert D

2017-07-01

This paper presents a systematic algorithm to design time-invariant decentralized feedback controllers to exponentially and robustly stabilize periodic orbits for hybrid dynamical systems against possible uncertainties in discrete-time phases. The algorithm assumes a family of parameterized and decentralized nonlinear controllers to coordinate interconnected hybrid subsystems based on a common phasing variable. The exponential and [Formula: see text] robust stabilization problems of periodic orbits are translated into an iterative sequence of optimization problems involving bilinear and linear matrix inequalities. By investigating the properties of the Poincaré map, some sufficient conditions for the convergence of the iterative algorithm are presented. The power of the algorithm is finally demonstrated through designing a set of robust stabilizing local nonlinear controllers for walking of an underactuated 3D autonomous bipedal robot with 9 degrees of freedom, impact model uncertainties, and a decentralization scheme motivated by amputee locomotion with a transpelvic prosthetic leg.

Decentralized Feedback Controllers for Robust Stabilization of Periodic Orbits of Hybrid Systems: Application to Bipedal Walking

PubMed Central

Hamed, Kaveh Akbari; Gregg, Robert D.

2016-01-01

This paper presents a systematic algorithm to design time-invariant decentralized feedback controllers to exponentially and robustly stabilize periodic orbits for hybrid dynamical systems against possible uncertainties in discrete-time phases. The algorithm assumes a family of parameterized and decentralized nonlinear controllers to coordinate interconnected hybrid subsystems based on a common phasing variable. The exponential and H2 robust stabilization problems of periodic orbits are translated into an iterative sequence of optimization problems involving bilinear and linear matrix inequalities. By investigating the properties of the Poincaré map, some sufficient conditions for the convergence of the iterative algorithm are presented. The power of the algorithm is finally demonstrated through designing a set of robust stabilizing local nonlinear controllers for walking of an underactuated 3D autonomous bipedal robot with 9 degrees of freedom, impact model uncertainties, and a decentralization scheme motivated by amputee locomotion with a transpelvic prosthetic leg. PMID:28959117

Quantitative FE-EPMA measurement of formation and inhibition of carbon contamination on Fe for trace carbon analysis.

PubMed

Tanaka, Yuji; Yamashita, Takako; Nagoshi, Masayasu

2017-04-01

Hydrocarbon contamination introduced during point, line and map analyses in a field emission electron probe microanalysis (FE-EPMA) was investigated to enable reliable quantitative analysis of trace amounts of carbon in steels. The increment of contamination on pure iron in point analysis is proportional to the number of iterations of beam irradiation, but not to the accumulated irradiation time. A combination of a longer dwell time and single measurement with a liquid nitrogen (LN2) trap as an anti-contamination device (ACD) is sufficient for a quantitative point analysis. However, in line and map analyses, contamination increases with irradiation time in addition to the number of iterations, even though the LN2 trap and a plasma cleaner are used as ACDs. Thus, a shorter dwell time and single measurement are preferred for line and map analyses, although it is difficult to eliminate the influence of contamination. While ring-like contamination around the irradiation point grows during electron-beam irradiation, contamination at the irradiation point increases during blanking time after irradiation. This can explain the increment of contamination in iterative point analysis as well as in line and map analyses. Among the ACDs, which are tested in this study, specimen heating at 373 K has a significant contamination inhibition effect. This technique makes it possible to obtain line and map analysis data with minimum influence of contamination. The above-mentioned FE-EPMA data are presented and discussed in terms of the contamination-formation mechanisms and the preferable experimental conditions for the quantification of trace carbon in steels. © The Author 2016. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Global boundary flattening transforms for acoustic propagation under rough sea surfaces.

PubMed

Oba, Roger M

2010-07-01

This paper introduces a conformal transform of an acoustic domain under a one-dimensional, rough sea surface onto a domain with a flat top. This non-perturbative transform can include many hundreds of wavelengths of the surface variation. The resulting two-dimensional, flat-topped domain allows direct application of any existing, acoustic propagation model of the Helmholtz or wave equation using transformed sound speeds. Such a transform-model combination applies where the surface particle velocity is much slower than sound speed, such that the boundary motion can be neglected. Once the acoustic field is computed, the bijective (one-to-one and onto) mapping permits the field interpolation in terms of the original coordinates. The Bergstrom method for inverse Riemann maps determines the transform by iterated solution of an integral equation for a surface matching term. Rough sea surface forward scatter test cases provide verification of the method using a particular parabolic equation model of the Helmholtz equation.

Destruction of the Last Good Magnetic Surface in Diii-D Usn with Elms and C-Coils Shot 115467 due to C-Coils Using Maps

NASA Astrophysics Data System (ADS)

McCray, A.; Punjabi, A.; Ali, H.

2004-11-01

Unperturbed magnetic topology of DIII-D shot 115467 is described by the symmetric simple map (SSM) with map parameter k=0.2623 [1], then last good surface passes through x=0 and y=0.9995, q_edge=6.48 (same as in shot 115467) if six iterations of SSM are taken to be equivalent to single toroidal circuit of DIII-D. The dipole map (DM) calculates the effects of localized, external high mode numbers magnetic perturbations on motion of field lines. We use dipole map to describe effects of C-coils on field line trajectories in DIII-D. We apply DM after each iteration of SSM, with s=1.0021, x_dipole=1.5617, y_dipole= 0 [1] for shot 115467. We study the changes in the last good surface and its destruction as a function of I_C-coil. This work is supported by NASA SHARP program and DE-FG02-02ER54673. [1] H. Ali, A. Punjabi, A. Boozer, and T. Evans, presented at the 31st European Physical Society Plasma Physics Meeting, London, UK, June 29, 2004, paper P2-172.

Reusable Ada Software for Command and Control Workstation Map Manipulation

DTIC Science & Technology

1992-06-18

h-.. I.. b 1 .. hm . T.... ~ N -k.L A..-bt ... ~ 4.g -np ft. Figure 15. The Main Display Storyboard (final iteration) are other panels not shown which...Defense, October 1988. 18. Defense Mapping Agency, Products Catalog, Digitizing The Future, 3d ed., Department of Defense, No Date. 183 19. Deitel , H

Marginal Consistency: Upper-Bounding Partition Functions over Commutative Semirings.

PubMed

Werner, Tomás

2015-07-01

Many inference tasks in pattern recognition and artificial intelligence lead to partition functions in which addition and multiplication are abstract binary operations forming a commutative semiring. By generalizing max-sum diffusion (one of convergent message passing algorithms for approximate MAP inference in graphical models), we propose an iterative algorithm to upper bound such partition functions over commutative semirings. The iteration of the algorithm is remarkably simple: change any two factors of the partition function such that their product remains the same and their overlapping marginals become equal. In many commutative semirings, repeating this iteration for different pairs of factors converges to a fixed point when the overlapping marginals of every pair of factors coincide. We call this state marginal consistency. During that, an upper bound on the partition function monotonically decreases. This abstract algorithm unifies several existing algorithms, including max-sum diffusion and basic constraint propagation (or local consistency) algorithms in constraint programming. We further construct a hierarchy of marginal consistencies of increasingly higher levels and show than any such level can be enforced by adding identity factors of higher arity (order). Finally, we discuss instances of the framework for several semirings, including the distributive lattice and the max-sum and sum-product semirings.

A Bifurcation Problem for a Nonlinear Partial Differential Equation of Parabolic Type,

DTIC Science & Technology

NONLINEAR DIFFERENTIAL EQUATIONS, INTEGRATION), (*PARTIAL DIFFERENTIAL EQUATIONS, BOUNDARY VALUE PROBLEMS), BANACH SPACE , MAPPING (TRANSFORMATIONS), SET THEORY, TOPOLOGY, ITERATIONS, STABILITY, THEOREMS

WE-AB-303-09: Rapid Projection Computations for On-Board Digital Tomosynthesis in Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iliopoulos, AS; Sun, X; Pitsianis, N

2015-06-15

Purpose: To facilitate fast and accurate iterative volumetric image reconstruction from limited-angle on-board projections. Methods: Intrafraction motion hinders the clinical applicability of modern radiotherapy techniques, such as lung stereotactic body radiation therapy (SBRT). The LIVE system may impact clinical practice by recovering volumetric information via Digital Tomosynthesis (DTS), thus entailing low time and radiation dose for image acquisition during treatment. The DTS is estimated as a deformation of prior CT via iterative registration with on-board images; this shifts the challenge to the computational domain, owing largely to repeated projection computations across iterations. We address this issue by composing efficient digitalmore » projection operators from their constituent parts. This allows us to separate the static (projection geometry) and dynamic (volume/image data) parts of projection operations by means of pre-computations, enabling fast on-board processing, while also relaxing constraints on underlying numerical models (e.g. regridding interpolation kernels). Further decoupling the projectors into simpler ones ensures the incurred memory overhead remains low, within the capacity of a single GPU. These operators depend only on the treatment plan and may be reused across iterations and patients. The dynamic processing load is kept to a minimum and maps well to the GPU computational model. Results: We have integrated efficient, pre-computable modules for volumetric ray-casting and FDK-based back-projection with the LIVE processing pipeline. Our results show a 60x acceleration of the DTS computations, compared to the previous version, using a single GPU; presently, reconstruction is attained within a couple of minutes. The present implementation allows for significant flexibility in terms of the numerical and operational projection model; we are investigating the benefit of further optimizations and accurate digital projection sub-kernels. Conclusion: Composable projection operators constitute a versatile research tool which can greatly accelerate iterative registration algorithms and may be conducive to the clinical applicability of LIVE. National Institutes of Health Grant No. R01-CA184173; GPU donation by NVIDIA Corporation.« less

Integration of Tuyere, Raceway and Shaft Models for Predicting Blast Furnace Process

NASA Astrophysics Data System (ADS)

Fu, Dong; Tang, Guangwu; Zhao, Yongfu; D'Alessio, John; Zhou, Chenn Q.

2018-06-01

A novel modeling strategy is presented for simulating the blast furnace iron making process. Such physical and chemical phenomena are taking place across a wide range of length and time scales, and three models are developed to simulate different regions of the blast furnace, i.e., the tuyere model, the raceway model and the shaft model. This paper focuses on the integration of the three models to predict the entire blast furnace process. Mapping output and input between models and an iterative scheme are developed to establish communications between models. The effects of tuyere operation and burden distribution on blast furnace fuel efficiency are investigated numerically. The integration of different models provides a way to realistically simulate the blast furnace by improving the modeling resolution on local phenomena and minimizing the model assumptions.

Extension of an iterative closest point algorithm for simultaneous localization and mapping in corridor environments

NASA Astrophysics Data System (ADS)

Yue, Haosong; Chen, Weihai; Wu, Xingming; Wang, Jianhua

2016-03-01

Three-dimensional (3-D) simultaneous localization and mapping (SLAM) is a crucial technique for intelligent robots to navigate autonomously and execute complex tasks. It can also be applied to shape measurement, reverse engineering, and many other scientific or engineering fields. A widespread SLAM algorithm, named KinectFusion, performs well in environments with complex shapes. However, it cannot handle translation uncertainties well in highly structured scenes. This paper improves the KinectFusion algorithm and makes it competent in both structured and unstructured environments. 3-D line features are first extracted according to both color and depth data captured by Kinect sensor. Then the lines in the current data frame are matched with the lines extracted from the entire constructed world model. Finally, we fuse the distance errors of these line-pairs into the standard KinectFusion framework and estimate sensor poses using an iterative closest point-based algorithm. Comparative experiments with the KinectFusion algorithm and one state-of-the-art method in a corridor scene have been done. The experimental results demonstrate that after our improvement, the KinectFusion algorithm can also be applied to structured environments and has higher accuracy. Experiments on two open access datasets further validated our improvements.

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services

PubMed Central

Zamani, Hamid

2017-01-01

Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges of data aggregation, maintenance, integration, translation, analysis, and security/privacy. The study objective to establish an interactive BDA platform with simulated patient data using open-source software technologies was achieved by construction of a platform framework with Hadoop Distributed File System (HDFS) using HBase (key-value NoSQL database). Distributed data structures were generated from benchmarked hospital-specific metadata of nine billion patient records. At optimized iteration, HDFS ingestion of HFiles to HBase store files revealed sustained availability over hundreds of iterations; however, to complete MapReduce to HBase required a week (for 10 TB) and a month for three billion (30 TB) indexed patient records, respectively. Found inconsistencies of MapReduce limited the capacity to generate and replicate data efficiently. Apache Spark and Drill showed high performance with high usability for technical support but poor usability for clinical services. Hospital system based on patient-centric data was challenging in using HBase, whereby not all data profiles were fully integrated with the complex patient-to-hospital relationships. However, we recommend using HBase to achieve secured patient data while querying entire hospital volumes in a simplified clinical event model across clinical services. PMID:29375652

Using Distributed Data over HBase in Big Data Analytics Platform for Clinical Services.

PubMed

Chrimes, Dillon; Zamani, Hamid

2017-01-01

Big data analytics (BDA) is important to reduce healthcare costs. However, there are many challenges of data aggregation, maintenance, integration, translation, analysis, and security/privacy. The study objective to establish an interactive BDA platform with simulated patient data using open-source software technologies was achieved by construction of a platform framework with Hadoop Distributed File System (HDFS) using HBase (key-value NoSQL database). Distributed data structures were generated from benchmarked hospital-specific metadata of nine billion patient records. At optimized iteration, HDFS ingestion of HFiles to HBase store files revealed sustained availability over hundreds of iterations; however, to complete MapReduce to HBase required a week (for 10 TB) and a month for three billion (30 TB) indexed patient records, respectively. Found inconsistencies of MapReduce limited the capacity to generate and replicate data efficiently. Apache Spark and Drill showed high performance with high usability for technical support but poor usability for clinical services. Hospital system based on patient-centric data was challenging in using HBase, whereby not all data profiles were fully integrated with the complex patient-to-hospital relationships. However, we recommend using HBase to achieve secured patient data while querying entire hospital volumes in a simplified clinical event model across clinical services.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

MPL-A program for computations with iterated integrals on moduli spaces of curves of genus zero

NASA Astrophysics Data System (ADS)

Bogner, Christian

2016-06-01

We introduce the Maple program MPL for computations with multiple polylogarithms. The program is based on homotopy invariant iterated integrals on moduli spaces M0,n of curves of genus 0 with n ordered marked points. It includes the symbol map and procedures for the analytic computation of period integrals on M0,n. It supports the automated computation of a certain class of Feynman integrals.

Quantum mechanical treatment of large spin baths

NASA Astrophysics Data System (ADS)

Röhrig, Robin; Schering, Philipp; Gravert, Lars B.; Fauseweh, Benedikt; Uhrig, Götz S.

2018-04-01

The electronic spin in quantum dots can be described by central spin models (CSMs) with a very large number Neff≈104 to 106 of bath spins posing a tremendous challenge to theoretical simulations. Here, a fully quantum mechanical theory is developed for the limit Neff→∞ by means of iterated equations of motion (iEoM). We find that the CSM can be mapped to a four-dimensional impurity coupled to a noninteracting bosonic bath in this limit. Remarkably, even for infinite bath the CSM does not become completely classical. The data obtained by the proposed iEoM approach are tested successfully against data from other, established approaches. Thus the iEoM mapping extends the set of theoretical tools that can be used to understand the spin dynamics in large CSMs.

DAVIS: A direct algorithm for velocity-map imaging system

NASA Astrophysics Data System (ADS)

Harrison, G. R.; Vaughan, J. C.; Hidle, B.; Laurent, G. M.

2018-05-01

In this work, we report a direct (non-iterative) algorithm to reconstruct the three-dimensional (3D) momentum-space picture of any charged particles collected with a velocity-map imaging system from the two-dimensional (2D) projected image captured by a position-sensitive detector. The method consists of fitting the measured image with the 2D projection of a model 3D velocity distribution defined by the physics of the light-matter interaction. The meaningful angle-correlated information is first extracted from the raw data by expanding the image with a complete set of Legendre polynomials. Both the particle's angular and energy distributions are then directly retrieved from the expansion coefficients. The algorithm is simple, easy to implement, fast, and explicitly takes into account the pixelization effect in the measurement.

Depth-color fusion strategy for 3-D scene modeling with Kinect.

PubMed

Camplani, Massimo; Mantecon, Tomas; Salgado, Luis

2013-12-01

Low-cost depth cameras, such as Microsoft Kinect, have completely changed the world of human-computer interaction through controller-free gaming applications. Depth data provided by the Kinect sensor presents several noise-related problems that have to be tackled to improve the accuracy of the depth data, thus obtaining more reliable game control platforms and broadening its applicability. In this paper, we present a depth-color fusion strategy for 3-D modeling of indoor scenes with Kinect. Accurate depth and color models of the background elements are iteratively built, and used to detect moving objects in the scene. Kinect depth data is processed with an innovative adaptive joint-bilateral filter that efficiently combines depth and color by analyzing an edge-uncertainty map and the detected foreground regions. Results show that the proposed approach efficiently tackles main Kinect data problems: distance-dependent depth maps, spatial noise, and temporal random fluctuations are dramatically reduced; objects depth boundaries are refined, and nonmeasured depth pixels are interpolated. Moreover, a robust depth and color background model and accurate moving objects silhouette are generated.

Varying face occlusion detection and iterative recovery for face recognition

NASA Astrophysics Data System (ADS)

Wang, Meng; Hu, Zhengping; Sun, Zhe; Zhao, Shuhuan; Sun, Mei

2017-05-01

In most sparse representation methods for face recognition (FR), occlusion problems were usually solved via removing the occlusion part of both query samples and training samples to perform the recognition process. This practice ignores the global feature of facial image and may lead to unsatisfactory results due to the limitation of local features. Considering the aforementioned drawback, we propose a method called varying occlusion detection and iterative recovery for FR. The main contributions of our method are as follows: (1) to detect an accurate occlusion area of facial images, an image processing and intersection-based clustering combination method is used for occlusion FR; (2) according to an accurate occlusion map, the new integrated facial images are recovered iteratively and put into a recognition process; and (3) the effectiveness on recognition accuracy of our method is verified by comparing it with three typical occlusion map detection methods. Experiments show that the proposed method has a highly accurate detection and recovery performance and that it outperforms several similar state-of-the-art methods against partial contiguous occlusion.

Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida

USGS Publications Warehouse

Arthur, J.D.; Wood, H.A.R.; Baker, A.E.; Cichon, J.R.; Raines, G.L.

2007-01-01

The Florida Aquifer Vulnerability Assessment (FAVA) was designed to provide a tool for environmental, regulatory, resource management, and planning professionals to facilitate protection of groundwater resources from surface sources of contamination. The FAVA project implements weights-of-evidence (WofE), a data-driven, Bayesian-probabilistic model to generate a series of maps reflecting relative aquifer vulnerability of Florida's principal aquifer systems. The vulnerability assessment process, from project design to map implementation is described herein in reference to the Floridan aquifer system (FAS). The WofE model calculates weighted relationships between hydrogeologic data layers that influence aquifer vulnerability and ambient groundwater parameters in wells that reflect relative degrees of vulnerability. Statewide model input data layers (evidential themes) include soil hydraulic conductivity, density of karst features, thickness of aquifer confinement, and hydraulic head difference between the FAS and the watertable. Wells with median dissolved nitrogen concentrations exceeding statistically established thresholds serve as training points in the WofE model. The resulting vulnerability map (response theme) reflects classified posterior probabilities based on spatial relationships between the evidential themes and training points. The response theme is subjected to extensive sensitivity and validation testing. Among the model validation techniques is calculation of a response theme based on a different water-quality indicator of relative recharge or vulnerability: dissolved oxygen. Successful implementation of the FAVA maps was facilitated by the overall project design, which included a needs assessment and iterative technical advisory committee input and review. Ongoing programs to protect Florida's springsheds have led to development of larger-scale WofE-based vulnerability assessments. Additional applications of the maps include land-use planning amendments and prioritization of land purchases to protect groundwater resources. ?? International Association for Mathematical Geology 2007.

Standard and reduced radiation dose liver CT images: adaptive statistical iterative reconstruction versus model-based iterative reconstruction-comparison of findings and image quality.

PubMed

Shuman, William P; Chan, Keith T; Busey, Janet M; Mitsumori, Lee M; Choi, Eunice; Koprowicz, Kent M; Kanal, Kalpana M

2014-12-01

To investigate whether reduced radiation dose liver computed tomography (CT) images reconstructed with model-based iterative reconstruction ( MBIR model-based iterative reconstruction ) might compromise depiction of clinically relevant findings or might have decreased image quality when compared with clinical standard radiation dose CT images reconstructed with adaptive statistical iterative reconstruction ( ASIR adaptive statistical iterative reconstruction ). With institutional review board approval, informed consent, and HIPAA compliance, 50 patients (39 men, 11 women) were prospectively included who underwent liver CT. After a portal venous pass with ASIR adaptive statistical iterative reconstruction images, a 60% reduced radiation dose pass was added with MBIR model-based iterative reconstruction images. One reviewer scored ASIR adaptive statistical iterative reconstruction image quality and marked findings. Two additional independent reviewers noted whether marked findings were present on MBIR model-based iterative reconstruction images and assigned scores for relative conspicuity, spatial resolution, image noise, and image quality. Liver and aorta Hounsfield units and image noise were measured. Volume CT dose index and size-specific dose estimate ( SSDE size-specific dose estimate ) were recorded. Qualitative reviewer scores were summarized. Formal statistical inference for signal-to-noise ratio ( SNR signal-to-noise ratio ), contrast-to-noise ratio ( CNR contrast-to-noise ratio ), volume CT dose index, and SSDE size-specific dose estimate was made (paired t tests), with Bonferroni adjustment. Two independent reviewers identified all 136 ASIR adaptive statistical iterative reconstruction image findings (n = 272) on MBIR model-based iterative reconstruction images, scoring them as equal or better for conspicuity, spatial resolution, and image noise in 94.1% (256 of 272), 96.7% (263 of 272), and 99.3% (270 of 272), respectively. In 50 image sets, two reviewers (n = 100) scored overall image quality as sufficient or good with MBIR model-based iterative reconstruction in 99% (99 of 100). Liver SNR signal-to-noise ratio was significantly greater for MBIR model-based iterative reconstruction (10.8 ± 2.5 [standard deviation] vs 7.7 ± 1.4, P < .001); there was no difference for CNR contrast-to-noise ratio (2.5 ± 1.4 vs 2.4 ± 1.4, P = .45). For ASIR adaptive statistical iterative reconstruction and MBIR model-based iterative reconstruction , respectively, volume CT dose index was 15.2 mGy ± 7.6 versus 6.2 mGy ± 3.6; SSDE size-specific dose estimate was 16.4 mGy ± 6.6 versus 6.7 mGy ± 3.1 (P < .001). Liver CT images reconstructed with MBIR model-based iterative reconstruction may allow up to 59% radiation dose reduction compared with the dose with ASIR adaptive statistical iterative reconstruction , without compromising depiction of findings or image quality. © RSNA, 2014.

High and low density development in Puerto Rico

Treesearch

William A. Gould; Sebastian Martinuzzi; Olga M. Ramos Gonzalez

2008-01-01

This map shows the distribution of high and low density developed lands in Puerto Rico (Martinuzzi et al. 2007). The map was created using a mosaic of Landsat ETM+ images that range from the years 2000 to 2003. The developed land cover was classified using the Iterative Self-Organizing Data Analysis Technique (ISODATA) unsupervised classification (ERDAS 2003)....

Integrating Concept Mapping into Information Systems Education for Meaningful Learning and Assessment

ERIC Educational Resources Information Center

Wei, Wei; Yue, Kwok-Bun

2017-01-01

Concept map (CM) is a theoretically sound yet easy to learn tool and can be effectively used to represent knowledge. Even though many disciplines have adopted CM as a teaching and learning tool to improve learning effectiveness, its application in IS curriculum is sparse. Meaningful learning happens when one iteratively integrates new concepts and…

The TRIDEC Virtual Tsunami Atlas - customized value-added simulation data products for Tsunami Early Warning generated on compute clusters

NASA Astrophysics Data System (ADS)

Löwe, P.; Hammitzsch, M.; Babeyko, A.; Wächter, J.

2012-04-01

The development of new Tsunami Early Warning Systems (TEWS) requires the modelling of spatio-temporal spreading of tsunami waves both recorded from past events and hypothetical future cases. The model results are maintained in digital repositories for use in TEWS command and control units for situation assessment once a real tsunami occurs. Thus the simulation results must be absolutely trustworthy, in a sense that the quality of these datasets is assured. This is a prerequisite as solid decision making during a crisis event and the dissemination of dependable warning messages to communities under risk will be based on them. This requires data format validity, but even more the integrity and information value of the content, being a derived value-added product derived from raw tsunami model output. Quality checking of simulation result products can be done in multiple ways, yet the visual verification of both temporal and spatial spreading characteristics for each simulation remains important. The eye of the human observer still remains an unmatched tool for the detection of irregularities. This requires the availability of convenient, human-accessible mappings of each simulation. The improvement of tsunami models necessitates the changes in many variables, including simulation end-parameters. Whenever new improved iterations of the general models or underlying spatial data are evaluated, hundreds to thousands of tsunami model results must be generated for each model iteration, each one having distinct initial parameter settings. The use of a Compute Cluster Environment (CCE) of sufficient size allows the automated generation of all tsunami-results within model iterations in little time. This is a significant improvement to linear processing on dedicated desktop machines or servers. This allows for accelerated/improved visual quality checking iterations, which in turn can provide a positive feedback into the overall model improvement iteratively. An approach to set-up and utilize the CCE has been implemented by the project Collaborative, Complex, and Critical Decision Processes in Evolving Crises (TRIDEC) funded under the European Union's FP7. TRIDEC focuses on real-time intelligent information management in Earth management. The addressed challenges include the design and implementation of a robust and scalable service infrastructure supporting the integration and utilisation of existing resources with accelerated generation of large volumes of data. These include sensor systems, geo-information repositories, simulations and data fusion tools. Additionally, TRIDEC adopts enhancements of Service Oriented Architecture (SOA) principles in terms of Event Driven Architecture (EDA) design. As a next step the implemented CCE's services to generate derived and customized simulation products are foreseen to be provided via an EDA service for on-demand processing for specific threat-parameters and to accommodate for model improvements.

Automatic recognition of holistic functional brain networks using iteratively optimized convolutional neural networks (IO-CNN) with weak label initialization.

PubMed

Zhao, Yu; Ge, Fangfei; Liu, Tianming

2018-07-01

fMRI data decomposition techniques have advanced significantly from shallow models such as Independent Component Analysis (ICA) and Sparse Coding and Dictionary Learning (SCDL) to deep learning models such Deep Belief Networks (DBN) and Convolutional Autoencoder (DCAE). However, interpretations of those decomposed networks are still open questions due to the lack of functional brain atlases, no correspondence across decomposed or reconstructed networks across different subjects, and significant individual variabilities. Recent studies showed that deep learning, especially deep convolutional neural networks (CNN), has extraordinary ability of accommodating spatial object patterns, e.g., our recent works using 3D CNN for fMRI-derived network classifications achieved high accuracy with a remarkable tolerance for mistakenly labelled training brain networks. However, the training data preparation is one of the biggest obstacles in these supervised deep learning models for functional brain network map recognitions, since manual labelling requires tedious and time-consuming labours which will sometimes even introduce label mistakes. Especially for mapping functional networks in large scale datasets such as hundreds of thousands of brain networks used in this paper, the manual labelling method will become almost infeasible. In response, in this work, we tackled both the network recognition and training data labelling tasks by proposing a new iteratively optimized deep learning CNN (IO-CNN) framework with an automatic weak label initialization, which enables the functional brain networks recognition task to a fully automatic large-scale classification procedure. Our extensive experiments based on ABIDE-II 1099 brains' fMRI data showed the great promise of our IO-CNN framework. Copyright © 2018 Elsevier B.V. All rights reserved.

Resource utilization model for the algorithm to architecture mapping model

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Patel, Rakesh R.

1993-01-01

The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.

Anisotropic modeling and joint-MAP stitching for improved ultrasound model-based iterative reconstruction of large and thick specimens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almansouri, Hani; Venkatakrishnan, Singanallur V.; Clayton, Dwight A.

One-sided non-destructive evaluation (NDE) is widely used to inspect materials, such as concrete structures in nuclear power plants (NPP). A widely used method for one-sided NDE is the synthetic aperture focusing technique (SAFT). The SAFT algorithm produces reasonable results when inspecting simple structures. However, for complex structures, such as heavily reinforced thick concrete structures, SAFT results in artifacts and hence there is a need for a more sophisticated inversion technique. Model-based iterative reconstruction (MBIR) algorithms, which are typically equivalent to regularized inversion techniques, offer a powerful framework to incorporate complex models for the physics, detector miscalibrations and the materials beingmore » imaged to obtain high quality reconstructions. Previously, we have proposed an ultrasonic MBIR method that signifcantly improves reconstruction quality compared to SAFT. However, the method made some simplifying assumptions on the propagation model and did not disucss ways to handle data that is obtained by raster scanning a system over a surface to inspect large regions. In this paper, we propose a novel MBIR algorithm that incorporates an anisotropic forward model and allows for the joint processing of data obtained from a system that raster scans a large surface. We demonstrate that the new MBIR method can produce dramatic improvements in reconstruction quality compared to SAFT and suppresses articfacts compared to the perviously presented MBIR approach.« less

Anisotropic modeling and joint-MAP stitching for improved ultrasound model-based iterative reconstruction of large and thick specimens

NASA Astrophysics Data System (ADS)

Almansouri, Hani; Venkatakrishnan, Singanallur; Clayton, Dwight; Polsky, Yarom; Bouman, Charles; Santos-Villalobos, Hector

2018-04-01

One-sided non-destructive evaluation (NDE) is widely used to inspect materials, such as concrete structures in nuclear power plants (NPP). A widely used method for one-sided NDE is the synthetic aperture focusing technique (SAFT). The SAFT algorithm produces reasonable results when inspecting simple structures. However, for complex structures, such as heavily reinforced thick concrete structures, SAFT results in artifacts and hence there is a need for a more sophisticated inversion technique. Model-based iterative reconstruction (MBIR) algorithms, which are typically equivalent to regularized inversion techniques, offer a powerful framework to incorporate complex models for the physics, detector miscalibrations and the materials being imaged to obtain high quality reconstructions. Previously, we have proposed an ultrasonic MBIR method that signifcantly improves reconstruction quality compared to SAFT. However, the method made some simplifying assumptions on the propagation model and did not disucss ways to handle data that is obtained by raster scanning a system over a surface to inspect large regions. In this paper, we propose a novel MBIR algorithm that incorporates an anisotropic forward model and allows for the joint processing of data obtained from a system that raster scans a large surface. We demonstrate that the new MBIR method can produce dramatic improvements in reconstruction quality compared to SAFT and suppresses articfacts compared to the perviously presented MBIR approach.

A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard

PubMed Central

Azadmanjir, Zahra; Torabi, Mashallah; Safdari, Reza; Bayat, Maryam; Golmahi, Fatemeh

2015-01-01

Introduction: management challenges of clinical laboratories are more complicated for educational hospital clinical laboratories. Managers can use tools of business intelligence (BI), such as information dashboards that provide the possibility of intelligent decision-making and problem solving about increasing income, reducing spending, utilization management and even improving quality. Critical phase of dashboard design is setting indicators and modeling causal relations between them. The paper describes the process of creating a map for laboratory dashboard. Methods: the study is one part of an action research that begins from 2012 by innovation initiative for implementing laboratory intelligent dashboard. Laboratories management problems were determined in educational hospitals by the brainstorming sessions. Then, with regard to the problems key performance indicators (KPIs) specified. Results: the map of indicators designed in form of three layered. They have a causal relationship so that issues measured in the subsequent layers affect issues measured in the prime layers. Conclusion: the proposed indicator map can be the base of performance monitoring. However, these indicators can be modified to improve during iterations of dashboard designing process. PMID:26483593

Theory of wavelet-based coarse-graining hierarchies for molecular dynamics.

PubMed

Rinderspacher, Berend Christopher; Bardhan, Jaydeep P; Ismail, Ahmed E

2017-07-01

We present a multiresolution approach to compressing the degrees of freedom and potentials associated with molecular dynamics, such as the bond potentials. The approach suggests a systematic way to accelerate large-scale molecular simulations with more than two levels of coarse graining, particularly applications of polymeric materials. In particular, we derive explicit models for (arbitrarily large) linear (homo)polymers and iterative methods to compute large-scale wavelet decompositions from fragment solutions. This approach does not require explicit preparation of atomistic-to-coarse-grained mappings, but instead uses the theory of diffusion wavelets for graph Laplacians to develop system-specific mappings. Our methodology leads to a hierarchy of system-specific coarse-grained degrees of freedom that provides a conceptually clear and mathematically rigorous framework for modeling chemical systems at relevant model scales. The approach is capable of automatically generating as many coarse-grained model scales as necessary, that is, to go beyond the two scales in conventional coarse-grained strategies; furthermore, the wavelet-based coarse-grained models explicitly link time and length scales. Furthermore, a straightforward method for the reintroduction of omitted degrees of freedom is presented, which plays a major role in maintaining model fidelity in long-time simulations and in capturing emergent behaviors.

Development and benchmarking of TASSER(iter) for the iterative improvement of protein structure predictions.

PubMed

Lee, Seung Yup; Skolnick, Jeffrey

2007-07-01

To improve the accuracy of TASSER models especially in the limit where threading provided template alignments are of poor quality, we have developed the TASSER(iter) algorithm which uses the templates and contact restraints from TASSER generated models for iterative structure refinement. We apply TASSER(iter) to a large benchmark set of 2,773 nonhomologous single domain proteins that are < or = 200 in length and that cover the PDB at the level of 35% pairwise sequence identity. Overall, TASSER(iter) models have a smaller global average RMSD of 5.48 A compared to 5.81 A RMSD of the original TASSER models. Classifying the targets by the level of prediction difficulty (where Easy targets have a good template with a corresponding good threading alignment, Medium targets have a good template but a poor alignment, and Hard targets have an incorrectly identified template), TASSER(iter) (TASSER) models have an average RMSD of 4.15 A (4.35 A) for the Easy set and 9.05 A (9.52 A) for the Hard set. The largest reduction of average RMSD is for the Medium set where the TASSER(iter) models have an average global RMSD of 5.67 A compared to 6.72 A of the TASSER models. Seventy percent of the Medium set TASSER(iter) models have a smaller RMSD than the TASSER models, while 63% of the Easy and 60% of the Hard TASSER models are improved by TASSER(iter). For the foldable cases, where the targets have a RMSD to the native <6.5 A, TASSER(iter) shows obvious improvement over TASSER models: For the Medium set, it improves the success rate from 57.0 to 67.2%, followed by the Hard targets where the success rate improves from 32.0 to 34.8%, with the smallest improvement in the Easy targets from 82.6 to 84.0%. These results suggest that TASSER(iter) can provide more reliable predictions for targets of Medium difficulty, a range that had resisted improvement in the quality of protein structure predictions. 2007 Wiley-Liss, Inc.

Mapping chemicals in air using an environmental CAT scanning system: evaluation of algorithms

NASA Astrophysics Data System (ADS)

Samanta, A.; Todd, L. A.

A new technique is being developed which creates near real-time maps of chemical concentrations in air for environmental and occupational environmental applications. This technique, we call Environmental CAT Scanning, combines the real-time measuring technique of open-path Fourier transform infrared spectroscopy with the mapping capabilitites of computed tomography to produce two-dimensional concentration maps. With this system, a network of open-path measurements is obtained over an area; measurements are then processed using a tomographic algorithm to reconstruct the concentrations. This research focussed on the process of evaluating and selecting appropriate reconstruction algorithms, for use in the field, by using test concentration data from both computer simultation and laboratory chamber studies. Four algorithms were tested using three types of data: (1) experimental open-path data from studies that used a prototype opne-path Fourier transform/computed tomography system in an exposure chamber; (2) synthetic open-path data generated from maps created by kriging point samples taken in the chamber studies (in 1), and; (3) synthetic open-path data generated using a chemical dispersion model to create time seires maps. The iterative algorithms used to reconstruct the concentration data were: Algebraic Reconstruction Technique without Weights (ART1), Algebraic Reconstruction Technique with Weights (ARTW), Maximum Likelihood with Expectation Maximization (MLEM) and Multiplicative Algebraic Reconstruction Technique (MART). Maps were evaluated quantitatively and qualitatively. In general, MART and MLEM performed best, followed by ARTW and ART1. However, algorithm performance varied under different contaminant scenarios. This study showed the importance of using a variety of maps, particulary those generated using dispersion models. The time series maps provided a more rigorous test of the algorithms and allowed distinctions to be made among the algorithms. A comprehensive evaluation of algorithms, for the environmental application of tomography, requires the use of a battery of test concentration data before field implementation, which models reality and tests the limits of the algorithms.

Aorta modeling with the element-based zero-stress state and isogeometric discretization

NASA Astrophysics Data System (ADS)

Takizawa, Kenji; Tezduyar, Tayfun E.; Sasaki, Takafumi

2017-02-01

Patient-specific arterial fluid-structure interaction computations, including aorta computations, require an estimation of the zero-stress state (ZSS), because the image-based arterial geometries do not come from a ZSS. We have earlier introduced a method for estimation of the element-based ZSS (EBZSS) in the context of finite element discretization of the arterial wall. The method has three main components. 1. An iterative method, which starts with a calculated initial guess, is used for computing the EBZSS such that when a given pressure load is applied, the image-based target shape is matched. 2. A method for straight-tube segments is used for computing the EBZSS so that we match the given diameter and longitudinal stretch in the target configuration and the "opening angle." 3. An element-based mapping between the artery and straight-tube is extracted from the mapping between the artery and straight-tube segments. This provides the mapping from the arterial configuration to the straight-tube configuration, and from the estimated EBZSS of the straight-tube configuration back to the arterial configuration, to be used as the initial guess for the iterative method that matches the image-based target shape. Here we present the version of the EBZSS estimation method with isogeometric wall discretization. With isogeometric discretization, we can obtain the element-based mapping directly, instead of extracting it from the mapping between the artery and straight-tube segments. That is because all we need for the element-based mapping, including the curvatures, can be obtained within an element. With NURBS basis functions, we may be able to achieve a similar level of accuracy as with the linear basis functions, but using larger-size and much fewer elements. Higher-order NURBS basis functions allow representation of more complex shapes within an element. To show how the new EBZSS estimation method performs, we first present 2D test computations with straight-tube configurations. Then we show how the method can be used in a 3D computation where the target geometry is coming from medical image of a human aorta.

Using habitat suitability models to target invasive plant species surveys

USGS Publications Warehouse

Crall, Alycia W.; Jarnevich, Catherine S.; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P 2) = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.

Using habitat suitability models to target invasive plant species surveys.

PubMed

Crall, Alycia W; Jarnevich, Catherine S; Panke, Brendon; Young, Nick; Renz, Mark; Morisette, Jeffrey

2013-01-01

Managers need new tools for detecting the movement and spread of nonnative, invasive species. Habitat suitability models are a popular tool for mapping the potential distribution of current invaders, but the ability of these models to prioritize monitoring efforts has not been tested in the field. We tested the utility of an iterative sampling design (i.e., models based on field observations used to guide subsequent field data collection to improve the model), hypothesizing that model performance would increase when new data were gathered from targeted sampling using criteria based on the initial model results. We also tested the ability of habitat suitability models to predict the spread of invasive species, hypothesizing that models would accurately predict occurrences in the field, and that the use of targeted sampling would detect more species with less sampling effort than a nontargeted approach. We tested these hypotheses on two species at the state scale (Centaurea stoebe and Pastinaca sativa) in Wisconsin (USA), and one genus at the regional scale (Tamarix) in the western United States. These initial data were merged with environmental data at 30-m2 resolution for Wisconsin and 1-km2 resolution for the western United States to produce our first iteration models. We stratified these initial models to target field sampling and compared our models and success at detecting our species of interest to other surveys being conducted during the same field season (i.e., nontargeted sampling). Although more data did not always improve our models based on correct classification rate (CCR), sensitivity, specificity, kappa, or area under the curve (AUC), our models generated from targeted sampling data always performed better than models generated from nontargeted data. For Wisconsin species, the model described actual locations in the field fairly well (kappa = 0.51, 0.19, P < 0.01), and targeted sampling did detect more species than nontargeted sampling with less sampling effort (chi2 = 47.42, P < 0.01). From these findings, we conclude that habitat suitability models can be highly useful tools for guiding invasive species monitoring, and we support the use of an iterative sampling design for guiding such efforts.

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Improved mapping of radio sources from VLBI data by least-square fit

NASA Technical Reports Server (NTRS)

Rodemich, E. R.

1985-01-01

A method is described for producing improved mapping of radio sources from Very Long Base Interferometry (VLBI) data. The method described is more direct than existing Fourier methods, is often more accurate, and runs at least as fast. The visibility data is modeled here, as in existing methods, as a function of the unknown brightness distribution and the unknown antenna gains and phases. These unknowns are chosen so that the resulting function values are as near as possible to the observed values. If researchers use the radio mapping source deviation to measure the closeness of this fit to the observed values, they are led to the problem of minimizing a certain function of all the unknown parameters. This minimization problem cannot be solved directly, but it can be attacked by iterative methods which we show converge automatically to the minimum with no user intervention. The resulting brightness distribution will furnish the best fit to the data among all brightness distributions of given resolution.

A statistically valid method for using FIA plots to guide spectral class rejection in producing stratification maps

Treesearch

Michael L. Hoppus; Andrew J. Lister

2002-01-01

A Landsat TM classification method (iterative guided spectral class rejection) produced a forest cover map of southern West Virginia that provided the stratification layer for producing estimates of timberland area from Forest Service FIA ground plots using a stratified sampling technique. These same high quality and expensive FIA ground plots provided ground reference...

Joint two dimensional inversion of gravity and magnetotelluric data using correspondence maps

NASA Astrophysics Data System (ADS)

Carrillo Lopez, J.; Gallardo, L. A.

2016-12-01

Inverse problems in Earth sciences are inherently non-unique. To improve models and reduce the number of solutions we need to provide extra information. In geological context, this information could be a priori information, for example, geological information, well log data, smoothness, or actually, information of measures of different kind of data. Joint inversion provides an approach to improve the solution and reduce the errors due to suppositions of each method. To do that, we need a link between two or more models. Some approaches have been explored successfully in recent years. For example, Gallardo and Meju (2003), Gallardo and Meju (2004, 2011), and Gallardo et. al. (2012) used the directions of properties to measure the similarity between models minimizing their cross gradients. In this work, we proposed a joint iterative inversion method that use spatial distribution of properties as a link. Correspondence maps could be better characterizing specific Earth systems due they consider the relation between properties. We implemented a code in Fortran to do a two dimensional inversion of magnetotelluric and gravity data, which are two of the standard methods in geophysical exploration. Synthetic tests show the advantages of joint inversion using correspondence maps against separate inversion. Finally, we applied this technique to magnetotelluric and gravity data in the geothermal zone located in Cerro Prieto, México.

Spatial uncertainty of a geoid undulation model in Guayaquil, Ecuador

NASA Astrophysics Data System (ADS)

Chicaiza, E. G.; Leiva, C. A.; Arranz, J. J.; Buenańo, X. E.

2017-06-01

Geostatistics is a discipline that deals with the statistical analysis of regionalized variables. In this case study, geostatistics is used to estimate geoid undulation in the rural area of Guayaquil town in Ecuador. The geostatistical approach was chosen because the estimation error of prediction map is getting. Open source statistical software R and mainly geoR, gstat and RGeostats libraries were used. Exploratory data analysis (EDA), trend and structural analysis were carried out. An automatic model fitting by Iterative Least Squares and other fitting procedures were employed to fit the variogram. Finally, Kriging using gravity anomaly of Bouguer as external drift and Universal Kriging were used to get a detailed map of geoid undulation. The estimation uncertainty was reached in the interval [-0.5; +0.5] m for errors and a maximum estimation standard deviation of 2 mm in relation with the method of interpolation applied. The error distribution of the geoid undulation map obtained in this study provides a better result than Earth gravitational models publicly available for the study area according the comparison with independent validation points. The main goal of this paper is to confirm the feasibility to use geoid undulations from Global Navigation Satellite Systems and leveling field measurements and geostatistical techniques methods in order to use them in high-accuracy engineering projects.

Application of Contraction Mappings to the Control of Nonlinear Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Killingsworth, W. R., Jr.

1972-01-01

The theoretical and applied aspects of successive approximation techniques are considered for the determination of controls for nonlinear dynamical systems. Particular emphasis is placed upon the methods of contraction mappings and modified contraction mappings. It is shown that application of the Pontryagin principle to the optimal nonlinear regulator problem results in necessary conditions for optimality in the form of a two point boundary value problem (TPBVP). The TPBVP is represented by an operator equation and functional analytic results on the iterative solution of operator equations are applied. The general convergence theorems are translated and applied to those operators arising from the optimal regulation of nonlinear systems. It is shown that simply structured matrices and similarity transformations may be used to facilitate the calculation of the matrix Green functions and the evaluation of the convergence criteria. A controllability theory based on the integral representation of TPBVP's, the implicit function theorem, and contraction mappings is developed for nonlinear dynamical systems. Contraction mappings are theoretically and practically applied to a nonlinear control problem with bounded input control and the Lipschitz norm is used to prove convergence for the nondifferentiable operator. A dynamic model representing community drug usage is developed and the contraction mappings method is used to study the optimal regulation of the nonlinear system.

Metric Optimization for Surface Analysis in the Laplace-Beltrami Embedding Space

PubMed Central

Lai, Rongjie; Wang, Danny J.J.; Pelletier, Daniel; Mohr, David; Sicotte, Nancy; Toga, Arthur W.

2014-01-01

In this paper we present a novel approach for the intrinsic mapping of anatomical surfaces and its application in brain mapping research. Using the Laplace-Beltrami eigen-system, we represent each surface with an isometry invariant embedding in a high dimensional space. The key idea in our system is that we realize surface deformation in the embedding space via the iterative optimization of a conformal metric without explicitly perturbing the surface or its embedding. By minimizing a distance measure in the embedding space with metric optimization, our method generates a conformal map directly between surfaces with highly uniform metric distortion and the ability of aligning salient geometric features. Besides pairwise surface maps, we also extend the metric optimization approach for group-wise atlas construction and multi-atlas cortical label fusion. In experimental results, we demonstrate the robustness and generality of our method by applying it to map both cortical and hippocampal surfaces in population studies. For cortical labeling, our method achieves excellent performance in a cross-validation experiment with 40 manually labeled surfaces, and successfully models localized brain development in a pediatric study of 80 subjects. For hippocampal mapping, our method produces much more significant results than two popular tools on a multiple sclerosis study of 109 subjects. PMID:24686245

Competency Maps: an Effective Model to Integrate Professional Competencies Across a STEM Curriculum

NASA Astrophysics Data System (ADS)

Sánchez Carracedo, Fermín; Soler, Antonia; Martín, Carme; López, David; Ageno, Alicia; Cabré, Jose; Garcia, Jordi; Aranda, Joan; Gibert, Karina

2018-05-01

Curricula designed in the context of the European Higher Education Area need to be based on both domain-specific and professional competencies. Whereas universities have had extensive experience in developing students' domain-specific competencies, fostering professional competencies poses a new challenge we need to face. This paper presents a model to globally develop professional competencies in a STEM (science, technology, engineering, and mathematics) degree program, and assesses the results of its implementation after 4 years. The model is based on the use of competency maps, in which each competency is defined in terms of competency units. Each competency unit is described by a set of expected learning outcomes at three domain levels. This model allows careful analysis, revision, and iteration for an effective integration of professional competencies in domain-specific subjects. A global competency map is also designed, including all the professional competency learning outcomes to be achieved throughout the degree. This map becomes a useful tool for curriculum designers and coordinators. The results were obtained from four sources: (1) students' grades (classes graduated from 2013 to 2016, the first 4 years of the new Bachelor's Degree in Informatics Engineering at the Barcelona School of Informatics); (2) students' surveys (answered by students when they finished the degree); (3) the government employment survey, where former students evaluate their satisfaction of the received training in the light of their work experience; and (4) the Everis Foundation University-Enterprise Ranking, answered by over 2000 employers evaluating their satisfaction regarding their employees' university training, where the Barcelona School of Informatics scores first in the national ranking. The results show that competency maps are a good tool for developing professional competencies in a STEM degree.

Statistical Significance of Optical Map Alignments

PubMed Central

Sarkar, Deepayan; Goldstein, Steve; Schwartz, David C.

2012-01-01

Abstract The Optical Mapping System constructs ordered restriction maps spanning entire genomes through the assembly and analysis of large datasets comprising individually analyzed genomic DNA molecules. Such restriction maps uniquely reveal mammalian genome structure and variation, but also raise computational and statistical questions beyond those that have been solved in the analysis of smaller, microbial genomes. We address the problem of how to filter maps that align poorly to a reference genome. We obtain map-specific thresholds that control errors and improve iterative assembly. We also show how an optimal self-alignment score provides an accurate approximation to the probability of alignment, which is useful in applications seeking to identify structural genomic abnormalities. PMID:22506568

Cochlea segmentation using iterated random walks with shape prior

NASA Astrophysics Data System (ADS)

Ruiz Pujadas, Esmeralda; Kjer, Hans Martin; Vera, Sergio; Ceresa, Mario; González Ballester, Miguel Ángel

2016-03-01

Cochlear implants can restore hearing to deaf or partially deaf patients. In order to plan the intervention, a model from high resolution µCT images is to be built from accurate cochlea segmentations and then, adapted to a patient-specific model. Thus, a precise segmentation is required to build such a model. We propose a new framework for segmentation of µCT cochlear images using random walks where a region term is combined with a distance shape prior weighted by a confidence map to adjust its influence according to the strength of the image contour. Then, the region term can take advantage of the high contrast between the background and foreground and the distance prior guides the segmentation to the exterior of the cochlea as well as to less contrasted regions inside the cochlea. Finally, a refinement is performed preserving the topology using a topological method and an error control map to prevent boundary leakage. We tested the proposed approach with 10 datasets and compared it with the latest techniques with random walks and priors. The experiments suggest that this method gives promising results for cochlea segmentation.

Experimental Mapping and Benchmarking of Magnetic Field Codes on the LHD Ion Accelerator

NASA Astrophysics Data System (ADS)

Chitarin, G.; Agostinetti, P.; Gallo, A.; Marconato, N.; Nakano, H.; Serianni, G.; Takeiri, Y.; Tsumori, K.

2011-09-01

For the validation of the numerical models used for the design of the Neutral Beam Test Facility for ITER in Padua [1], an experimental benchmark against a full-size device has been sought. The LHD BL2 injector [2] has been chosen as a first benchmark, because the BL2 Negative Ion Source and Beam Accelerator are geometrically similar to SPIDER, even though BL2 does not include current bars and ferromagnetic materials. A comprehensive 3D magnetic field model of the LHD BL2 device has been developed based on the same assumptions used for SPIDER. In parallel, a detailed experimental magnetic map of the BL2 device has been obtained using a suitably designed 3D adjustable structure for the fine positioning of the magnetic sensors inside 27 of the 770 beamlet apertures. The calculated values have been compared to the experimental data. The work has confirmed the quality of the numerical model, and has also provided useful information on the magnetic non-uniformities due to the edge effects and to the tolerance on permanent magnet remanence.

Experimental Mapping and Benchmarking of Magnetic Field Codes on the LHD Ion Accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chitarin, G.; University of Padova, Dept. of Management and Engineering, strad. S. Nicola, 36100 Vicenza; Agostinetti, P.

2011-09-26

For the validation of the numerical models used for the design of the Neutral Beam Test Facility for ITER in Padua [1], an experimental benchmark against a full-size device has been sought. The LHD BL2 injector [2] has been chosen as a first benchmark, because the BL2 Negative Ion Source and Beam Accelerator are geometrically similar to SPIDER, even though BL2 does not include current bars and ferromagnetic materials. A comprehensive 3D magnetic field model of the LHD BL2 device has been developed based on the same assumptions used for SPIDER. In parallel, a detailed experimental magnetic map of themore » BL2 device has been obtained using a suitably designed 3D adjustable structure for the fine positioning of the magnetic sensors inside 27 of the 770 beamlet apertures. The calculated values have been compared to the experimental data. The work has confirmed the quality of the numerical model, and has also provided useful information on the magnetic non-uniformities due to the edge effects and to the tolerance on permanent magnet remanence.« less

Exactly solved mixed spin-(1,1/2) Ising-Heisenberg diamond chain with a single-ion anisotropy

NASA Astrophysics Data System (ADS)

Lisnyi, Bohdan; Strečka, Jozef

2015-03-01

The mixed spin-(1,1/2) Ising-Heisenberg diamond chain with a single-ion anisotropy is exactly solved through the generalized decoration-iteration transformation and the transfer-matrix method. The decoration-iteration transformation is first used for establishing a rigorous mapping equivalence with the corresponding spin-1 Blume-Emery-Griffiths chain, which is subsequently exactly treated within the transfer-matrix technique. Apart from three classical ground states the model exhibits three striking quantum ground states in which a singlet-dimer state of the interstitial Heisenberg spins is accompanied either with a frustrated state or a polarized state or a non-magnetic state of the nodal Ising spins. It is evidenced that two magnetization plateaus at zero and/or one-half of the saturation magnetization may appear in low-temperature magnetization curves. The specific heat may display remarkable temperature dependences with up to three and four distinct round maxima in a zero and non-zero magnetic field, respectively.

Rapid water and lipid imaging with T2 mapping using a radial IDEAL-GRASE technique.

PubMed

Li, Zhiqiang; Graff, Christian; Gmitro, Arthur F; Squire, Scott W; Bilgin, Ali; Outwater, Eric K; Altbach, Maria I

2009-06-01

Three-point Dixon methods have been investigated as a means to generate water and fat images without the effects of field inhomogeneities. Recently, an iterative algorithm (IDEAL, iterative decomposition of water and fat with echo asymmetry and least squares estimation) was combined with a gradient and spin-echo acquisition strategy (IDEAL-GRASE) to provide a time-efficient method for lipid-water imaging with correction for the effects of field inhomogeneities. The method presented in this work combines IDEAL-GRASE with radial data acquisition. Radial data sampling offers robustness to motion over Cartesian trajectories as well as the possibility of generating high-resolution T(2) maps in addition to the water and fat images. The radial IDEAL-GRASE technique is demonstrated in phantoms and in vivo for various applications including abdominal, pelvic, and cardiac imaging.

Multidirectional hybrid algorithm for the split common fixed point problem and application to the split common null point problem.

PubMed

Li, Xia; Guo, Meifang; Su, Yongfu

2016-01-01

In this article, a new multidirectional monotone hybrid iteration algorithm for finding a solution to the split common fixed point problem is presented for two countable families of quasi-nonexpansive mappings in Banach spaces. Strong convergence theorems are proved. The application of the result is to consider the split common null point problem of maximal monotone operators in Banach spaces. Strong convergence theorems for finding a solution of the split common null point problem are derived. This iteration algorithm can accelerate the convergence speed of iterative sequence. The results of this paper improve and extend the recent results of Takahashi and Yao (Fixed Point Theory Appl 2015:87, 2015) and many others .

High-Level Performance Modeling of SAR Systems

NASA Technical Reports Server (NTRS)

Chen, Curtis

2006-01-01

SAUSAGE (Still Another Utility for SAR Analysis that s General and Extensible) is a computer program for modeling (see figure) the performance of synthetic- aperture radar (SAR) or interferometric synthetic-aperture radar (InSAR or IFSAR) systems. The user is assumed to be familiar with the basic principles of SAR imaging and interferometry. Given design parameters (e.g., altitude, power, and bandwidth) that characterize a radar system, the software predicts various performance metrics (e.g., signal-to-noise ratio and resolution). SAUSAGE is intended to be a general software tool for quick, high-level evaluation of radar designs; it is not meant to capture all the subtleties, nuances, and particulars of specific systems. SAUSAGE was written to facilitate the exploration of engineering tradeoffs within the multidimensional space of design parameters. Typically, this space is examined through an iterative process of adjusting the values of the design parameters and examining the effects of the adjustments on the overall performance of the system at each iteration. The software is designed to be modular and extensible to enable consideration of a variety of operating modes and antenna beam patterns, including, for example, strip-map and spotlight SAR acquisitions, polarimetry, burst modes, and squinted geometries.

Synchronous, Alternating, and Phase-Locked Stridulation by a Tropical Katydid

NASA Astrophysics Data System (ADS)

Sismondo, Enrico

1990-07-01

In the field the chirps of neighboring Mecopoda sp. (Orthoptera, Tettigoniidae, and Mecopodinae) males are normally synchronized, but between more distant individuals the chirps are either synchronous or regularly alternating. The phase response to single-stimulus chirps depends on both the phase and the intensity of the stimulus. Iteration of the Poincare map of the phase response predicts a variety of phase-locked synchronization regimes, including period-doubling bifurcations, in close agreement with experimental observations. The versatile acoustic behavior of Mecopoda encompasses most of the phenomena found in other synchronizing insects and thus provides a general model of insect synchronization behavior.

Iterative h-minima-based marker-controlled watershed for cell nucleus segmentation.

PubMed

Koyuncu, Can Fahrettin; Akhan, Ece; Ersahin, Tulin; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2016-04-01

Automated microscopy imaging systems facilitate high-throughput screening in molecular cellular biology research. The first step of these systems is cell nucleus segmentation, which has a great impact on the success of the overall system. The marker-controlled watershed is a technique commonly used by the previous studies for nucleus segmentation. These studies define their markers finding regional minima on the intensity/gradient and/or distance transform maps. They typically use the h-minima transform beforehand to suppress noise on these maps. The selection of the h value is critical; unnecessarily small values do not sufficiently suppress the noise, resulting in false and oversegmented markers, and unnecessarily large ones suppress too many pixels, causing missing and undersegmented markers. Because cell nuclei show different characteristics within an image, the same h value may not work to define correct markers for all the nuclei. To address this issue, in this work, we propose a new watershed algorithm that iteratively identifies its markers, considering a set of different h values. In each iteration, the proposed algorithm defines a set of candidates using a particular h value and selects the markers from those candidates provided that they fulfill the size requirement. Working with widefield fluorescence microscopy images, our experiments reveal that the use of multiple h values in our iterative algorithm leads to better segmentation results, compared to its counterparts. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Quantum state matching of qubits via measurement-induced nonlinear transformations

NASA Astrophysics Data System (ADS)

Kálmán, Orsolya; Kiss, Tamás

2018-03-01

We consider the task of deciding whether an unknown qubit state falls in a prescribed neighborhood of a reference state. We assume that several copies of the unknown state are given and apply a unitary operation pairwise on them combined with a postselection scheme conditioned on the measurement result obtained on one of the qubits of the pair. The resulting transformation is a deterministic, nonlinear, chaotic map in the Hilbert space. We derive a class of these transformations capable of orthogonalizing nonorthogonal qubit states after a few iterations. These nonlinear maps orthogonalize states which correspond to the two different convergence regions of the nonlinear map. Based on the analysis of the border (the so-called Julia set) between the two regions of convergence, we show that it is always possible to find a map capable of deciding whether an unknown state is within a neighborhood of fixed radius around a desired quantum state. We analyze which one- and two-qubit operations would physically realize the scheme. It is possible to find a single two-qubit unitary gate for each map or, alternatively, a universal special two-qubit gate together with single-qubit gates in order to carry out the task. We note that it is enough to have a single physical realization of the required gates due to the iterative nature of the scheme.

Iterative Demodulation and Decoding of Non-Square QAM

NASA Technical Reports Server (NTRS)

Li, Lifang; Divsalar, Dariush; Dolinar, Samuel

2004-01-01

It has been shown that a non-square (NS) 2(sup 2n+1)-ary (where n is a positive integer) quadrature amplitude modulation [(NS)2(sup 2n+1)-QAM] has inherent memory that can be exploited to obtain coding gains. Moreover, it should not be necessary to build new hardware to realize these gains. The present scheme is a product of theoretical calculations directed toward reducing the computational complexity of decoding coded 2(sup 2n+1)-QAM. In the general case of 2(sup 2n+1)-QAM, the signal constellation is not square and it is impossible to have independent in-phase (I) and quadrature-phase (Q) mapping and demapping. However, independent I and Q mapping and demapping are desirable for reducing the complexity of computing the log likelihood ratio (LLR) between a bit and a received symbol (such computations are essential operations in iterative decoding). This is because in modulation schemes that include independent I and Q mapping and demapping, each bit of a signal point is involved in only one-dimensional mapping and demapping. As a result, the computation of the LLR is equivalent to that of a one-dimensional pulse amplitude modulation (PAM) system. Therefore, it is desirable to find a signal constellation that enables independent I and Q mapping and demapping for 2(sup 2n+1)-QAM.

Computer-aided diagnosis of early knee osteoarthritis based on MRI T2 mapping.

PubMed

Wu, Yixiao; Yang, Ran; Jia, Sen; Li, Zhanjun; Zhou, Zhiyang; Lou, Ting

2014-01-01

This work was aimed at studying the method of computer-aided diagnosis of early knee OA (OA: osteoarthritis). Based on the technique of MRI (MRI: Magnetic Resonance Imaging) T2 Mapping, through computer image processing, feature extraction, calculation and analysis via constructing a classifier, an effective computer-aided diagnosis method for knee OA was created to assist doctors in their accurate, timely and convenient detection of potential risk of OA. In order to evaluate this method, a total of 1380 data from the MRI images of 46 samples of knee joints were collected. These data were then modeled through linear regression on an offline general platform by the use of the ImageJ software, and a map of the physical parameter T2 was reconstructed. After the image processing, the T2 values of ten regions in the WORMS (WORMS: Whole-organ Magnetic Resonance Imaging Score) areas of the articular cartilage were extracted to be used as the eigenvalues in data mining. Then,a RBF (RBF: Radical Basis Function) network classifier was built to classify and identify the collected data. The classifier exhibited a final identification accuracy of 75%, indicating a good result of assisting diagnosis. Since the knee OA classifier constituted by a weights-directly-determined RBF neural network didn't require any iteration, our results demonstrated that the optimal weights, appropriate center and variance could be yielded through simple procedures. Furthermore, the accuracy for both the training samples and the testing samples from the normal group could reach 100%. Finally, the classifier was superior both in time efficiency and classification performance to the frequently used classifiers based on iterative learning. Thus it was suitable to be used as an aid to computer-aided diagnosis of early knee OA.

A novel structure-based multimode QSAR method affords predictive models for phosphodiesterase inhibitors.

PubMed

Dong, Xialan; Ebalunode, Jerry O; Cho, Sung Jin; Zheng, Weifan

2010-02-22

Quantitative structure-activity relationship (QSAR) methods aim to build quantitatively predictive models for the discovery of new molecules. It has been widely used in medicinal chemistry for drug discovery. Many QSAR techniques have been developed since Hansch's seminal work, and more are still being developed. Motivated by Hopfinger's receptor-dependent QSAR (RD-QSAR) formalism and the Lukacova-Balaz scheme to treat multimode issues, we have initiated studies that focus on a structure-based multimode QSAR (SBMM QSAR) method, where the structure of the target protein is used in characterizing the ligand, and the multimode issue of ligand binding is systematically treated with a modified Lukacova-Balaz scheme. All ligand molecules are first docked to the target binding pocket to obtain a set of aligned ligand poses. A structure-based pharmacophore concept is adopted to characterize the binding pocket. Specifically, we represent the binding pocket as a geometric grid labeled by pharmacophoric features. Each pose of the ligand is also represented as a labeled grid, where each grid point is labeled according to the atom types of nearby ligand atoms. These labeled grids or three-dimensional (3D) maps (both the receptor map (R-map) and the ligand map (L-map)) are compared to each other to derive descriptors for each pose of the ligand, resulting in a multimode structure-activity relationship (SAR) table. Iterative partial least-squares (PLS) is employed to build the QSAR models. When we applied this method to analyze PDE-4 inhibitors, predictive models have been developed, obtaining models with excellent training correlation (r(2) = 0.65-0.66), as well as test correlation (R(2) = 0.64-0.65). A comparative analysis with 4 other QSAR techniques demonstrates that this new method affords better models, in terms of the prediction power for the test set.

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2009-01-01

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

Deformable Image Registration based on Similarity-Steered CNN Regression.

PubMed

Cao, Xiaohuan; Yang, Jianhua; Zhang, Jun; Nie, Dong; Kim, Min-Jeong; Wang, Qian; Shen, Dinggang

2017-09-01

Existing deformable registration methods require exhaustively iterative optimization, along with careful parameter tuning, to estimate the deformation field between images. Although some learning-based methods have been proposed for initiating deformation estimation, they are often template-specific and not flexible in practical use. In this paper, we propose a convolutional neural network (CNN) based regression model to directly learn the complex mapping from the input image pair (i.e., a pair of template and subject) to their corresponding deformation field. Specifically, our CNN architecture is designed in a patch-based manner to learn the complex mapping from the input patch pairs to their respective deformation field. First, the equalized active-points guided sampling strategy is introduced to facilitate accurate CNN model learning upon a limited image dataset. Then, the similarity-steered CNN architecture is designed, where we propose to add the auxiliary contextual cue, i.e., the similarity between input patches, to more directly guide the learning process. Experiments on different brain image datasets demonstrate promising registration performance based on our CNN model. Furthermore, it is found that the trained CNN model from one dataset can be successfully transferred to another dataset, although brain appearances across datasets are quite variable.

Registration of terrestrial mobile laser data on 2D or 3D geographic database by use of a non-rigid ICP approach.

NASA Astrophysics Data System (ADS)

Monnier, F.; Vallet, B.; Paparoditis, N.; Papelard, J.-P.; David, N.

2013-10-01

This article presents a generic and efficient method to register terrestrial mobile data with imperfect location on a geographic database with better overall accuracy but less details. The registration method proposed in this paper is based on a semi-rigid point to plane ICP ("Iterative Closest Point"). The main applications of such registration is to improve existing geographic databases, particularly in terms of accuracy, level of detail and diversity of represented objects. Other applications include fine geometric modelling and fine façade texturing, object extraction such as trees, poles, road signs marks, facilities, vehicles, etc. The geopositionning system of mobile mapping systems is affected by GPS masks that are only partially corrected by an Inertial Navigation System (INS) which can cause an important drift. As this drift varies non-linearly, but slowly in time, it will be modelled by a translation defined as a piecewise linear function of time which variation over time will be minimized (rigidity term). For each iteration of the ICP, the drift is estimated in order to minimise the distance between laser points and planar model primitives (data attachment term). The method has been tested on real data (a scan of the city of Paris of 3.6 million laser points registered on a 3D model of approximately 71,400 triangles).

Composing chaotic music from the letter m

NASA Astrophysics Data System (ADS)

Sotiropoulos, Anastasios D.

Chaotic music is composed from a proposed iterative map depicting the letter m, relating the pitch, duration and loudness of successive steps. Each of the two curves of the letter m is based on the classical logistic map. Thus, the generating map is xn+1 = r xn(1/2 - xn) for xn between 0 and 1/2 defining the first curve, and xn+1 = r (xn - 1/2)(1 - xn) for xn between 1/2 and 1 representing the second curve. The parameter r which determines the height(s) of the letter m varies from 2 to 16, the latter value ensuring fully developed chaotic solutions for the whole letter m; r = 8 yielding full chaotic solutions only for its first curve. The m-model yields fixed points, bifurcation points and chaotic regions for each separate curve, as well as values of the parameter r greater than 8 which produce inter-fixed points, inter-bifurcation points and inter-chaotic regions from the interplay of the two curves. Based on this, music is composed from mapping the m- recurrence model solutions onto actual notes. The resulting musical score strongly depends on the sequence of notes chosen by the composer to define the musical range corresponding to the range of the chaotic mathematical solutions x from 0 to 1. Here, two musical ranges are used; one is the middle chromatic scale and the other is the seven- octaves range. At the composer's will and, for aesthetics, within the same composition, notes can be the outcome of different values of r and/or shifted in any octave. Compositions with endings of non-repeating note patterns result from values of r in the m-model that do not produce bifurcations. Scores of chaotic music composed from the m-model and the classical logistic model are presented.

Physics and technology in the ion-cyclotron range of frequency on Tore Supra and TITAN test facility: implication for ITER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Litaudon, X; Bernard, J. M.; Colas, L.

2013-01-01

To support the design of an ITER ion-cyclotron range of frequency heating (ICRH) system and to mitigate risks of operation in ITER, CEA has initiated an ambitious Research & Development program accompanied by experiments on Tore Supra or test-bed facility together with a significant modelling effort. The paper summarizes the recent results in the following areas: Comprehensive characterization (experiments and modelling) of a new Faraday screen concept tested on the Tore Supra antenna. A new model is developed for calculating the ICRH sheath rectification at the antenna vicinity. The model is applied to calculate the local heat flux on Toremore » Supra and ITER ICRH antennas. Full-wave modelling of ITER ICRH heating and current drive scenarios with the EVE code. With 20 MW of power, a current of 400 kA could be driven on axis in the DT scenario. Comparison between DT and DT(3He) scenario is given for heating and current drive efficiencies. First operation of CW test-bed facility, TITAN, designed for ITER ICRH components testing and could host up to a quarter of an ITER antenna. R&D of high permittivity materials to improve load of test facilities to better simulate ITER plasma antenna loading conditions.« less

Intelligent process mapping through systematic improvement of heuristics

NASA Technical Reports Server (NTRS)

Ieumwananonthachai, Arthur; Aizawa, Akiko N.; Schwartz, Steven R.; Wah, Benjamin W.; Yan, Jerry C.

1992-01-01

The present system for automatic learning/evaluation of novel heuristic methods applicable to the mapping of communication-process sets on a computer network has its basis in the testing of a population of competing heuristic methods within a fixed time-constraint. The TEACHER 4.1 prototype learning system implemented or learning new postgame analysis heuristic methods iteratively generates and refines the mappings of a set of communicating processes on a computer network. A systematic exploration of the space of possible heuristic methods is shown to promise significant improvement.

Destruction of the Last Good Surface in Diii-D Usn with ELMs and C-Coils Shot 115467 due to ELMs and C-Coils Using Maps

NASA Astrophysics Data System (ADS)

Sherrow, K.; Punjabi, A.; Ali, H.

2004-11-01

Unperturbed magnetic topology of DIII-D shot 115467 is described by the symmetric simple map (SSM) with parameter k=0.2623, then q_edge=6.48 (as in shot 115467) if six iterations of SSM are taken to be equivalent to single toroidal circuit of DIII-D [1]. Low mn map (LM) calculates effects of m=1, n=+1,-1 modes on trajectories of field lines. We use LM with amplitude ɛ=6X10-4 (value expected in modern divertor tokamaks) to describe effects of ELMs. With ELMs, last good surface passes through x=0, y=0.98375. We use dipole map (DM) to represent effects of C-coils. We apply DM after each iteration of SSM. We use s=1.0021, x_dipole=1.5617, y_dipole= 0 for DIII-D shot 115467 [1]. We study changes in the last good surface and its destruction as function of I_C-coil with fixed ɛ = 6X10-4. This work is supported by NASA SHARP program and DE-FG02-02ER54673. [1] H. Ali, A. Punjabi, A. Boozer, and T. Evans, 31st EPS Plasma Phys Mtg, London, UK, June 29, 2004, paper P2-172.

A FAST ITERATIVE METHOD FOR SOLVING THE EIKONAL EQUATION ON TRIANGULATED SURFACES*

PubMed Central

Fu, Zhisong; Jeong, Won-Ki; Pan, Yongsheng; Kirby, Robert M.; Whitaker, Ross T.

2012-01-01

This paper presents an efficient, fine-grained parallel algorithm for solving the Eikonal equation on triangular meshes. The Eikonal equation, and the broader class of Hamilton–Jacobi equations to which it belongs, have a wide range of applications from geometric optics and seismology to biological modeling and analysis of geometry and images. The ability to solve such equations accurately and efficiently provides new capabilities for exploring and visualizing parameter spaces and for solving inverse problems that rely on such equations in the forward model. Efficient solvers on state-of-the-art, parallel architectures require new algorithms that are not, in many cases, optimal, but are better suited to synchronous updates of the solution. In previous work [W. K. Jeong and R. T. Whitaker, SIAM J. Sci. Comput., 30 (2008), pp. 2512–2534], the authors proposed the fast iterative method (FIM) to efficiently solve the Eikonal equation on regular grids. In this paper we extend the fast iterative method to solve Eikonal equations efficiently on triangulated domains on the CPU and on parallel architectures, including graphics processors. We propose a new local update scheme that provides solutions of first-order accuracy for both architectures. We also propose a novel triangle-based update scheme and its corresponding data structure for efficient irregular data mapping to parallel single-instruction multiple-data (SIMD) processors. We provide detailed descriptions of the implementations on a single CPU, a multicore CPU with shared memory, and SIMD architectures with comparative results against state-of-the-art Eikonal solvers. PMID:22641200

Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

Statistically based iterative approaches for image reconstruction have gained much attention in medical imaging. An accurate system matrix that defines the mapping from the image space to the data space is the key to high-resolution image reconstruction. However, an accurate system matrix is often associated with high computational cost and huge storage requirement. Here we present a method to address this problem by using sparse matrix factorization and parallel computing on a graphic processing unit (GPU).We factor the accurate system matrix into three sparse matrices: a sinogram blurring matrix, a geometric projection matrix, and an image blurring matrix. The sinogram blurring matrix models the detector response. The geometric projection matrix is based on a simple line integral model. The image blurring matrix is to compensate for the line-of-response (LOR) degradation due to the simplified geometric projection matrix. The geometric projection matrix is precomputed, while the sinogram and image blurring matrices are estimated by minimizing the difference between the factored system matrix and the original system matrix. The resulting factored system matrix has much less number of nonzero elements than the original system matrix and thus substantially reduces the storage and computation cost. The smaller size also allows an efficient implement of the forward and back projectors on GPUs, which have limited amount of memory. Our simulation studies show that the proposed method can dramatically reduce the computation cost of high-resolution iterative image reconstruction. The proposed technique is applicable to image reconstruction for different imaging modalities, including x-ray CT, PET, and SPECT.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca

Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less

Low dose dynamic myocardial CT perfusion using advanced iterative reconstruction

NASA Astrophysics Data System (ADS)

Eck, Brendan L.; Fahmi, Rachid; Fuqua, Christopher; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.

2015-03-01

Dynamic myocardial CT perfusion (CTP) can provide quantitative functional information for the assessment of coronary artery disease. However, x-ray dose in dynamic CTP is high, typically from 10mSv to >20mSv. We compared the dose reduction potential of advanced iterative reconstruction, Iterative Model Reconstruction (IMR, Philips Healthcare, Cleveland, Ohio) to hybrid iterative reconstruction (iDose4) and filtered back projection (FBP). Dynamic CTP scans were obtained using a porcine model with balloon-induced ischemia in the left anterior descending coronary artery to prescribed fractional flow reserve values. High dose dynamic CTP scans were acquired at 100kVp/100mAs with effective dose of 23mSv. Low dose scans at 75mAs, 50mAs, and 25mAs were simulated by adding x-ray quantum noise and detector electronic noise to the projection space data. Images were reconstructed with FBP, iDose4, and IMR at each dose level. Image quality in static CTP images was assessed by SNR and CNR. Blood flow was obtained using a dynamic CTP analysis pipeline and blood flow image quality was assessed using flow-SNR and flow-CNR. IMR showed highest static image quality according to SNR and CNR. Blood flow in FBP was increasingly over-estimated at reduced dose. Flow was more consistent for iDose4 from 100mAs to 50mAs, but was over-estimated at 25mAs. IMR was most consistent from 100mAs to 25mAs. Static images and flow maps for 100mAs FBP, 50mAs iDose4, and 25mAs IMR showed comparable, clear ischemia, CNR, and flow-CNR values. These results suggest that IMR can enable dynamic CTP at significantly reduced dose, at 5.8mSv or 25% of the comparable 23mSv FBP protocol.

Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.

PubMed

Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2015-11-01

The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.

A system of nonlinear set valued variational inclusions.

PubMed

Tang, Yong-Kun; Chang, Shih-Sen; Salahuddin, Salahuddin

2014-01-01

In this paper, we studied the existence theorems and techniques for finding the solutions of a system of nonlinear set valued variational inclusions in Hilbert spaces. To overcome the difficulties, due to the presence of a proper convex lower semicontinuous function ϕ and a mapping g which appeared in the considered problems, we have used the resolvent operator technique to suggest an iterative algorithm to compute approximate solutions of the system of nonlinear set valued variational inclusions. The convergence of the iterative sequences generated by algorithm is also proved. 49J40; 47H06.

Bouncing droplets on a billiard table.

PubMed

Shirokoff, David

2013-03-01

In a set of experiments, Couder et al. demonstrate that an oscillating fluid bed may propagate a bouncing droplet through the guidance of the surface waves. I present a dynamical systems model, in the form of an iterative map, for a droplet on an oscillating bath. I examine the droplet bifurcation from bouncing to walking, and prescribe general requirements for the surface wave to support stable walking states. I show that in addition to walking, there is a region of large forcing that may support the chaotic motion of the droplet. Using the map, I then investigate the droplet trajectories in a square (billiard ball) domain. I show that in large domains, the long time trajectories are either non-periodic dense curves or approach a quasiperiodic orbit. In contrast, in small domains, at low forcing, trajectories tend to approach an array of circular attracting sets. As the forcing increases, the attracting sets break down and the droplet travels throughout space.

Bridging the Nomothetic and Idiographic Approaches to the Analysis of Clinical Data.

PubMed

Beltz, Adriene M; Wright, Aidan G C; Sprague, Briana N; Molenaar, Peter C M

2016-08-01

The nomothetic approach (i.e., the study of interindividual variation) dominates analyses of clinical data, even though its assumption of homogeneity across people and time is often violated. The idiographic approach (i.e., the study of intraindividual variation) is best suited for analyses of heterogeneous clinical data, but its person-specific methods and results have been criticized as unwieldy. Group iterative multiple model estimation (GIMME) combines the assets of the nomothetic and idiographic approaches by creating person-specific maps that contain a group-level structure. The maps show how intensively measured variables predict and are predicted by each other at different time scales. In this article, GIMME is introduced conceptually and mathematically, and then applied to an empirical data set containing the negative affect, detachment, disinhibition, and hostility composite ratings from the daily diaries of 25 individuals with personality pathology. Results are discussed with the aim of elucidating GIMME's potential for clinical research and practice.

Robust synchronization in fiber laser arrays.

PubMed

Peles, Slaven; Rogers, Jeffrey L; Wiesenfeld, Kurt

2006-02-01

Synchronization of coupled fiber lasers has been reported in recent experiments [Bruesselbach, Opt. Lett. 30, 1339 (2005); Minden, Proc. SPIE 5335, 89 (2004)]. While these results may lead to dramatic advances in laser technology, the mechanism by which these lasers synchronize is not understood. We analyze a recently proposed [Rogers, IEEE J. Quantum Electron. 41, 767 (2005)] iterated map model of fiber laser arrays to explore this phenomenon. In particular, we look at synchronous solutions of the maps when the gain fields are constant. Determining the stability of these solutions is analytically tractable for a number of different coupling schemes. We find that in the most symmetric physical configurations the most symmetric solution is either unstable or stable over insufficient parameter range to be practical. In contrast, a lower symmetry configuration yields surprisingly robust coherence. This coherence persists beyond the pumping threshold for which the gain fields become time dependent.

Assortative Mating: Encounter-Network Topology and the Evolution of Attractiveness

PubMed Central

Dipple, S.; Jia, T.; Caraco, T.; Korniss, G.; Szymanski, B. K.

2017-01-01

We model a social-encounter network where linked nodes match for reproduction in a manner depending probabilistically on each node’s attractiveness. The developed model reveals that increasing either the network’s mean degree or the “choosiness” exercised during pair formation increases the strength of positive assortative mating. That is, we note that attractiveness is correlated among mated nodes. Their total number also increases with mean degree and selectivity during pair formation. By iterating over the model’s mapping of parents onto offspring across generations, we study the evolution of attractiveness. Selection mediated by exclusion from reproduction increases mean attractiveness, but is rapidly balanced by skew in the offspring distribution of highly attractive mated pairs. PMID:28345625

On the dual equivalence of the self-dual and topologically massive /B∧F models coupled to dynamical fermionic matter

NASA Astrophysics Data System (ADS)

Menezes, R.; Nascimento, J. R. S.; Ribeiro, R. F.; Wotzasek, C.

2002-06-01

We study the equivalence between the /B∧F self-dual (SDB∧F) and the /B∧F topologically massive (TMB∧F) models including the coupling to dynamical, U(1) charged fermionic matter. This is done through an iterative procedure of gauge embedding that produces the dual mapping. In the interactive cases, the minimal coupling adopted for both vector and tensor fields in the self-dual representation is transformed into a non-minimal magnetic like coupling in the topologically massive representation but with the currents swapped. It is known that to establish this equivalence a current-current interaction term is needed to render the matter sector unchanged. We show that both terms arise naturally from the embedding procedure.

An Exploratory Study of Cost Engineering in Axiomatic Design: Creation of the Cost Model Based on an FR-DP Map

NASA Technical Reports Server (NTRS)

Lee, Taesik; Jeziorek, Peter

2004-01-01

Large complex projects cost large sums of money throughout their life cycle for a variety of reasons and causes. For such large programs, the credible estimation of the project cost, a quick assessment of the cost of making changes, and the management of the project budget with effective cost reduction determine the viability of the project. Cost engineering that deals with these issues requires a rigorous method and systematic processes. This paper introduces a logical framework to a&e effective cost engineering. The framework is built upon Axiomatic Design process. The structure in the Axiomatic Design process provides a good foundation to closely tie engineering design and cost information together. The cost framework presented in this paper is a systematic link between the functional domain (FRs), physical domain (DPs), cost domain (CUs), and a task/process-based model. The FR-DP map relates a system s functional requirements to design solutions across all levels and branches of the decomposition hierarchy. DPs are mapped into CUs, which provides a means to estimate the cost of design solutions - DPs - from the cost of the physical entities in the system - CUs. The task/process model describes the iterative process ot-developing each of the CUs, and is used to estimate the cost of CUs. By linking the four domains, this framework provides a superior traceability from requirements to cost information.

Atlas Based Segmentation and Mapping of Organs at Risk from Planning CT for the Development of Voxel-Wise Predictive Models of Toxicity in Prostate Radiotherapy

NASA Astrophysics Data System (ADS)

Acosta, Oscar; Dowling, Jason; Cazoulat, Guillaume; Simon, Antoine; Salvado, Olivier; de Crevoisier, Renaud; Haigron, Pascal

The prediction of toxicity is crucial to managing prostate cancer radiotherapy (RT). This prediction is classically organ wise and based on the dose volume histograms (DVH) computed during the planning step, and using for example the mathematical Lyman Normal Tissue Complication Probability (NTCP) model. However, these models lack spatial accuracy, do not take into account deformations and may be inappropiate to explain toxicity events related with the distribution of the delivered dose. Producing voxel wise statistical models of toxicity might help to explain the risks linked to the dose spatial distribution but is challenging due to the difficulties lying on the mapping of organs and dose in a common template. In this paper we investigate the use of atlas based methods to perform the non-rigid mapping and segmentation of the individuals' organs at risk (OAR) from CT scans. To build a labeled atlas, 19 CT scans were selected from a population of patients treated for prostate cancer by radiotherapy. The prostate and the OAR (Rectum, Bladder, Bones) were then manually delineated by an expert and constituted the training data. After a number of affine and non rigid registration iterations, an average image (template) representing the whole population was obtained. The amount of consensus between labels was used to generate probabilistic maps for each organ. We validated the accuracy of the approach by segmenting the organs using the training data in a leave one out scheme. The agreement between the volumes after deformable registration and the manually segmented organs was on average above 60% for the organs at risk. The proposed methodology provides a way to map the organs from a whole population on a single template and sets the stage to perform further voxel wise analysis. With this method new and accurate predictive models of toxicity will be built.

Page layout analysis and classification for complex scanned documents

NASA Astrophysics Data System (ADS)

Erkilinc, M. Sezer; Jaber, Mustafa; Saber, Eli; Bauer, Peter; Depalov, Dejan

2011-09-01

A framework for region/zone classification in color and gray-scale scanned documents is proposed in this paper. The algorithm includes modules for extracting text, photo, and strong edge/line regions. Firstly, a text detection module which is based on wavelet analysis and Run Length Encoding (RLE) technique is employed. Local and global energy maps in high frequency bands of the wavelet domain are generated and used as initial text maps. Further analysis using RLE yields a final text map. The second module is developed to detect image/photo and pictorial regions in the input document. A block-based classifier using basis vector projections is employed to identify photo candidate regions. Then, a final photo map is obtained by applying probabilistic model based on Markov random field (MRF) based maximum a posteriori (MAP) optimization with iterated conditional mode (ICM). The final module detects lines and strong edges using Hough transform and edge-linkages analysis, respectively. The text, photo, and strong edge/line maps are combined to generate a page layout classification of the scanned target document. Experimental results and objective evaluation show that the proposed technique has a very effective performance on variety of simple and complex scanned document types obtained from MediaTeam Oulu document database. The proposed page layout classifier can be used in systems for efficient document storage, content based document retrieval, optical character recognition, mobile phone imagery, and augmented reality.

Competencies "plus": the nature of written comments on internal medicine residents' evaluation forms.

PubMed

Ginsburg, Shiphra; Gold, Wayne; Cavalcanti, Rodrigo B; Kurabi, Bochra; McDonald-Blumer, Heather

2011-10-01

Comments on residents' in-training evaluation reports (ITERs) may be more useful than scores in identifying trainees in difficulty. However, little is known about the nature of comments written by internal medicine faculty on residents' ITERs. Comments on 1,770 ITERs (from 180 residents in postgraduate years 1-3) were analyzed using constructivist grounded theory beginning with an existing framework. Ninety-three percent of ITERs contained comments, which were frequently easy to map onto traditional competencies, such as knowledge base (n = 1,075 comments) to the CanMEDs Medical Expert role. Many comments, however, could be linked to several overlapping competencies. Also common were comments completely unrelated to competencies, for instance, the resident's impact on staff (813), or personality issues (450). Residents' "trajectory" was a major theme (performance in relation to expected norms [494], improvement seen [286], or future predictions [286]). Faculty's assessments of residents are underpinned by factors related and unrelated to traditional competencies. Future evaluations should attempt to capture these holistic, integrated impressions.

Matrix completion-based reconstruction for undersampled magnetic resonance fingerprinting data.

PubMed

Doneva, Mariya; Amthor, Thomas; Koken, Peter; Sommer, Karsten; Börnert, Peter

2017-09-01

An iterative reconstruction method for undersampled magnetic resonance fingerprinting data is presented. The method performs the reconstruction entirely in k-space and is related to low rank matrix completion methods. A low dimensional data subspace is estimated from a small number of k-space locations fully sampled in the temporal direction and used to reconstruct the missing k-space samples before MRF dictionary matching. Performing the iterations in k-space eliminates the need for applying a forward and an inverse Fourier transform in each iteration required in previously proposed iterative reconstruction methods for undersampled MRF data. A projection onto the low dimensional data subspace is performed as a matrix multiplication instead of a singular value thresholding typically used in low rank matrix completion, further reducing the computational complexity of the reconstruction. The method is theoretically described and validated in phantom and in-vivo experiments. The quality of the parameter maps can be significantly improved compared to direct matching on undersampled data. Copyright © 2017 Elsevier Inc. All rights reserved.

Gamut mapping in a high-dynamic-range color space

NASA Astrophysics Data System (ADS)

Preiss, Jens; Fairchild, Mark D.; Ferwerda, James A.; Urban, Philipp

2014-01-01

In this paper, we present a novel approach of tone mapping as gamut mapping in a high-dynamic-range (HDR) color space. High- and low-dynamic-range (LDR) images as well as device gamut boundaries can simultaneously be represented within such a color space. This enables a unified transformation of the HDR image into the gamut of an output device (in this paper called HDR gamut mapping). An additional aim of this paper is to investigate the suitability of a specific HDR color space to serve as a working color space for the proposed HDR gamut mapping. For the HDR gamut mapping, we use a recent approach that iteratively minimizes an image-difference metric subject to in-gamut images. A psychophysical experiment on an HDR display shows that the standard reproduction workflow of two subsequent transformations - tone mapping and then gamut mapping - may be improved by HDR gamut mapping.

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

Continuous evaluation of dairy cattle with a random regression test-day model requires a fast solving method and algorithm. A new computing technique feasible in Jacobi and conjugate gradient based iterative methods using iteration on data is presented. In the new computing technique, the calculations in multiplication of a vector by a matrix were recorded to three steps instead of the commonly used two steps. The three-step method was implemented in a general mixed linear model program that used preconditioned conjugate gradient iteration. Performance of this program in comparison to other general solving programs was assessed via estimation of breeding values using univariate, multivariate, and random regression test-day models. Central processing unit time per iteration with the new three-step technique was, at best, one-third that needed with the old technique. Performance was best with the test-day model, which was the largest and most complex model used. The new program did well in comparison to other general software. Programs keeping the mixed model equations in random access memory required at least 20 and 435% more time to solve the univariate and multivariate animal models, respectively. Computations of the second best iteration on data took approximately three and five times longer for the animal and test-day models, respectively, than did the new program. Good performance was due to fast computing time per iteration and quick convergence to the final solutions. Use of preconditioned conjugate gradient based methods in solving large breeding value problems is supported by our findings.

Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica.

PubMed

Cho, Hyoungsig; Hong, Seunghwan; Kim, Sangmin; Park, Hyokeun; Park, Ilsuk; Sohn, Hong-Gyoo

2015-09-16

A terrestrial Light Detection and Ranging (LIDAR) system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1) a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2) co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP) algorithm; and (3) a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS) receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM) generated from the LIDAR scanning data was ±27.7 cm.

Model of Peatland Vegetation Species using HyMap Image and Machine Learning

NASA Astrophysics Data System (ADS)

Dayuf Jusuf, Muhammad; Danoedoro, Projo; Muljo Sukojo, Bangun; Hartono

2017-12-01

Species Tumih / Parepat (Combretocarpus-rotundatus Mig. Dancer) family Anisophylleaceae and Meranti (Shorea Belangerang, Shorea Teysmanniana Dyer ex Brandis) family Dipterocarpaceae is a group of vegetation species distribution model. Species pioneer is predicted as an indicator of the succession of ecosystem restoration of tropical peatland characteristics and extremely fragile (unique) in the endemic hot spot of Sundaland. Climate change projections and conservation planning are hot topics of current discussion, analysis of alternative approaches and the development of combinations of species projection modelling algorithms through geospatial information systems technology. Approach model to find out the research problem of vegetation level based on the machine learning hybrid method, wavelet and artificial neural networks. Field data are used as a reference collection of natural resource field sample objects and biodiversity assessment. The testing and training ANN data set iterations times 28, achieve a performance value of 0.0867 MSE value is smaller than the ANN training data, above 50%, and spectral accuracy 82.1 %. Identify the location of the sample point position of the Tumih / Parepat vegetation species using HyMap Image is good enough, at least the modelling, design of the species distribution can reach the target in this study. The computation validation rate above 90% proves the calculation can be considered.

A predictive numerical model for potential mapping of the gas hydrate stability zone in the Gulf of Cadiz

NASA Astrophysics Data System (ADS)

Leon, R.; Somoza, L.

2009-04-01

This comunication presents a computational model for mapping the regional 3D distribution in which seafloor gas hydrates would be stable, that is carried out in a Geographical Information System (GIS) environment. The construction of the model is comprised of three primary steps, namely (1) the construction of surfaces for the various variables based on available 3D data (seafloor temperature, geothermal gradient and depth-pressure); (2) the calculation of the gas function equilibrium functions for the various hydrocarbon compositions reported from hydrate and sediment samples; and (3) the calculation of the thickness of the hydrate stability zone. The solution is based on a transcendental function, which is solved iteratively in a GIS environment. The model has been applied in the northernmost continental slope of the Gulf of Cadiz, an area where an abundant supply for hydrate formation, such as extensive hydrocarbon seeps, diapirs and fault structures, is combined with deep undercurrents and a complex seafloor morphology. In the Gulf of Cadiz, model depicts the distribution of the base of the gas hydrate stability zone for both biogenic and thermogenic gas compositions, and explains the geometry and distribution of geological structures derived from gas venting in the Tasyo Field (Gulf of Cadiz) and the generation of BSR levels on the upper continental slope.

Hydraulic tomography of discrete networks of conduits and fractures in a karstic aquifer by using a deterministic inversion algorithm

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Lecoq, N.

2018-02-01

In this paper, we present a novel inverse modeling method called Discrete Network Deterministic Inversion (DNDI) for mapping the geometry and property of the discrete network of conduits and fractures in the karstified aquifers. The DNDI algorithm is based on a coupled discrete-continuum concept to simulate numerically water flows in a model and a deterministic optimization algorithm to invert a set of observed piezometric data recorded during multiple pumping tests. In this method, the model is partioned in subspaces piloted by a set of parameters (matrix transmissivity, and geometry and equivalent transmissivity of the conduits) that are considered as unknown. In this way, the deterministic optimization process can iteratively correct the geometry of the network and the values of the properties, until it converges to a global network geometry in a solution model able to reproduce the set of data. An uncertainty analysis of this result can be performed from the maps of posterior uncertainties on the network geometry or on the property values. This method has been successfully tested for three different theoretical and simplified study cases with hydraulic responses data generated from hypothetical karstic models with an increasing complexity of the network geometry, and of the matrix heterogeneity.

The ZpiM algorithm: a method for interferometric image reconstruction in SAR/SAS.

PubMed

Dias, José M B; Leitao, José M N

2002-01-01

This paper presents an effective algorithm for absolute phase (not simply modulo-2-pi) estimation from incomplete, noisy and modulo-2pi observations in interferometric aperture radar and sonar (InSAR/InSAS). The adopted framework is also representative of other applications such as optical interferometry, magnetic resonance imaging and diffraction tomography. The Bayesian viewpoint is adopted; the observation density is 2-pi-periodic and accounts for the interferometric pair decorrelation and system noise; the a priori probability of the absolute phase is modeled by a compound Gauss-Markov random field (CGMRF) tailored to piecewise smooth absolute phase images. We propose an iterative scheme for the computation of the maximum a posteriori probability (MAP) absolute phase estimate. Each iteration embodies a discrete optimization step (Z-step), implemented by network programming techniques and an iterative conditional modes (ICM) step (pi-step). Accordingly, the algorithm is termed ZpiM, where the letter M stands for maximization. An important contribution of the paper is the simultaneous implementation of phase unwrapping (inference of the 2pi-multiples) and smoothing (denoising of the observations). This improves considerably the accuracy of the absolute phase estimates compared to methods in which the data is low-pass filtered prior to unwrapping. A set of experimental results, comparing the proposed algorithm with alternative methods, illustrates the effectiveness of our approach.

PyCCF: Python Cross Correlation Function for reverberation mapping studies

NASA Astrophysics Data System (ADS)

Sun, Mouyuan; Grier, C. J.; Peterson, B. M.

2018-05-01

PyCCF emulates a Fortran program written by B. Peterson for use with reverberation mapping. The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monto Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results.

An iterative approach for compound detection in an unknown pharmaceutical drug product: Application on Raman microscopy.

PubMed

Boiret, Mathieu; Gorretta, Nathalie; Ginot, Yves-Michel; Roger, Jean-Michel

2016-02-20

Raman chemical imaging provides both spectral and spatial information on a pharmaceutical drug product. Even if the main objective of chemical imaging is to obtain distribution maps of each formulation compound, identification of pure signals in a mixture dataset remains of huge interest. In this work, an iterative approach is proposed to identify the compounds in a pharmaceutical drug product, assuming that the chemical composition of the product is not known by the analyst and that a low dose compound can be present in the studied medicine. The proposed approach uses a spectral library, spectral distances and orthogonal projections to iteratively detect pure compounds of a tablet. Since the proposed method is not based on variance decomposition, it should be well adapted for a drug product which contains a low dose product, interpreted as a compound located in few pixels and with low spectral contributions. The method is tested on a tablet specifically manufactured for this study with one active pharmaceutical ingredient and five excipients. A spectral library, constituted of 24 pure pharmaceutical compounds, is used as a reference spectral database. Pure spectra of active and excipients, including a modification of the crystalline form and a low dose compound, are iteratively detected. Once the pure spectra are identified, multivariate curve resolution-alternating least squares process is performed on the data to provide distribution maps of each compound in the studied sample. Distributions of the two crystalline forms of active and the five excipients were in accordance with the theoretical formulation. Copyright © 2015 Elsevier B.V. All rights reserved.

Progress in Development of the ITER Plasma Control System Simulation Platform

NASA Astrophysics Data System (ADS)

Walker, Michael; Humphreys, David; Sammuli, Brian; Ambrosino, Giuseppe; de Tommasi, Gianmaria; Mattei, Massimiliano; Raupp, Gerhard; Treutterer, Wolfgang; Winter, Axel

2017-10-01

We report on progress made and expected uses of the Plasma Control System Simulation Platform (PCSSP), the primary test environment for development of the ITER Plasma Control System (PCS). PCSSP will be used for verification and validation of the ITER PCS Final Design for First Plasma, to be completed in 2020. We discuss the objectives of PCSSP, its overall structure, selected features, application to existing devices, and expected evolution over the lifetime of the ITER PCS. We describe an archiving solution for simulation results, methods for incorporating physics models of the plasma and physical plant (tokamak, actuator, and diagnostic systems) into PCSSP, and defining characteristics of models suitable for a plasma control development environment such as PCSSP. Applications of PCSSP simulation models including resistive plasma equilibrium evolution are demonstrated. PCSSP development supported by ITER Organization under ITER/CTS/6000000037. Resistive evolution code developed under General Atomics' Internal funding. The views and opinions expressed herein do not necessarily reflect those of the ITER Organization.

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

PubMed

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

Spatial frequency domain spectroscopy of two layer media

NASA Astrophysics Data System (ADS)

Yudovsky, Dmitry; Durkin, Anthony J.

2011-10-01

Monitoring of tissue blood volume and oxygen saturation using biomedical optics techniques has the potential to inform the assessment of tissue health, healing, and dysfunction. These quantities are typically estimated from the contribution of oxyhemoglobin and deoxyhemoglobin to the absorption spectrum of the dermis. However, estimation of blood related absorption in superficial tissue such as the skin can be confounded by the strong absorption of melanin in the epidermis. Furthermore, epidermal thickness and pigmentation varies with anatomic location, race, gender, and degree of disease progression. This study describes a technique for decoupling the effect of melanin absorption in the epidermis from blood absorption in the dermis for a large range of skin types and thicknesses. An artificial neural network was used to map input optical properties to spatial frequency domain diffuse reflectance of two layer media. Then, iterative fitting was used to determine the optical properties from simulated spatial frequency domain diffuse reflectance. Additionally, an artificial neural network was trained to directly map spatial frequency domain reflectance to sets of optical properties of a two layer medium, thus bypassing the need for iteration. In both cases, the optical thickness of the epidermis and absorption and reduced scattering coefficients of the dermis were determined independently. The accuracy and efficiency of the iterative fitting approach was compared with the direct neural network inversion.

A Model and Simple Iterative Algorithm for Redundancy Analysis.

ERIC Educational Resources Information Center

Fornell, Claes; And Others

1988-01-01

This paper shows that redundancy maximization with J. K. Johansson's extension can be accomplished via a simple iterative algorithm based on H. Wold's Partial Least Squares. The model and the iterative algorithm for the least squares approach to redundancy maximization are presented. (TJH)

SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Loikith, P.; Lee, H.; McGibbney, L. J.; Whitehall, K. D.

2014-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark. Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based ApacheTM Hadoop by 100x in memory and by 10x on disk, and makes iterative algorithms feasible. SciSpark will enable scalable model evaluation by executing large-scale comparisons of A-Train satellite observations to model grids on a cluster of 100 to 1000 compute nodes. This 2nd generation capability for NASA's Regional Climate Model Evaluation System (RCMES) will compute simple climate metrics at interactive speeds, and extend to quite sophisticated iterative algorithms such as machine-learning (ML) based clustering of temperature PDFs, and even graph-based algorithms for searching for Mesocale Convective Complexes. The goals of SciSpark are to: (1) Decrease the time to compute comparison statistics and plots from minutes to seconds; (2) Allow for interactive exploration of time-series properties over seasons and years; (3) Decrease the time for satellite data ingestion into RCMES to hours; (4) Allow for Level-2 comparisons with higher-order statistics or PDF's in minutes to hours; and (5) Move RCMES into a near real time decision-making platform. We will report on: the architecture and design of SciSpark, our efforts to integrate climate science algorithms in Python and Scala, parallel ingest and partitioning (sharding) of A-Train satellite observations from HDF files and model grids from netCDF files, first parallel runs to compute comparison statistics and PDF's, and first metrics quantifying parallel speedups and memory & disk usage.

Susceptibility analysis for slides and rockfall: an example from the Northern Calcareous Alps (Vorarlberg, Austria)

NASA Astrophysics Data System (ADS)

Ruff, Michael; Rohn, Joachim

2008-07-01

In this paper a tool for semi-quantitative susceptibility assessment at a regional scale is presented which is applicable at areas with complex geological setting. At a study area within the Northern Calcareous Alps geotechnical mappings were implemented into a Geographical Information System and analysed as grid data with a cell size of 25 m. The susceptibility to sliding and falling processes was considered according to five classes (very low, low, medium, high, very high). Susceptibility to sliding was analysed using an index method. The layers of lithology, bedding conditions, tectonic faults, slope angle, slope aspect, vegetation and erosion were combined iteratively. Dropout zones of rockfall material were determined with help of a Digital Elevation Model. The movement of rolling rock samples was modelled by a cost analysis of all potential rockfall trajectories. These trajectories were also divided into five susceptibility classes. The susceptibility maps are presented in a general way to be used by communities and spatial planners. Conflict areas of susceptibility and landuse were located and can be presented destinctively.

Lesion identification using unified segmentation-normalisation models and fuzzy clustering

PubMed Central

Seghier, Mohamed L.; Ramlackhansingh, Anil; Crinion, Jenny; Leff, Alexander P.; Price, Cathy J.

2008-01-01

In this paper, we propose a new automated procedure for lesion identification from single images based on the detection of outlier voxels. We demonstrate the utility of this procedure using artificial and real lesions. The scheme rests on two innovations: First, we augment the generative model used for combined segmentation and normalization of images, with an empirical prior for an atypical tissue class, which can be optimised iteratively. Second, we adopt a fuzzy clustering procedure to identify outlier voxels in normalised gray and white matter segments. These two advances suppress misclassification of voxels and restrict lesion identification to gray/white matter lesions respectively. Our analyses show a high sensitivity for detecting and delineating brain lesions with different sizes, locations, and textures. Our approach has important implications for the generation of lesion overlap maps of a given population and the assessment of lesion-deficit mappings. From a clinical perspective, our method should help to compute the total volume of lesion or to trace precisely lesion boundaries that might be pertinent for surgical or diagnostic purposes. PMID:18482850

xMDFF: molecular dynamics flexible fitting of low-resolution X-ray structures.

PubMed

McGreevy, Ryan; Singharoy, Abhishek; Li, Qufei; Zhang, Jingfen; Xu, Dong; Perozo, Eduardo; Schulten, Klaus

2014-09-01

X-ray crystallography remains the most dominant method for solving atomic structures. However, for relatively large systems, the availability of only medium-to-low-resolution diffraction data often limits the determination of all-atom details. A new molecular dynamics flexible fitting (MDFF)-based approach, xMDFF, for determining structures from such low-resolution crystallographic data is reported. xMDFF employs a real-space refinement scheme that flexibly fits atomic models into an iteratively updating electron-density map. It addresses significant large-scale deformations of the initial model to fit the low-resolution density, as tested with synthetic low-resolution maps of D-ribose-binding protein. xMDFF has been successfully applied to re-refine six low-resolution protein structures of varying sizes that had already been submitted to the Protein Data Bank. Finally, via systematic refinement of a series of data from 3.6 to 7 Å resolution, xMDFF refinements together with electrophysiology experiments were used to validate the first all-atom structure of the voltage-sensing protein Ci-VSP.

An Expert Map of Gambling Risk Perception.

PubMed

Spurrier, Michael; Blaszczynski, Alexander; Rhodes, Paul

2015-12-01

The purpose of the current study was to investigate the moderating or mediating role played by risk perception in decision-making, gambling behaviour, and disordered gambling aetiology. Eleven gambling expert clinicians and researchers completed a semi-structured interview derived from mental models and grounded theory methodologies. Expert interview data was used to construct a comprehensive expert mental model 'map' detailing risk-perception related factors contributing to harmful or safe gambling. Systematic overlapping processes of data gathering and analysis were used to iteratively extend, saturate, test for exception, and verify concepts and emergent themes. Findings indicated that experts considered idiosyncratic beliefs among gamblers result in overall underestimates of risk and loss, insufficient prioritization of needs, and planning and implementation of risk management strategies. Additional contextual factors influencing use of risk information (reinforcement and learning; mental states, environmental cues, ambivalence; and socio-cultural and biological variables) acted to shape risk perceptions and increase vulnerabilities to harm or disordered gambling. It was concluded that understanding the nature, extent and processes by which risk perception predisposes an individual to maintain gambling despite adverse consequences can guide the content of preventative educational responsible gambling campaigns.

Development of a conceptual model of cancer caregiver health literacy.

PubMed

Yuen, E Y N; Dodson, S; Batterham, R W; Knight, T; Chirgwin, J; Livingston, P M

2016-03-01

Caregivers play a vital role in caring for people diagnosed with cancer. However, little is understood about caregivers' capacity to find, understand, appraise and use information to improve health outcomes. The study aimed to develop a conceptual model that describes the elements of cancer caregiver health literacy. Six concept mapping workshops were conducted with 13 caregivers, 13 people with cancer and 11 healthcare providers/policymakers. An iterative, mixed methods approach was used to analyse and synthesise workshop data and to generate the conceptual model. Six major themes and 17 subthemes were identified from 279 statements generated by participants during concept mapping workshops. Major themes included: access to information, understanding of information, relationship with healthcare providers, relationship with the care recipient, managing challenges of caregiving and support systems. The study extends conceptualisations of health literacy by identifying factors specific to caregiving within the cancer context. The findings demonstrate that caregiver health literacy is multidimensional, includes a broad range of individual and interpersonal elements, and is influenced by broader healthcare system and community factors. These results provide guidance for the development of: caregiver health literacy measurement tools; strategies for improving health service delivery, and; interventions to improve caregiver health literacy. © 2015 John Wiley & Sons Ltd.

Computer-assisted concept mapping: Visual aids for knowledge construction

PubMed Central

Mammen, Jennifer R.

2016-01-01

Background Concept mapping is a visual representation of ideas that facilitates critical thinking and is applicable to many areas of nursing education. Computer-Assisted Concept Maps are more flexible and less constrained than traditional paper methods, allowing for analysis and synthesis of complex topics and larger amounts of data. Ability to iteratively revise and collaboratively create computerized maps can contribute to enhanced interpersonal learning. However, there is limited awareness of free software that can support these types of applications. Discussion This educational brief examines affordances and limitations of Computer-Assisted Concept Maps and reviews free software for development of complex, collaborative malleable maps. Free software such as VUE, Xmind, MindMaple, and others can substantially contribute to utility of concept-mapping for nursing education. Conclusions Computerized concept-mapping is an important tool for nursing and is likely to hold greater benefit for students and faculty than traditional pen and paper methods alone. PMID:27351610

Rapid anatomical brain imaging using spiral acquisition and an expanded signal model.

PubMed

Kasper, Lars; Engel, Maria; Barmet, Christoph; Haeberlin, Maximilian; Wilm, Bertram J; Dietrich, Benjamin E; Schmid, Thomas; Gross, Simon; Brunner, David O; Stephan, Klaas E; Pruessmann, Klaas P

2018-03-01

We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B 0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T 2 * contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency. Copyright © 2017 Elsevier Inc. All rights reserved.

The integration of palaeogeography and tectonics in refining plate tectonic models: an example from SE Asia

NASA Astrophysics Data System (ADS)

Masterton, S. M.; Markwick, P.; Bailiff, R.; Campanile, D.; Edgecombe, E.; Eue, D.; Galsworthy, A.; Wilson, K.

2012-04-01

Our understanding of lithospheric evolution and global plate motions throughout the Earth's history is based largely upon detailed knowledge of plate boundary structures, inferences about tectonic regimes, ocean isochrons and palaeomagnetic data. Most currently available plate models are either regionally restricted or do not consider palaeogeographies in their construction. Here, we present an integrated methodology in which derived hypotheses have been further refined using global and regional palaeogeographic, palaeotopological and palaeobathymetric maps. Iteration between our self-consistent and structurally constrained global plate model and palaeogeographic interpretations which are built on these reconstructions, allows for greater testing and refinement of results. Our initial structural and tectonic interpretations are based largely on analysis of our extensive global database of gravity and magnetic potential field data, and are further constrained by seismic, SRTM and Landsat data. This has been used as the basis for detailed interpretations that have allowed us to compile a new global map and database of structures, crustal types, plate boundaries and basin definitions. Our structural database is used in the identification of major tectonic terranes and their relative motions, from which we have developed our global plate model. It is subject to an ongoing process of regional evaluation and revisions in an effort to incorporate and reflect new tectonic and geologic interpretations. A major element of this programme is the extension of our existing plate model (GETECH Global Plate Model V1) back to the Neoproterozic. Our plate model forms the critical framework upon which palaeogeographic and palaeotopographic reconstructions have been made for every time stage in the Cretaceous and Cenozoic. Generating palaeogeographies involves integration of a variety of data, such as regional geology, palaeoclimate analyses, lithology, sea-level estimates, thermo-mechanical events and regional tectonics. These data are interpreted to constrain depositional systems and tectonophysiographic terranes. Palaeotopography and palaeobathymetry are derived from these tectonophysiographic terranes and depositional systems, and are further constrained using geological relationships, thermochronometric data, palaeoaltimetry indicators and modern analogues. Throughout this process, our plate model is iteratively tested against our palaeogeographies and their environmental consequences. Both the plate model and the palaeogeographies are refined until we have obtained a consistent and scientifically robust result. In this presentation we show an example from Southeast Asia, where the plate model complexity and wide variation in hypotheses has huge implications for the palaeogeographic interpretation, which can then be tested using geological observations from well and seismic data. For example, the Khorat Plateau Basin, Northeastern Thailand, comprises a succession of fluvial clastics during the Cretaceous, which include the evaporites of the Maha Sarakham Formation. These have been variously interpreted as indicative of saline lake or marine incursion depositional environments. We show how the feasibility of these different hypotheses is dependent on the regional palaeogeography (whether a marine link is possible), which in turn depends on the underlying plate model. We show two models with widely different environmental consequences. A more robust model that takes into account all these consequences, as well as data, can be defined by iterating through the consequences of the plate model and geological observations.

Foldover-free shape deformation for biomedicine.

PubMed

Yu, Hongchuan; Zhang, Jian J; Lee, Tong-Yee

2014-04-01

Shape deformation as a fundamental geometric operation underpins a wide range of applications, from geometric modelling, medical imaging to biomechanics. In medical imaging, for example, to quantify the difference between two corresponding images, 2D or 3D, one needs to find the deformation between both images. However, such deformations, particularly deforming complex volume datasets, are prone to the problem of foldover, i.e. during deformation, the required property of one-to-one mapping no longer holds for some points. Despite numerous research efforts, the construction of a mathematically robust foldover-free solution subject to positional constraints remains open. In this paper, we address this challenge by developing a radial basis function-based deformation method. In particular we formulate an effective iterative mechanism which ensures the foldover-free property is satisfied all the time. The experimental results suggest that the resulting deformations meet the internal positional constraints. In addition to radial basis functions, this iterative mechanism can also be incorporated into other deformation approaches, e.g. B-spline based FFDs, to develop different deformable approaches for various applications. Crown Copyright © 2013. Published by Elsevier Inc. All rights reserved.

Using sequential self-calibration method to identify conductivity distribution: Conditioning on tracer test data

USGS Publications Warehouse

Hu, B.X.; He, C.

2008-01-01

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases. ?? International Association for Mathematical Geology 2008.

Image Encryption Algorithm Based on Hyperchaotic Maps and Nucleotide Sequences Database

PubMed Central

2017-01-01

Image encryption technology is one of the main means to ensure the safety of image information. Using the characteristics of chaos, such as randomness, regularity, ergodicity, and initial value sensitiveness, combined with the unique space conformation of DNA molecules and their unique information storage and processing ability, an efficient method for image encryption based on the chaos theory and a DNA sequence database is proposed. In this paper, digital image encryption employs a process of transforming the image pixel gray value by using chaotic sequence scrambling image pixel location and establishing superchaotic mapping, which maps quaternary sequences and DNA sequences, and by combining with the logic of the transformation between DNA sequences. The bases are replaced under the displaced rules by using DNA coding in a certain number of iterations that are based on the enhanced quaternary hyperchaotic sequence; the sequence is generated by Chen chaos. The cipher feedback mode and chaos iteration are employed in the encryption process to enhance the confusion and diffusion properties of the algorithm. Theoretical analysis and experimental results show that the proposed scheme not only demonstrates excellent encryption but also effectively resists chosen-plaintext attack, statistical attack, and differential attack. PMID:28392799

A multiscale restriction-smoothed basis method for high contrast porous media represented on unstructured grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Møyner, Olav, E-mail: olav.moyner@sintef.no; Lie, Knut-Andreas, E-mail: knut-andreas.lie@sintef.no

2016-01-01

A wide variety of multiscale methods have been proposed in the literature to reduce runtime and provide better scaling for the solution of Poisson-type equations modeling flow in porous media. We present a new multiscale restricted-smoothed basis (MsRSB) method that is designed to be applicable to both rectilinear grids and unstructured grids. Like many other multiscale methods, MsRSB relies on a coarse partition of the underlying fine grid and a set of local prolongation operators (multiscale basis functions) that map unknowns associated with the fine grid cells to unknowns associated with blocks in the coarse partition. These mappings are constructedmore » by restricted smoothing: Starting from a constant, a localized iterative scheme is applied directly to the fine-scale discretization to compute prolongation operators that are consistent with the local properties of the differential operators. The resulting method has three main advantages: First of all, both the coarse and the fine grid can have general polyhedral geometry and unstructured topology. This means that partitions and good prolongation operators can easily be constructed for complex models involving high media contrasts and unstructured cell connections introduced by faults, pinch-outs, erosion, local grid refinement, etc. In particular, the coarse partition can be adapted to geological or flow-field properties represented on cells or faces to improve accuracy. Secondly, the method is accurate and robust when compared to existing multiscale methods and does not need expensive recomputation of local basis functions to account for transient behavior: Dynamic mobility changes are incorporated by continuing to iterate a few extra steps on existing basis functions. This way, the cost of updating the prolongation operators becomes proportional to the amount of change in fluid mobility and one reduces the need for expensive, tolerance-based updates. Finally, since the MsRSB method is formulated on top of a cell-centered, conservative, finite-volume method, it is applicable to any flow model in which one can isolate a pressure equation. Herein, we only discuss single and two-phase incompressible models. Compressible flow, e.g., as modeled by the black-oil equations, is discussed in a separate paper.« less

Using parallel banded linear system solvers in generalized eigenvalue problems

NASA Technical Reports Server (NTRS)

Zhang, Hong; Moss, William F.

1993-01-01

Subspace iteration is a reliable and cost effective method for solving positive definite banded symmetric generalized eigenproblems, especially in the case of large scale problems. This paper discusses an algorithm that makes use of two parallel banded solvers in subspace iteration. A shift is introduced to decompose the banded linear systems into relatively independent subsystems and to accelerate the iterations. With this shift, an eigenproblem is mapped efficiently into the memories of a multiprocessor and a high speed-up is obtained for parallel implementations. An optimal shift is a shift that balances total computation and communication costs. Under certain conditions, we show how to estimate an optimal shift analytically using the decay rate for the inverse of a banded matrix, and how to improve this estimate. Computational results on iPSC/2 and iPSC/860 multiprocessors are presented.

Fast and secure encryption-decryption method based on chaotic dynamics

DOEpatents

Protopopescu, Vladimir A.; Santoro, Robert T.; Tolliver, Johnny S.

1995-01-01

A method and system for the secure encryption of information. The method comprises the steps of dividing a message of length L into its character components; generating m chaotic iterates from m independent chaotic maps; producing an "initial" value based upon the m chaotic iterates; transforming the "initial" value to create a pseudo-random integer; repeating the steps of generating, producing and transforming until a pseudo-random integer sequence of length L is created; and encrypting the message as ciphertext based upon the pseudo random integer sequence. A system for accomplishing the invention is also provided.

Convergence of Newton's method for a single real equation

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1985-01-01

Newton's method for finding the zeroes of a single real function is investigated in some detail. Convergence is generally checked using the Contraction Mapping Theorem which yields sufficient but not necessary conditions for convergence of the general single point iteration method. The resulting convergence intervals are frequently considerably smaller than actual convergence zones. For a specific single point iteration method, such as Newton's method, better estimates of regions of convergence should be possible. A technique is described which, under certain conditions (frequently satisfied by well behaved functions) gives much larger zones where convergence is guaranteed.

Group search algorithm recovers effective connectivity maps for individuals in homogeneous and heterogeneous samples.

PubMed

Gates, Kathleen M; Molenaar, Peter C M

2012-10-15

At its best, connectivity mapping can offer researchers great insight into how spatially disparate regions of the human brain coordinate activity during brain processing. A recent investigation conducted by Smith and colleagues (2011) on methods for estimating connectivity maps suggested that those which attempt to ascertain the direction of influence among ROIs rarely provide reliable results. Another problem gaining increasing attention is heterogeneity in connectivity maps. Most group-level methods require that the data come from homogeneous samples, and misleading findings may arise from current methods if the connectivity maps for individuals vary across the sample (which is likely the case). The utility of maps resulting from effective connectivity on the individual or group levels is thus diminished because they do not accurately inform researchers. The present paper introduces a novel estimation technique for fMRI researchers, Group Iterative Multiple Model Estimation (GIMME), which demonstrates that using information across individuals assists in the recovery of the existence of connections among ROIs used by Smith and colleagues (2011) and the direction of the influence. Using heterogeneous in-house data, we demonstrate that GIMME offers a unique improvement over current approaches by arriving at reliable group and individual structures even when the data are highly heterogeneous across individuals comprising the group. An added benefit of GIMME is that it obtains reliable connectivity map estimates equally well using the data from resting state, block, or event-related designs. GIMME provides researchers with a powerful, flexible tool for identifying directed connectivity maps at the group and individual levels. Copyright © 2012 Elsevier Inc. All rights reserved.

Revisiting r > g-The asymptotic dynamics of wealth inequality

NASA Astrophysics Data System (ADS)

Berman, Yonatan; Shapira, Yoash

2017-02-01

Studying the underlying mechanisms of wealth inequality dynamics is essential for its understanding and for policy aiming to regulate its level. We apply a heterogeneous non-interacting agent-based modeling approach, solved using iterated maps to model the dynamics of wealth inequality based on 3 parameters-the economic output growth rate g, the capital value change rate a and the personal savings rate s and show that for a < g the wealth distribution reaches an asymptotic shape and becomes close to the income distribution. If a > g, the wealth distribution constantly becomes more and more inegalitarian. We also show that when a < g, wealth is asymptotically accumulated at the same rate as the economic output, which also implies that the wealth-disposable income ratio asymptotically converges to s /(g - a) .

Iterative-Transform Phase Retrieval Using Adaptive Diversity

NASA Technical Reports Server (NTRS)

Dean, Bruce H.

2007-01-01

A phase-diverse iterative-transform phase-retrieval algorithm enables high spatial-frequency, high-dynamic-range, image-based wavefront sensing. [The terms phase-diverse, phase retrieval, image-based, and wavefront sensing are defined in the first of the two immediately preceding articles, Broadband Phase Retrieval for Image-Based Wavefront Sensing (GSC-14899-1).] As described below, no prior phase-retrieval algorithm has offered both high dynamic range and the capability to recover high spatial-frequency components. Each of the previously developed image-based phase-retrieval techniques can be classified into one of two categories: iterative transform or parametric. Among the modifications of the original iterative-transform approach has been the introduction of a defocus diversity function (also defined in the cited companion article). Modifications of the original parametric approach have included minimizing alternative objective functions as well as implementing a variety of nonlinear optimization methods. The iterative-transform approach offers the advantage of ability to recover low, middle, and high spatial frequencies, but has disadvantage of having a limited dynamic range to one wavelength or less. In contrast, parametric phase retrieval offers the advantage of high dynamic range, but is poorly suited for recovering higher spatial frequency aberrations. The present phase-diverse iterative transform phase-retrieval algorithm offers both the high-spatial-frequency capability of the iterative-transform approach and the high dynamic range of parametric phase-recovery techniques. In implementation, this is a focus-diverse iterative-transform phaseretrieval algorithm that incorporates an adaptive diversity function, which makes it possible to avoid phase unwrapping while preserving high-spatial-frequency recovery. The algorithm includes an inner and an outer loop (see figure). An initial estimate of phase is used to start the algorithm on the inner loop, wherein multiple intensity images are processed, each using a different defocus value. The processing is done by an iterative-transform method, yielding individual phase estimates corresponding to each image of the defocus-diversity data set. These individual phase estimates are combined in a weighted average to form a new phase estimate, which serves as the initial phase estimate for either the next iteration of the iterative-transform method or, if the maximum number of iterations has been reached, for the next several steps, which constitute the outerloop portion of the algorithm. The details of the next several steps must be omitted here for the sake of brevity. The overall effect of these steps is to adaptively update the diversity defocus values according to recovery of global defocus in the phase estimate. Aberration recovery varies with differing amounts as the amount of diversity defocus is updated in each image; thus, feedback is incorporated into the recovery process. This process is iterated until the global defocus error is driven to zero during the recovery process. The amplitude of aberration may far exceed one wavelength after completion of the inner-loop portion of the algorithm, and the classical iterative transform method does not, by itself, enable recovery of multi-wavelength aberrations. Hence, in the absence of a means of off-loading the multi-wavelength portion of the aberration, the algorithm would produce a wrapped phase map. However, a special aberration-fitting procedure can be applied to the wrapped phase data to transfer at least some portion of the multi-wavelength aberration to the diversity function, wherein the data are treated as known phase values. In this way, a multiwavelength aberration can be recovered incrementally by successively applying the aberration-fitting procedure to intermediate wrapped phase maps. During recovery, as more of the aberration is transferred to the diversity function following successive iterations around the ter loop, the estimated phase ceases to wrap in places where the aberration values become incorporated as part of the diversity function. As a result, as the aberration content is transferred to the diversity function, the phase estimate resembles that of a reference flat.

A Model Based Deconvolution Approach for Creating Surface Composition Maps of Irregularly Shaped Bodies from Limited Orbiting Nuclear Spectrometer Measurements

NASA Astrophysics Data System (ADS)

Dallmann, N. A.; Carlsten, B. E.; Stonehill, L. C.

2017-12-01

Orbiting nuclear spectrometers have contributed significantly to our understanding of the composition of solar system bodies. Gamma rays and neutrons are produced within the surfaces of bodies by impacting galactic cosmic rays (GCR) and by intrinsic radionuclide decay. Measuring the flux and energy spectrum of these products at one point in an orbit elucidates the elemental content of the area in view. Deconvolution of measurements from many spatially registered orbit points can produce detailed maps of elemental abundances. In applying these well-established techniques to small and irregularly shaped bodies like Phobos, one encounters unique challenges beyond those of a large spheroid. Polar mapping orbits are not possible for Phobos and quasistatic orbits will realize only modest inclinations unavoidably limiting surface coverage and creating North-South ambiguities in deconvolution. The irregular shape causes self-shadowing both of the body to the spectrometer but also of the body to the incoming GCR. The view angle to the surface normal as well as the distance between the surface and the spectrometer is highly irregular. These characteristics can be synthesized into a complicated and continuously changing measurement system point spread function. We have begun to explore different model-based, statistically rigorous, iterative deconvolution methods to produce elemental abundance maps for a proposed future investigation of Phobos. By incorporating the satellite orbit, the existing high accuracy shape-models of Phobos, and the spectrometer response function, a detailed and accurate system model can be constructed. Many aspects of this model formation are particularly well suited to modern graphics processing techniques and parallel processing. We will present the current status and preliminary visualizations of the Phobos measurement system model. We will also discuss different deconvolution strategies and their relative merit in statistical rigor, stability, achievable resolution, and exploitation of the irregular shape to partially resolve ambiguities. The general applicability of these new approaches to existing data sets from Mars, Mercury, and Lunar investigations will be noted.

Modeling design iteration in product design and development and its solution by a novel artificial bee colony algorithm.

PubMed

Chen, Tinggui; Xiao, Renbin

2014-01-01

Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness.

ANNIT - An Efficient Inversion Algorithm based on Prediction Principles

NASA Astrophysics Data System (ADS)

Růžek, B.; Kolář, P.

2009-04-01

Solution of inverse problems represents meaningful job in geophysics. The amount of data is continuously increasing, methods of modeling are being improved and the computer facilities are also advancing great technical progress. Therefore the development of new and efficient algorithms and computer codes for both forward and inverse modeling is still up to date. ANNIT is contributing to this stream since it is a tool for efficient solution of a set of non-linear equations. Typical geophysical problems are based on parametric approach. The system is characterized by a vector of parameters p, the response of the system is characterized by a vector of data d. The forward problem is usually represented by unique mapping F(p)=d. The inverse problem is much more complex and the inverse mapping p=G(d) is available in an analytical or closed form only exceptionally and generally it may not exist at all. Technically, both forward and inverse mapping F and G are sets of non-linear equations. ANNIT solves such situation as follows: (i) joint subspaces {pD, pM} of original data and model spaces D, M, resp. are searched for, within which the forward mapping F is sufficiently smooth that the inverse mapping G does exist, (ii) numerical approximation of G in subspaces {pD, pM} is found, (iii) candidate solution is predicted by using this numerical approximation. ANNIT is working in an iterative way in cycles. The subspaces {pD, pM} are searched for by generating suitable populations of individuals (models) covering data and model spaces. The approximation of the inverse mapping is made by using three methods: (a) linear regression, (b) Radial Basis Function Network technique, (c) linear prediction (also known as "Kriging"). The ANNIT algorithm has built in also an archive of already evaluated models. Archive models are re-used in a suitable way and thus the number of forward evaluations is minimized. ANNIT is now implemented both in MATLAB and SCILAB. Numerical tests show good performance of the algorithm. Both versions and documentation are available on Internet and anybody can download them. The goal of this presentation is to offer the algorithm and computer codes for anybody interested in the solution to inverse problems.

Comparison between iteration schemes for three-dimensional coordinate-transformed saturated-unsaturated flow model

NASA Astrophysics Data System (ADS)

An, Hyunuk; Ichikawa, Yutaka; Tachikawa, Yasuto; Shiiba, Michiharu

2012-11-01

SummaryThree different iteration methods for a three-dimensional coordinate-transformed saturated-unsaturated flow model are compared in this study. The Picard and Newton iteration methods are the common approaches for solving Richards' equation. The Picard method is simple to implement and cost-efficient (on an individual iteration basis). However it converges slower than the Newton method. On the other hand, although the Newton method converges faster, it is more complex to implement and consumes more CPU resources per iteration than the Picard method. The comparison of the two methods in finite-element model (FEM) for saturated-unsaturated flow has been well evaluated in previous studies. However, two iteration methods might exhibit different behavior in the coordinate-transformed finite-difference model (FDM). In addition, the Newton-Krylov method could be a suitable alternative for the coordinate-transformed FDM because it requires the evaluation of a 19-point stencil matrix. The formation of a 19-point stencil is quite a complex and laborious procedure. Instead, the Newton-Krylov method calculates the matrix-vector product, which can be easily approximated by calculating the differences of the original nonlinear function. In this respect, the Newton-Krylov method might be the most appropriate iteration method for coordinate-transformed FDM. However, this method involves the additional cost of taking an approximation at each Krylov iteration in the Newton-Krylov method. In this paper, we evaluated the efficiency and robustness of three iteration methods—the Picard, Newton, and Newton-Krylov methods—for simulating saturated-unsaturated flow through porous media using a three-dimensional coordinate-transformed FDM.

New methods of testing nonlinear hypothesis using iterative NLLS estimator

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Mokeshrayalu, G.; Balasiddamuni, P.

2017-11-01

This research paper discusses the method of testing nonlinear hypothesis using iterative Nonlinear Least Squares (NLLS) estimator. Takeshi Amemiya [1] explained this method. However in the present research paper, a modified Wald test statistic due to Engle, Robert [6] is proposed to test the nonlinear hypothesis using iterative NLLS estimator. An alternative method for testing nonlinear hypothesis using iterative NLLS estimator based on nonlinear hypothesis using iterative NLLS estimator based on nonlinear studentized residuals has been proposed. In this research article an innovative method of testing nonlinear hypothesis using iterative restricted NLLS estimator is derived. Pesaran and Deaton [10] explained the methods of testing nonlinear hypothesis. This paper uses asymptotic properties of nonlinear least squares estimator proposed by Jenrich [8]. The main purpose of this paper is to provide very innovative methods of testing nonlinear hypothesis using iterative NLLS estimator, iterative NLLS estimator based on nonlinear studentized residuals and iterative restricted NLLS estimator. Eakambaram et al. [12] discussed least absolute deviation estimations versus nonlinear regression model with heteroscedastic errors and also they studied the problem of heteroscedasticity with reference to nonlinear regression models with suitable illustration. William Grene [13] examined the interaction effect in nonlinear models disused by Ai and Norton [14] and suggested ways to examine the effects that do not involve statistical testing. Peter [15] provided guidelines for identifying composite hypothesis and addressing the probability of false rejection for multiple hypotheses.

Global transport in a nonautonomous periodic standard map

DOE PAGES

Calleja, Renato C.; del-Castillo-Negrete, D.; Martinez-del-Rio, D.; ...

2017-04-14

A non-autonomous version of the standard map with a periodic variation of the perturbation parameter is introduced and studied via an autonomous map obtained from the iteration of the nonautonomous map over a period. Symmetry properties in the variables and parameters of the map are found and used to find relations between rotation numbers of invariant sets. The role of the nonautonomous dynamics on period-one orbits, stability and bifurcation is studied. The critical boundaries for the global transport and for the destruction of invariant circles with fixed rotation number are studied in detail using direct computation and a continuation method.more » In the case of global transport, the critical boundary has a particular symmetrical horn shape. Here, the results are contrasted with similar calculations found in the literature.« less

Global transport in a nonautonomous periodic standard map

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calleja, Renato C.; del-Castillo-Negrete, D.; Martinez-del-Rio, D.

A non-autonomous version of the standard map with a periodic variation of the perturbation parameter is introduced and studied via an autonomous map obtained from the iteration of the nonautonomous map over a period. Symmetry properties in the variables and parameters of the map are found and used to find relations between rotation numbers of invariant sets. The role of the nonautonomous dynamics on period-one orbits, stability and bifurcation is studied. The critical boundaries for the global transport and for the destruction of invariant circles with fixed rotation number are studied in detail using direct computation and a continuation method.more » In the case of global transport, the critical boundary has a particular symmetrical horn shape. Here, the results are contrasted with similar calculations found in the literature.« less

Adjusting stream-sediment geochemical maps in the Austrian Bohemian Massif by analysis of variance

USGS Publications Warehouse

Davis, J.C.; Hausberger, G.; Schermann, O.; Bohling, G.

1995-01-01

The Austrian portion of the Bohemian Massif is a Precambrian terrane composed mostly of highly metamorphosed rocks intruded by a series of granitoids that are petrographically similar. Rocks are exposed poorly and the subtle variations in rock type are difficult to map in the field. A detailed geochemical survey of stream sediments in this region has been conducted and included as part of the Geochemischer Atlas der Republik O??sterreich, and the variations in stream sediment composition may help refine the geological interpretation. In an earlier study, multivariate analysis of variance (MANOVA) was applied to the stream-sediment data in order to minimize unwanted sampling variation and emphasize relationships between stream sediments and rock types in sample catchment areas. The estimated coefficients were used successfully to correct for the sampling effects throughout most of the region, but also introduced an overcorrection in some areas that seems to result from consistent but subtle differences in composition of specific rock types. By expanding the model to include an additional factor reflecting the presence of a major tectonic unit, the Rohrbach block, the overcorrection is removed. This iterative process simultaneously refines both the geochemical map by removing extraneous variation and the geological map by suggesting a more detailed classification of rock types. ?? 1995 International Association for Mathematical Geology.

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping.

NASA Astrophysics Data System (ADS)

Hamalainen, Sampsa; Geng, Xiaoyuan; He, Juanxia

2017-04-01

Latin Hypercube Sampling (LHS) at variable resolutions for enhanced watershed scale Soil Sampling and Digital Soil Mapping. Sampsa Hamalainen, Xiaoyuan Geng, and Juanxia, He. AAFC - Agriculture and Agr-Food Canada, Ottawa, Canada. The Latin Hypercube Sampling (LHS) approach to assist with Digital Soil Mapping has been developed for some time now, however the purpose of this work was to complement LHS with use of multiple spatial resolutions of covariate datasets and variability in the range of sampling points produced. This allowed for specific sets of LHS points to be produced to fulfil the needs of various partners from multiple projects working in the Ontario and Prince Edward Island provinces of Canada. Secondary soil and environmental attributes are critical inputs that are required in the development of sampling points by LHS. These include a required Digital Elevation Model (DEM) and subsequent covariate datasets produced as a result of a Digital Terrain Analysis performed on the DEM. These additional covariates often include but are not limited to Topographic Wetness Index (TWI), Length-Slope (LS) Factor, and Slope which are continuous data. The range of specific points created in LHS included 50 - 200 depending on the size of the watershed and more importantly the number of soil types found within. The spatial resolution of covariates included within the work ranged from 5 - 30 m. The iterations within the LHS sampling were run at an optimal level so the LHS model provided a good spatial representation of the environmental attributes within the watershed. Also, additional covariates were included in the Latin Hypercube Sampling approach which is categorical in nature such as external Surficial Geology data. Some initial results of the work include using a 1000 iteration variable within the LHS model. 1000 iterations was consistently a reasonable value used to produce sampling points that provided a good spatial representation of the environmental attributes. When working within the same spatial resolution for covariates, however only modifying the desired number of sampling points produced, the change of point location portrayed a strong geospatial relationship when using continuous data. Access to agricultural fields and adjacent land uses is often "pinned" as the greatest deterrent to performing soil sampling for both soil survey and soil attribute validation work. The lack of access can be a result of poor road access and/or difficult geographical conditions to navigate for field work individuals. This seems a simple yet continuous issue to overcome for the scientific community and in particular, soils professionals. The ability to assist with the ease of access to sampling points will be in the future a contribution to the Latin Hypercube Sampling (LHS) approach. By removing all locations in the initial instance from the DEM, the LHS model can be restricted to locations only with access from the adjacent road or trail. To further the approach, a road network geospatial dataset can be included within spatial Geographic Information Systems (GIS) applications to access already produced points using a shortest-distance network method.

Iterative quantization: a Procrustean approach to learning binary codes for large-scale image retrieval.

PubMed

Gong, Yunchao; Lazebnik, Svetlana; Gordo, Albert; Perronnin, Florent

2013-12-01

This paper addresses the problem of learning similarity-preserving binary codes for efficient similarity search in large-scale image collections. We formulate this problem in terms of finding a rotation of zero-centered data so as to minimize the quantization error of mapping this data to the vertices of a zero-centered binary hypercube, and propose a simple and efficient alternating minimization algorithm to accomplish this task. This algorithm, dubbed iterative quantization (ITQ), has connections to multiclass spectral clustering and to the orthogonal Procrustes problem, and it can be used both with unsupervised data embeddings such as PCA and supervised embeddings such as canonical correlation analysis (CCA). The resulting binary codes significantly outperform several other state-of-the-art methods. We also show that further performance improvements can result from transforming the data with a nonlinear kernel mapping prior to PCA or CCA. Finally, we demonstrate an application of ITQ to learning binary attributes or "classemes" on the ImageNet data set.

Analysis of Online Composite Mirror Descent Algorithm.

PubMed

Lei, Yunwen; Zhou, Ding-Xuan

2017-03-01

We study the convergence of the online composite mirror descent algorithm, which involves a mirror map to reflect the geometry of the data and a convex objective function consisting of a loss and a regularizer possibly inducing sparsity. Our error analysis provides convergence rates in terms of properties of the strongly convex differentiable mirror map and the objective function. For a class of objective functions with Hölder continuous gradients, the convergence rates of the excess (regularized) risk under polynomially decaying step sizes have the order [Formula: see text] after [Formula: see text] iterates. Our results improve the existing error analysis for the online composite mirror descent algorithm by avoiding averaging and removing boundedness assumptions, and they sharpen the existing convergence rates of the last iterate for online gradient descent without any boundedness assumptions. Our methodology mainly depends on a novel error decomposition in terms of an excess Bregman distance, refined analysis of self-bounding properties of the objective function, and the resulting one-step progress bounds.

Analysis of drift effects on the tokamak power scrape-off width using SOLPS-ITER

NASA Astrophysics Data System (ADS)

Meier, E. T.; Goldston, R. J.; Kaveeva, E. G.; Makowski, M. A.; Mordijck, S.; Rozhansky, V. A.; Senichenkov, I. Yu; Voskoboynikov, S. P.

2016-12-01

SOLPS-ITER, a comprehensive 2D scrape-off layer modeling package, is used to examine the physical mechanisms that set the scrape-off width ({λq} ) for inter-ELM power exhaust. Guided by Goldston’s heuristic drift (HD) model, which shows remarkable quantitative agreement with experimental data, this research examines drift effects on {λq} in a DIII-D H-mode magnetic equilibrium. As a numerical expedient, a low target recycling coefficient of 0.9 is used in the simulations, resulting in outer target plasma that is sheath limited instead of conduction limited as in the experiment. Scrape-off layer (SOL) particle diffusivity (D SOL) is scanned from 1 to 0.1 m2 s-1. Across this diffusivity range, outer divertor heat flux is dominated by a narrow (˜3-4 mm when mapped to the outer midplane) electron convection channel associated with thermoelectric current through the SOL from outer to inner divertor. An order-unity up-down ion pressure asymmetry allows net ion drift flux across the separatrix, facilitated by an artificial mechanism that mimics the anomalous electron transport required for overall ambipolarity in the HD model. At {{D}\\text{SOL}}=0.1 m2 s-1, the density fall-off length is similar to the electron temperature fall-off length, as predicted by the HD model and as seen experimentally. This research represents a step toward a deeper understanding of the power scrape-off width, and serves as a basis for extending fluid modeling to more experimentally relevant, high-collisionality regimes.

Analysis of drift effects on the tokamak power scrape-off width using SOLPS-ITER

DOE PAGES

Meier, E. T.; Goldston, R. J.; Kaveeva, E. G.; ...

2016-11-02

SOLPS-ITER, a comprehensive 2D scrape-off layer modeling package, is used to examine the physical mechanisms that set the scrape-off width (more » $${{\\lambda}_{q}}$$ ) for inter-ELM power exhaust. Guided by Goldston's heuristic drift (HD) model, which shows remarkable quantitative agreement with experimental data, this research examines drift effects on $${{\\lambda}_{q}}$$ in a DIII-D H-mode magnetic equilibrium. As a numerical expedient, a low target recycling coefficient of 0.9 is used in the simulations, resulting in outer target plasma that is sheath limited instead of conduction limited as in the experiment. Scrape-off layer (SOL) particle diffusivity (D SOL) is scanned from 1 to 0.1 m2 s –1. Across this diffusivity range, outer divertor heat flux is dominated by a narrow (~3–4mm when mapped to the outer midplane) electron convection channel associated with thermoelectric current through the SOL from outer to inner divertor. An order-unity up–down ion pressure asymmetry allows net ion drift flux across the separatrix, facilitated by an artificial mechanism that mimics the anomalous electron transport required for overall ambipolarity in the HD model. At $${{D}_{\\text{SOL}}}=0.1$$ m2 s –1, the density fall-off length is similar to the electron temperature fall-off length, as predicted by the HD model and as seen experimentally. Furthermore, this research represents a step toward a deeper understanding of the power scrape-off width, and serves as a basis for extending fluid modeling to more experimentally relevant, high-collisionality regimes.« less

Auxiliary principle technique and iterative algorithm for a perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems.

PubMed

Rahaman, Mijanur; Pang, Chin-Tzong; Ishtyak, Mohd; Ahmad, Rais

2017-01-01

In this article, we introduce a perturbed system of generalized mixed quasi-equilibrium-like problems involving multi-valued mappings in Hilbert spaces. To calculate the approximate solutions of the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems, firstly we develop a perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems, and then by using the celebrated Fan-KKM technique, we establish the existence and uniqueness of solutions of the perturbed system of auxiliary generalized multi-valued mixed quasi-equilibrium-like problems. By deploying an auxiliary principle technique and an existence result, we formulate an iterative algorithm for solving the perturbed system of generalized multi-valued mixed quasi-equilibrium-like problems. Lastly, we study the strong convergence analysis of the proposed iterative sequences under monotonicity and some mild conditions. These results are new and generalize some known results in this field.

From MIMO-OFDM Algorithms to a Real-Time Wireless Prototype: A Systematic Matlab-to-Hardware Design Flow

NASA Astrophysics Data System (ADS)

Weijers, Jan-Willem; Derudder, Veerle; Janssens, Sven; Petré, Frederik; Bourdoux, André

2006-12-01

To assess the performance of forthcoming 4th generation wireless local area networks, the algorithmic functionality is usually modelled using a high-level mathematical software package, for instance, Matlab. In order to validate the modelling assumptions against the real physical world, the high-level functional model needs to be translated into a prototype. A systematic system design methodology proves very valuable, since it avoids, or, at least reduces, numerous design iterations. In this paper, we propose a novel Matlab-to-hardware design flow, which allows to map the algorithmic functionality onto the target prototyping platform in a systematic and reproducible way. The proposed design flow is partly manual and partly tool assisted. It is shown that the proposed design flow allows to use the same testbench throughout the whole design flow and avoids time-consuming and error-prone intermediate translation steps.

Task Equivalence for Model and Human-Observer Comparisons in SPECT Localization Studies

NASA Astrophysics Data System (ADS)

Sen, Anando; Kalantari, Faraz; Gifford, Howard C.

2016-06-01

While mathematical model observers are intended for efficient assessment of medical imaging systems, their findings should be relevant for human observers as the primary clinical end users. We have investigated whether pursuing equivalence between the model and human-observer tasks can help ensure this goal. A localization receiver operating characteristic (LROC) study tested prostate lesion detection in simulated In-111 SPECT imaging with anthropomorphic phantoms. The test images were 2D slices extracted from reconstructed volumes. The iterative ordered sets expectation-maximization (OSEM) reconstruction algorithm was used with Gaussian postsmoothing. Variations in the number of iterations and the level of postfiltering defined the test strategies in the study. Human-observer performance was compared with that of a visual-search (VS) observer, a scanning channelized Hotelling observer, and a scanning channelized nonprewhitening (CNPW) observer. These model observers were applied with precise information about the target regions of interest (ROIs). ROI knowledge was a study variable for the human observers. In one study format, the humans read the SPECT image alone. With a dual-modality format, the SPECT image was presented alongside an anatomical image slice extracted from the density map of the phantom. Performance was scored by area under the LROC curve. The human observers performed significantly better with the dual-modality format, and correlation with the model observers was also improved. Given the human-observer data from the SPECT study format, the Pearson correlation coefficients for the model observers were 0.58 (VS), -0.12 (CH), and -0.23 (CNPW). The respective coefficients based on the human-observer data from the dual-modality study were 0.72, 0.27, and -0.11. These results point towards the continued development of the VS observer for enhancing task equivalence in model-observer studies.

A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

NASA Astrophysics Data System (ADS)

Ghosh, Aniruddha; Fassnacht, Fabian Ewald; Joshi, P. K.; Koch, Barbara

2014-02-01

Knowledge of tree species distribution is important worldwide for sustainable forest management and resource evaluation. The accuracy and information content of species maps produced using remote sensing images vary with scale, sensor (optical, microwave, LiDAR), classification algorithm, verification design and natural conditions like tree age, forest structure and density. Imaging spectroscopy reduces the inaccuracies making use of the detailed spectral response. However, the scale effect still has a strong influence and cannot be neglected. This study aims to bridge the knowledge gap in understanding the scale effect in imaging spectroscopy when moving from 4 to 30 m pixel size for tree species mapping, keeping in mind that most current and future hyperspectral satellite based sensors work with spatial resolution around 30 m or more. Two airborne (HyMAP) and one spaceborne (Hyperion) imaging spectroscopy dataset with pixel sizes of 4, 8 and 30 m, respectively were available to examine the effect of scale over a central European forest. The forest under examination is a typical managed forest with relatively homogenous stands featuring mostly two canopy layers. Normalized digital surface model (nDSM) derived from LiDAR data was used additionally to examine the effect of height information in tree species mapping. Six different sets of predictor variables (reflectance value of all bands, selected components of a Minimum Noise Fraction (MNF), Vegetation Indices (VI) and each of these sets combined with LiDAR derived height) were explored at each scale. Supervised kernel based (Support Vector Machines) and ensemble based (Random Forest) machine learning algorithms were applied on the dataset to investigate the effect of the classifier. Iterative bootstrap-validation with 100 iterations was performed for classification model building and testing for all the trials. For scale, analysis of overall classification accuracy and kappa values indicated that 8 m spatial resolution (reaching kappa values of over 0.83) slightly outperformed the results obtained from 4 m for the study area and five tree species under examination. The 30 m resolution Hyperion image produced sound results (kappa values of over 0.70), which in some areas of the test site were comparable with the higher spatial resolution imagery when qualitatively assessing the map outputs. Considering input predictor sets, MNF bands performed best at 4 and 8 m resolution. Optical bands were found to be best for 30 m spatial resolution. Classification with MNF as input predictors produced better visual appearance of tree species patches when compared with reference maps. Based on the analysis, it was concluded that there is no significant effect of height information on tree species classification accuracies for the present framework and study area. Furthermore, in the examined cases there was no single best choice among the two classifiers across scales and predictors. It can be concluded that tree species mapping from imaging spectroscopy for forest sites comparable to the one under investigation is possible with reliable accuracies not only from airborne but also from spaceborne imaging spectroscopy datasets.

Examining occupational therapy education through faculty engagement in curriculum mapping and pedagogical reflection.

PubMed

MacNeil, Cheryl; Hand, Theresa

2014-01-01

This article discusses a 1-yr evaluation study of a master of science in occupational therapy program to examine curriculum content and pedagogical practices as a way to gauge program preparedness to move to a clinical doctorate. Faculty members participated in a multitiered qualitative study that included curriculum mapping, semistructured individual interviewing, and iterative group analysis. Findings indicate that curriculum mapping and authentic dialogue helped the program formulate a more streamlined and integrated curriculum with increased faculty collaboration. Curriculum mapping and collaborative pedagogical reflection are valuable evaluation strategies for examining preparedness to offer a clinical doctorate, enhancing a self-study process, and providing information for ongoing formative curriculum review. Copyright © 2014 by the American Occupational Therapy Association, Inc.

Acceleration of image-based resolution modelling reconstruction using an expectation maximization nested algorithm.

PubMed

Angelis, G I; Reader, A J; Markiewicz, P J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2013-08-07

Recent studies have demonstrated the benefits of a resolution model within iterative reconstruction algorithms in an attempt to account for effects that degrade the spatial resolution of the reconstructed images. However, these algorithms suffer from slower convergence rates, compared to algorithms where no resolution model is used, due to the additional need to solve an image deconvolution problem. In this paper, a recently proposed algorithm, which decouples the tomographic and image deconvolution problems within an image-based expectation maximization (EM) framework, was evaluated. This separation is convenient, because more computational effort can be placed on the image deconvolution problem and therefore accelerate convergence. Since the computational cost of solving the image deconvolution problem is relatively small, multiple image-based EM iterations do not significantly increase the overall reconstruction time. The proposed algorithm was evaluated using 2D simulations, as well as measured 3D data acquired on the high-resolution research tomograph. Results showed that bias reduction can be accelerated by interleaving multiple iterations of the image-based EM algorithm solving the resolution model problem, with a single EM iteration solving the tomographic problem. Significant improvements were observed particularly for voxels that were located on the boundaries between regions of high contrast within the object being imaged and for small regions of interest, where resolution recovery is usually more challenging. Minor differences were observed using the proposed nested algorithm, compared to the single iteration normally performed, when an optimal number of iterations are performed for each algorithm. However, using the proposed nested approach convergence is significantly accelerated enabling reconstruction using far fewer tomographic iterations (up to 70% fewer iterations for small regions). Nevertheless, the optimal number of nested image-based EM iterations is hard to be defined and it should be selected according to the given application.

HYTHIRM Radiance Modeling and Image Analyses in Support of STS-119, STS-125 and STS-128 Space Shuttle Hypersonic Re-entries

NASA Technical Reports Server (NTRS)

Gibson, David M.; Spisz, Thomas S.; Taylor, Jeff C.; Zalameda, Joseph N.; Horvath, Thomas J.; Tomek, Deborah M.; Tietjen, Alan B.; Tack, Steve; Bush, Brett C.

2010-01-01

We provide the first geometrically accurate (i.e., 3-D) temperature maps of the entire windward surface of the Space Shuttle during hypersonic reentry. To accomplish this task we began with estimated surface temperatures derived from CFD models at integral high Mach numbers and used them, the Shuttle's surface properties and reasonable estimates of the sensor-to-target geometry to predict the emitted spectral radiance from the surface (in units of W sr-1 m-2 nm-1). These data were converted to sensor counts using properties of the sensor (e.g. aperture, spectral band, and various efficiencies), the expected background, and the atmosphere transmission to inform the optimal settings for the near-infrared and midwave IR cameras on the Cast Glance aircraft. Once these data were collected, calibrated, edited, registered and co-added we formed both 2-D maps of the scene in the above units and 3-D maps of the bottom surface in temperature that could be compared with not only the initial inputs but also thermocouple data from the Shuttle itself. The 3-D temperature mapping process was based on the initial radiance modeling process. Here temperatures were guessed for each node in a well-resolved 3-D framework, a radiance model was produced and compared to the processed imagery, and corrections to the temperature were estimated until the iterative process converged. This process did very well in characterizing the temperature structure of the large asymmetric boundary layer transition the covered much of the starboard bottom surface of STS-119 Discovery. Both internally estimated accuracies and differences with CFD models and thermocouple measurements are at most a few percent. The technique did less well characterizing the temperature structure of the turbulent wedge behind the trip due to limitations in understanding the true sensor resolution. (Note: Those less inclined to read the entire paper are encouraged to read an Executive Summary provided at the end.)

Extending systems thinking in planning and evaluation using group concept mapping and system dynamics to tackle complex problems.

PubMed

Hassmiller Lich, Kristen; Urban, Jennifer Brown; Frerichs, Leah; Dave, Gaurav

2017-02-01

Group concept mapping (GCM) has been successfully employed in program planning and evaluation for over 25 years. The broader set of systems thinking methodologies (of which GCM is one), have only recently found their way into the field. We present an overview of systems thinking emerging from a system dynamics (SD) perspective, and illustrate the potential synergy between GCM and SD. As with GCM, participatory processes are frequently employed when building SD models; however, it can be challenging to engage a large and diverse group of stakeholders in the iterative cycles of divergent thinking and consensus building required, while maintaining a broad perspective on the issue being studied. GCM provides a compelling resource for overcoming this challenge, by richly engaging a diverse set of stakeholders in broad exploration, structuring, and prioritization. SD provides an opportunity to extend GCM findings by embedding constructs in a testable hypothesis (SD model) describing how system structure and changes in constructs affect outcomes over time. SD can be used to simulate the hypothesized dynamics inherent in GCM concept maps. We illustrate the potential of the marriage of these methodologies in a case study of BECOMING, a federally-funded program aimed at strengthening the cross-sector system of care for youth with severe emotional disturbances. Copyright © 2016 Elsevier Ltd. All rights reserved.

Iterative Transform Phase Diversity: An Image-Based Object and Wavefront Recovery

NASA Technical Reports Server (NTRS)

Smith, Jeffrey

2012-01-01

The Iterative Transform Phase Diversity algorithm is designed to solve the problem of recovering the wavefront in the exit pupil of an optical system and the object being imaged. This algorithm builds upon the robust convergence capability of Variable Sampling Mapping (VSM), in combination with the known success of various deconvolution algorithms. VSM is an alternative method for enforcing the amplitude constraints of a Misell-Gerchberg-Saxton (MGS) algorithm. When provided the object and additional optical parameters, VSM can accurately recover the exit pupil wavefront. By combining VSM and deconvolution, one is able to simultaneously recover the wavefront and the object.

Rigorous-two-Steps scheme of TRIPOLI-4® Monte Carlo code validation for shutdown dose rate calculation

NASA Astrophysics Data System (ADS)

Jaboulay, Jean-Charles; Brun, Emeric; Hugot, François-Xavier; Huynh, Tan-Dat; Malouch, Fadhel; Mancusi, Davide; Tsilanizara, Aime

2017-09-01

After fission or fusion reactor shutdown the activated structure emits decay photons. For maintenance operations the radiation dose map must be established in the reactor building. Several calculation schemes have been developed to calculate the shutdown dose rate. These schemes are widely developed in fusion application and more precisely for the ITER tokamak. This paper presents the rigorous-two-steps scheme implemented at CEA. It is based on the TRIPOLI-4® Monte Carlo code and the inventory code MENDEL. The ITER shutdown dose rate benchmark has been carried out, results are in a good agreement with the other participant.

Convergence Time towards Periodic Orbits in Discrete Dynamical Systems

PubMed Central

San Martín, Jesús; Porter, Mason A.

2014-01-01

We investigate the convergence towards periodic orbits in discrete dynamical systems. We examine the probability that a randomly chosen point converges to a particular neighborhood of a periodic orbit in a fixed number of iterations, and we use linearized equations to examine the evolution near that neighborhood. The underlying idea is that points of stable periodic orbit are associated with intervals. We state and prove a theorem that details what regions of phase space are mapped into these intervals (once they are known) and how many iterations are required to get there. We also construct algorithms that allow our theoretical results to be implemented successfully in practice. PMID:24736594

Computer-Assisted Concept Mapping: Visual Aids for Knowledge Construction.

PubMed

Mammen, Jennifer R

2016-07-01

Concept mapping is a visual representation of ideas that facilitates critical thinking and is applicable to many areas of nursing education. Computer-assisted concept maps are more flexible and less constrained than traditional paper methods, allowing for analysis and synthesis of complex topics and larger amounts of data. Ability to iteratively revise and collaboratively create computerized maps can contribute to enhanced interpersonal learning. However, there is limited awareness of free software that can support these types of applications. This educational brief examines affordances and limitations of computer-assisted concept maps and reviews free software for development of complex, collaborative malleable maps. Free software, such as VUE, XMind, MindMaple, and others, can substantially contribute to the utility of concept mapping for nursing education. Computerized concept-mapping is an important tool for nursing and is likely to hold greater benefit for students and faculty than traditional pen-and-paper methods alone. [J Nurs Educ. 2016;55(7):403-406.]. Copyright 2016, SLACK Incorporated.

Steady state numerical solutions for determining the location of MEMS on projectile

NASA Astrophysics Data System (ADS)

Abiprayu, K.; Abdigusna, M. F. F.; Gunawan, P. H.

2018-03-01

This paper is devoted to compare the numerical solutions for the steady and unsteady state heat distribution model on projectile. Here, the best location for installing of the MEMS on the projectile based on the surface temperature is investigated. Numerical iteration methods, Jacobi and Gauss-Seidel have been elaborated to solve the steady state heat distribution model on projectile. The results using Jacobi and Gauss-Seidel are shown identical but the discrepancy iteration cost for each methods is gained. Using Jacobi’s method, the iteration cost is 350 iterations. Meanwhile, using Gauss-Seidel 188 iterations are obtained, faster than the Jacobi’s method. The comparison of the simulation by steady state model and the unsteady state model by a reference is shown satisfying. Moreover, the best candidate for installing MEMS on projectile is observed at pointT(10, 0) which has the lowest temperature for the other points. The temperature using Jacobi and Gauss-Seidel for scenario 1 and 2 atT(10, 0) are 307 and 309 Kelvin respectively.

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

NASA Astrophysics Data System (ADS)

Loughman, Robert; Bhartia, Pawan K.; Chen, Zhong; Xu, Philippe; Nyaku, Ernest; Taha, Ghassan

2018-05-01

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss-Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

Bridging the Nomothetic and Idiographic Approaches to the Analysis of Clinical Data

PubMed Central

Beltz, Adriene M.; Wright, Aidan G. C.; Sprague, Briana N.; Molenaar, Peter C. M.

2016-01-01

The nomothetic approach (i.e., the study of interindividual variation) dominates analyses of clinical data, even though its assumption of homogeneity across people and time is often violated. The idiographic approach (i.e., the study of intraindividual variation) is best suited for analyses of heterogeneous clinical data, but its person-specific methods and results have been criticized as unwieldy. Group iterative multiple model estimation (GIMME) combines the assets of the nomothetic and idiographic approaches by creating person-specific maps that contain a group-level structure. The maps show how intensively measured variables predict and are predicted by each other at different time scales. In this article, GIMME is introduced conceptually and mathematically, and then applied to an empirical data set containing the negative affect, detachment, disinhibition, and hostility composite ratings from the daily diaries of 25 individuals with personality pathology. Results are discussed with the aim of elucidating GIMME's potential for clinical research and practice. PMID:27165092

Simultaneous source and attenuation reconstruction in SPECT using ballistic and single scattering data

NASA Astrophysics Data System (ADS)

Courdurier, M.; Monard, F.; Osses, A.; Romero, F.

2015-09-01

In medical single-photon emission computed tomography (SPECT) imaging, we seek to simultaneously obtain the internal radioactive sources and the attenuation map using not only ballistic measurements but also first-order scattering measurements and assuming a very specific scattering regime. The problem is modeled using the radiative transfer equation by means of an explicit non-linear operator that gives the ballistic and scattering measurements as a function of the radioactive source and attenuation distributions. First, by differentiating this non-linear operator we obtain a linearized inverse problem. Then, under regularity hypothesis for the source distribution and attenuation map and considering small attenuations, we rigorously prove that the linear operator is invertible and we compute its inverse explicitly. This allows proof of local uniqueness for the non-linear inverse problem. Finally, using the previous inversion result for the linear operator, we propose a new type of iterative algorithm for simultaneous source and attenuation recovery for SPECT based on the Neumann series and a Newton-Raphson algorithm.

A terracing operator for physical property mapping with potential field data

USGS Publications Warehouse

Cordell, L.; McCafferty, A.E.

1989-01-01

The terracing operator works iteratively on gravity or magnetic data, using the sense of the measured field's local curvature, to produce a field comprised of uniform domains separated by abrupt domain boundaries. The result is crudely proportional to a physical-property function defined in one (profile case) or two (map case) horizontal dimensions. This result can be extended to a physical-property model if its behavior in the third (vertical) dimension is defined, either arbitrarily or on the basis of the local geologic situation. The terracing algorithm is computationally fast and appropriate to use with very large digital data sets. The terracing operator was applied separately to aeromagnetic and gravity data from a 136km x 123km area in eastern Kansas. Results provide a reasonable good physical representation of both the gravity and the aeromagnetic data. Superposition of the results from the two data sets shows many areas of agreement that can be referenced to geologic features within the buried Precambrian crystalline basement. -from Authors

CAS2D: FORTRAN program for nonrotating blade-to-blade, steady, potential transonic cascade flows

NASA Technical Reports Server (NTRS)

Dulikravich, D. S.

1980-01-01

An exact, full-potential-equation (FPE) model for the steady, irrotational, homentropic and homoenergetic flow of a compressible, homocompositional, inviscid fluid through two dimensional planar cascades of airfoils was derived, together with its appropriate boundary conditions. A computer program, CAS2D, was developed that numerically solves an artificially time-dependent form of the actual FPE. The governing equation was discretized by using type-dependent, rotated finite differencing and the finite area technique. The flow field was discretized by providing a boundary-fitted, nonuniform computational mesh. The mesh was generated by using a sequence of conforming mapping, nonorthogonal coordinate stretching, and local, isoparametric, bilinear mapping functions. The discretized form of the FPE was solved iteratively by using successive line overrelaxation. The possible isentropic shocks were correctly captured by adding explicitly an artificial viscosity in a conservative form. In addition, a three-level consecutive, mesh refinement feature makes CAS2D a reliable and fast algorithm for the analysis of transonic, two dimensional cascade flows.

Measure accurately, Act rapidly, and Partner with patients: An intuitive and practical three-part framework to guide efforts to improve hypertension control.

PubMed

Boonyasai, Romsai T; Rakotz, Michael K; Lubomski, Lisa H; Daniel, Donna M; Marsteller, Jill A; Taylor, Kathryn S; Cooper, Lisa A; Hasan, Omar; Wynia, Matthew K

2017-07-01

Hypertension is the leading cause of cardiovascular disease in the United States and worldwide. It also provides a useful model for team-based chronic disease management. This article describes the M.A.P. checklists: a framework to help practice teams summarize best practices for providing coordinated, evidence-based care to patients with hypertension. Consisting of three domains-Measure Accurately; Act Rapidly; and Partner With Patients, Families, and Communities-the checklists were developed by a team of clinicians, hypertension experts, and quality improvement experts through a multistep process that combined literature review, iterative feedback from a panel of internationally recognized experts, and pilot testing among a convenience sample of primary care practices in two states. In contrast to many guidelines, the M.A.P. checklists specifically target practice teams, instead of individual clinicians, and are designed to be brief, cognitively easy to consume and recall, and accessible to healthcare workers from a range of professional backgrounds. ©2017 Wiley Periodicals, Inc.

Road displacement model based on structural mechanics

NASA Astrophysics Data System (ADS)

Lu, Xiuqin; Guo, Qingsheng; Zhang, Yi

2006-10-01

Spatial conflict resolution is an important part of cartographic generalization, and it can deal with the problems of having too much information competing for too little space, while feature displacement is a primary operator of map generalization, which aims at resolving the spatial conflicts between neighbor objects especially road features. Considering the road object, this paper explains an idea of displacement based on structural mechanics. In view of spatial conflict problem after road symbolization, it is the buffer zones that are used to detect conflicts, then we focus on each conflicting region, with the finite element method, taking every triangular element for analysis, listing stiffness matrix, gathering system equations and calculating with iteration strategy, and we give the solution to road symbol conflicts. Being like this until all the conflicts in conflicting regions are solved, then we take the whole map into consideration again, conflicts are detected by reusing the buffer zones and solved by displacement operator, so as to all of them are handled.

Mapping the Drude polarizable force field onto a multipole and induced dipole model

NASA Astrophysics Data System (ADS)

Huang, Jing; Simmonett, Andrew C.; Pickard, Frank C.; MacKerell, Alexander D.; Brooks, Bernard R.

2017-10-01

The induced dipole and the classical Drude oscillator represent two major approaches for the explicit inclusion of electronic polarizability into force field-based molecular modeling and simulations. In this work, we explore the equivalency of these two models by comparing condensed phase properties computed using the Drude force field and a multipole and induced dipole (MPID) model. Presented is an approach to map the electrostatic model optimized in the context of the Drude force field onto the MPID model. Condensed phase simulations on water and 15 small model compounds show that without any reparametrization, the MPID model yields properties similar to the Drude force field with both models yielding satisfactory reproduction of a range of experimental values and quantum mechanical data. Our results illustrate that the Drude oscillator model and the point induced dipole model are different representations of essentially the same physical model. However, results indicate the presence of small differences between the use of atomic multipoles and off-center charge sites. Additionally, results on the use of dispersion particle mesh Ewald further support its utility for treating long-range Lennard Jones dispersion contributions in the context of polarizable force fields. The main motivation in demonstrating the transferability of parameters between the Drude and MPID models is that the more than 15 years of development of the Drude polarizable force field can now be used with MPID formalism without the need for dual-thermostat integrators nor self-consistent iterations. This opens up a wide range of new methodological opportunities for polarizable models.

Analytical three-point Dixon method: With applications for spiral water-fat imaging.

PubMed

Wang, Dinghui; Zwart, Nicholas R; Li, Zhiqiang; Schär, Michael; Pipe, James G

2016-02-01

The goal of this work is to present a new three-point analytical approach with flexible even or uneven echo increments for water-fat separation and to evaluate its feasibility with spiral imaging. Two sets of possible solutions of water and fat are first found analytically. Then, two field maps of the B0 inhomogeneity are obtained by linear regression. The initial identification of the true solution is facilitated by the root-mean-square error of the linear regression and the incorporation of a fat spectrum model. The resolved field map after a region-growing algorithm is refined iteratively for spiral imaging. The final water and fat images are recalculated using a joint water-fat separation and deblurring algorithm. Successful implementations were demonstrated with three-dimensional gradient-echo head imaging and single breathhold abdominal imaging. Spiral, high-resolution T1 -weighted brain images were shown with comparable sharpness to the reference Cartesian images. With appropriate choices of uneven echo increments, it is feasible to resolve the aliasing of the field map voxel-wise. High-quality water-fat spiral imaging can be achieved with the proposed approach. © 2015 Wiley Periodicals, Inc.

Compartmentalized Low-Rank Recovery for High-Resolution Lipid Unsuppressed MRSI

PubMed Central

Bhattacharya, Ipshita; Jacob, Mathews

2017-01-01

Purpose To introduce a novel algorithm for the recovery of high-resolution magnetic resonance spectroscopic imaging (MRSI) data with minimal lipid leakage artifacts, from dual-density spiral acquisition. Methods The reconstruction of MRSI data from dual-density spiral data is formulated as a compartmental low-rank recovery problem. The MRSI dataset is modeled as the sum of metabolite and lipid signals, each of which is support limited to the brain and extracranial regions, respectively, in addition to being orthogonal to each other. The reconstruction problem is formulated as an optimization problem, which is solved using iterative reweighted nuclear norm minimization. Results The comparisons of the scheme against dual-resolution reconstruction algorithm on numerical phantom and in vivo datasets demonstrate the ability of the scheme to provide higher spatial resolution and lower lipid leakage artifacts. The experiments demonstrate the ability of the scheme to recover the metabolite maps, from lipid unsuppressed datasets with echo time (TE)=55 ms. Conclusion The proposed reconstruction method and data acquisition strategy provide an efficient way to achieve high-resolution metabolite maps without lipid suppression. This algorithm would be beneficial for fast metabolic mapping and extension to multislice acquisitions. PMID:27851875

Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm

PubMed Central

2014-01-01

Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. PMID:25431584

Modelling of edge localised modes and edge localised mode control [Modelling of ELMs and ELM control

DOE PAGES

Huijsmans, G. T. A.; Chang, C. S.; Ferraro, N.; ...

2015-02-07

Edge Localised Modes (ELMs) in ITER Q = 10 H-mode plasmas are likely to lead to large transient heat loads to the divertor. In order to avoid an ELM induced reduction of the divertor lifetime, the large ELM energy losses need to be controlled. In ITER, ELM control is foreseen using magnetic field perturbations created by in-vessel coils and the injection of small D2 pellets. ITER plasmas are characterised by low collisionality at a high density (high fraction of the Greenwald density limit). These parameters cannot simultaneously be achieved in current experiments. Thus, the extrapolation of the ELM properties andmore » the requirements for ELM control in ITER relies on the development of validated physics models and numerical simulations. Here, we describe the modelling of ELMs and ELM control methods in ITER. The aim of this paper is not a complete review on the subject of ELM and ELM control modelling but rather to describe the current status and discuss open issues.« less

A Novel Real-Time Reference Key Frame Scan Matching Method.

PubMed

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-05-07

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions' environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Climate Voyager: An Iteratively Built Information and Visualization Tool for At-Risk Climate Communities

NASA Astrophysics Data System (ADS)

Terando, A. J.; Lascurain, A.; Aldridge, H. D.; Davis, C.

2016-12-01

Climate Voyager provides an innovative way to visualize both large-scale and local climate change projections using a three-map layout and time series plot. This product includes a suite of tools designed to assist with climate risk and opportunity assessments, including changes in average seasonal conditions and the capability to evaluate a variety of different decision-relevant thresholds (e.g. changes in extreme temperature occurrence). Each tool summarizes output from 20 downscaled global climate models and contains a historical average for comparison with the spread of projected future outcomes. The Climate Voyager website is interactive, allowing users to explore both regional and location-specific guidance for two Representative Concentration Pathways (RCPs) and four future 20-year time periods. By presenting climate model projections and measures of uncertainty of specific parameters beyond just annual temperatures and precipitation, Climate Voyager can help a wide variety of decision makers plan for climate changes that may affect them. We present a case study in which a new module was developed within Climate Voyager for use by Tribes and native communities in the eastern U.S. to help make informed resource decisions. In this first attempt, Ramps (Allium tricoccum), a plant species of great cultural significance, was incorporated through consultation with the tribal organization. We will also discuss the process of engagement employed with end-users and the potential to make the Climate Voyager interface an iterative, co-produced process to enhance the usability of climate model information for adaptation planning.

Modeling the Lyα Forest in Collisionless Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorini, Daniele; Oñorbe, José; Lukić, Zarija

2016-08-11

Cosmological hydrodynamic simulations can accurately predict the properties of the intergalactic medium (IGM), but only under the condition of retaining the high spatial resolution necessary to resolve density fluctuations in the IGM. This resolution constraint prohibits simulating large volumes, such as those probed by BOSS and future surveys, like DESI and 4MOST. To overcome this limitation, we present in this paper "Iteratively Matched Statistics" (IMS), a novel method to accurately model the Lyα forest with collisionless N-body simulations, where the relevant density fluctuations are unresolved. We use a small-box, high-resolution hydrodynamic simulation to obtain the probability distribution function (PDF) andmore » the power spectrum of the real-space Lyα forest flux. These two statistics are iteratively mapped onto a pseudo-flux field of an N-body simulation, which we construct from the matter density. We demonstrate that our method can reproduce the PDF, line of sight and 3D power spectra of the Lyα forest with good accuracy (7%, 4%, and 7% respectively). We quantify the performance of the commonly used Gaussian smoothing technique and show that it has significantly lower accuracy (20%–80%), especially for N-body simulations with achievable mean inter-particle separations in large-volume simulations. Finally, in addition, we show that IMS produces reasonable and smooth spectra, making it a powerful tool for modeling the IGM in large cosmological volumes and for producing realistic "mock" skies for Lyα forest surveys.« less

MODELING THE Ly α FOREST IN COLLISIONLESS SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sorini, Daniele; Oñorbe, José; Hennawi, Joseph F.

2016-08-20

Cosmological hydrodynamic simulations can accurately predict the properties of the intergalactic medium (IGM), but only under the condition of retaining the high spatial resolution necessary to resolve density fluctuations in the IGM. This resolution constraint prohibits simulating large volumes, such as those probed by BOSS and future surveys, like DESI and 4MOST. To overcome this limitation, we present “Iteratively Matched Statistics” (IMS), a novel method to accurately model the Ly α forest with collisionless N -body simulations, where the relevant density fluctuations are unresolved. We use a small-box, high-resolution hydrodynamic simulation to obtain the probability distribution function (PDF) and themore » power spectrum of the real-space Ly α forest flux. These two statistics are iteratively mapped onto a pseudo-flux field of an N -body simulation, which we construct from the matter density. We demonstrate that our method can reproduce the PDF, line of sight and 3D power spectra of the Ly α forest with good accuracy (7%, 4%, and 7% respectively). We quantify the performance of the commonly used Gaussian smoothing technique and show that it has significantly lower accuracy (20%–80%), especially for N -body simulations with achievable mean inter-particle separations in large-volume simulations. In addition, we show that IMS produces reasonable and smooth spectra, making it a powerful tool for modeling the IGM in large cosmological volumes and for producing realistic “mock” skies for Ly α forest surveys.« less

Assessment of Ice Shape Roughness Using a Self-Orgainizing Map Approach

NASA Technical Reports Server (NTRS)

Mcclain, Stephen T.; Kreeger, Richard E.

2013-01-01

Self-organizing maps are neural-network techniques for representing noisy, multidimensional data aligned along a lower-dimensional and nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. Prior investigations of ice shapes have focused on using self-organizing maps to characterize mean ice forms. The Icing Research Branch has recently acquired a high resolution three dimensional scanner system capable of resolving ice shape surface roughness. A method is presented for the evaluation of surface roughness variations using high-resolution surface scans based on a self-organizing map representation of the mean ice shape. The new method is demonstrated for 1) an 18-in. NACA 23012 airfoil 2 AOA just after the initial ice coverage of the leading 5 of the suction surface of the airfoil, 2) a 21-in. NACA 0012 at 0AOA following coverage of the leading 10 of the airfoil surface, and 3) a cold-soaked 21-in.NACA 0012 airfoil without ice. The SOM method resulted in descriptions of the statistical coverage limits and a quantitative representation of early stages of ice roughness formation on the airfoils. Limitations of the SOM method are explored, and the uncertainty limits of the method are investigated using the non-iced NACA 0012 airfoil measurements.

Toward accelerating landslide mapping with interactive machine learning techniques

NASA Astrophysics Data System (ADS)

Stumpf, André; Lachiche, Nicolas; Malet, Jean-Philippe; Kerle, Norman; Puissant, Anne

2013-04-01

Despite important advances in the development of more automated methods for landslide mapping from optical remote sensing images, the elaboration of inventory maps after major triggering events still remains a tedious task. Image classification with expert defined rules typically still requires significant manual labour for the elaboration and adaption of rule sets for each particular case. Machine learning algorithm, on the contrary, have the ability to learn and identify complex image patterns from labelled examples but may require relatively large amounts of training data. In order to reduce the amount of required training data active learning has evolved as key concept to guide the sampling for applications such as document classification, genetics and remote sensing. The general underlying idea of most active learning approaches is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and/or the data structure to iteratively select the most valuable samples that should be labelled by the user and added in the training set. With relatively few queries and labelled samples, an active learning strategy should ideally yield at least the same accuracy than an equivalent classifier trained with many randomly selected samples. Our study was dedicated to the development of an active learning approach for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. The developed approach is a region-based query heuristic that enables to guide the user attention towards few compact spatial batches rather than distributed points resulting in time savings of 50% and more compared to standard active learning techniques. The approach was tested with multi-temporal and multi-sensor satellite images capturing recent large scale triggering events in Brazil and China and demonstrated balanced user's and producer's accuracies between 74% and 80%. The assessment also included an experimental evaluation of the uncertainties of manual mappings from multiple experts and demonstrated strong relationships between the uncertainty of the experts and the machine learning model.

Bifurcations of 2-Periodic Nonautonomous Stunted Tent Systems

NASA Astrophysics Data System (ADS)

Silva, L.; Rocha, J. Leonel; Silva, M. T.

2017-06-01

In this paper, we will consider a family of 2-periodic nonautonomous dynamical systems, generated by the alternate iteration of two stunted tent maps and study its bifurcation skeleton. We will describe the bifurcation phenomena along and around the bones accomplished with the combinatorial data furnished by the respective symbolic dynamics.

Identification of Stochastically Perturbed Autonomous Systems from Temporal Sequences of Probability Density Functions

NASA Astrophysics Data System (ADS)

Nie, Xiaokai; Luo, Jingjing; Coca, Daniel; Birkin, Mark; Chen, Jing

2018-03-01

The paper introduces a method for reconstructing one-dimensional iterated maps that are driven by an external control input and subjected to an additive stochastic perturbation, from sequences of probability density functions that are generated by the stochastic dynamical systems and observed experimentally.

Iterative updating of model error for Bayesian inversion

NASA Astrophysics Data System (ADS)

Calvetti, Daniela; Dunlop, Matthew; Somersalo, Erkki; Stuart, Andrew

2018-02-01

In computational inverse problems, it is common that a detailed and accurate forward model is approximated by a computationally less challenging substitute. The model reduction may be necessary to meet constraints in computing time when optimization algorithms are used to find a single estimate, or to speed up Markov chain Monte Carlo (MCMC) calculations in the Bayesian framework. The use of an approximate model introduces a discrepancy, or modeling error, that may have a detrimental effect on the solution of the ill-posed inverse problem, or it may severely distort the estimate of the posterior distribution. In the Bayesian paradigm, the modeling error can be considered as a random variable, and by using an estimate of the probability distribution of the unknown, one may estimate the probability distribution of the modeling error and incorporate it into the inversion. We introduce an algorithm which iterates this idea to update the distribution of the model error, leading to a sequence of posterior distributions that are demonstrated empirically to capture the underlying truth with increasing accuracy. Since the algorithm is not based on rejections, it requires only limited full model evaluations. We show analytically that, in the linear Gaussian case, the algorithm converges geometrically fast with respect to the number of iterations when the data is finite dimensional. For more general models, we introduce particle approximations of the iteratively generated sequence of distributions; we also prove that each element of the sequence converges in the large particle limit under a simplifying assumption. We show numerically that, as in the linear case, rapid convergence occurs with respect to the number of iterations. Additionally, we show through computed examples that point estimates obtained from this iterative algorithm are superior to those obtained by neglecting the model error.

Imaging Electric Properties of Biological Tissues by RF Field Mapping in MRI

PubMed Central

Zhang, Xiaotong; Zhu, Shanan; He, Bin

2010-01-01

The electric properties (EPs) of biological tissue, i.e., the electric conductivity and permittivity, can provide important information in the diagnosis of various diseases. The EPs also play an important role in specific absorption rate (SAR) calculation, a major concern in high-field Magnetic Resonance Imaging (MRI), as well as in non-medical areas such as wireless-telecommunications. The high-field MRI system is accompanied by significant wave propagation effects, and the radio frequency (RF) radiation is dependent on the EPs of biological tissue. Based on the measurement of the active transverse magnetic component of the applied RF field (known as B1-mapping technique), we propose a dual-excitation algorithm, which uses two sets of measured B1 data to noninvasively reconstruct the electric properties of biological tissues. The Finite Element Method (FEM) was utilized in three-dimensional (3D) modeling and B1 field calculation. A series of computer simulations were conducted to evaluate the feasibility and performance of the proposed method on a 3D head model within a transverse electromagnetic (TEM) coil and a birdcage (BC) coil. Using a TEM coil, when noise free, the reconstructed EP distribution of tissues in the brain has relative errors of 12% ∼ 28% and correlated coefficients of greater than 0.91. Compared with other B1-mapping based reconstruction algorithms, our approach provides superior performance without the need for iterative computations. The present simulation results suggest that good reconstruction of electric properties from B1 mapping can be achieved. PMID:20129847

A Hybrid Neuro-Fuzzy Model For Integrating Large Earth-Science Datasets

NASA Astrophysics Data System (ADS)

Porwal, A.; Carranza, J.; Hale, M.

2004-12-01

A GIS-based hybrid neuro-fuzzy approach to integration of large earth-science datasets for mineral prospectivity mapping is described. It implements a Takagi-Sugeno type fuzzy inference system in the framework of a four-layered feed-forward adaptive neural network. Each unique combination of the datasets is considered a feature vector whose components are derived by knowledge-based ordinal encoding of the constituent datasets. A subset of feature vectors with a known output target vector (i.e., unique conditions known to be associated with either a mineralized or a barren location) is used for the training of an adaptive neuro-fuzzy inference system. Training involves iterative adjustment of parameters of the adaptive neuro-fuzzy inference system using a hybrid learning procedure for mapping each training vector to its output target vector with minimum sum of squared error. The trained adaptive neuro-fuzzy inference system is used to process all feature vectors. The output for each feature vector is a value that indicates the extent to which a feature vector belongs to the mineralized class or the barren class. These values are used to generate a prospectivity map. The procedure is demonstrated by an application to regional-scale base metal prospectivity mapping in a study area located in the Aravalli metallogenic province (western India). A comparison of the hybrid neuro-fuzzy approach with pure knowledge-driven fuzzy and pure data-driven neural network approaches indicates that the former offers a superior method for integrating large earth-science datasets for predictive spatial mathematical modelling.

The Chlamydomonas genome project: a decade on

PubMed Central

Blaby, Ian K.; Blaby-Haas, Crysten; Tourasse, Nicolas; Hom, Erik F. Y.; Lopez, David; Aksoy, Munevver; Grossman, Arthur; Umen, James; Dutcher, Susan; Porter, Mary; King, Stephen; Witman, George; Stanke, Mario; Harris, Elizabeth H.; Goodstein, David; Grimwood, Jane; Schmutz, Jeremy; Vallon, Olivier; Merchant, Sabeeha S.; Prochnik, Simon

2014-01-01

The green alga Chlamydomonas reinhardtii is a popular unicellular organism for studying photosynthesis, cilia biogenesis and micronutrient homeostasis. Ten years since its genome project was initiated, an iterative process of improvements to the genome and gene predictions has propelled this organism to the forefront of the “omics” era. Housed at Phytozome, the Joint Genome Institute’s (JGI) plant genomics portal, the most up-to-date genomic data include a genome arranged on chromosomes and high-quality gene models with alternative splice forms supported by an abundance of RNA-Seq data. Here, we present the past, present and future of Chlamydomonas genomics. Specifically, we detail progress on genome assembly and gene model refinement, discuss resources for gene annotations, functional predictions and locus ID mapping between versions and, importantly, outline a standardized framework for naming genes. PMID:24950814

Magnetic and magnetocaloric properties of the exactly solvable mixed-spin Ising model on a decorated triangular lattice in a magnetic field

NASA Astrophysics Data System (ADS)

Gálisová, Lucia; Strečka, Jozef

2018-05-01

The ground state, zero-temperature magnetization process, critical behaviour and isothermal entropy change of the mixed-spin Ising model on a decorated triangular lattice in a magnetic field are exactly studied after performing the generalized decoration-iteration mapping transformation. It is shown that both the inverse and conventional magnetocaloric effect can be found near the absolute zero temperature. The former phenomenon can be found in a vicinity of the discontinuous phase transitions and their crossing points, while the latter one occurs in some paramagnetic phases due to a spin frustration to be present at zero magnetic field. The inverse magnetocaloric effect can also be detected slightly above continuous phase transitions following the power-law dependence | - ΔSisomin | ∝hn, where n depends basically on the ground-state spin ordering.

An updated geospatial liquefaction model for global application

USGS Publications Warehouse

Zhu, Jing; Baise, Laurie G.; Thompson, Eric M.

2017-01-01

We present an updated geospatial approach to estimation of earthquake-induced liquefaction from globally available geospatial proxies. Our previous iteration of the geospatial liquefaction model was based on mapped liquefaction surface effects from four earthquakes in Christchurch, New Zealand, and Kobe, Japan, paired with geospatial explanatory variables including slope-derived VS30, compound topographic index, and magnitude-adjusted peak ground acceleration from ShakeMap. The updated geospatial liquefaction model presented herein improves the performance and the generality of the model. The updates include (1) expanding the liquefaction database to 27 earthquake events across 6 countries, (2) addressing the sampling of nonliquefaction for incomplete liquefaction inventories, (3) testing interaction effects between explanatory variables, and (4) overall improving model performance. While we test 14 geospatial proxies for soil density and soil saturation, the most promising geospatial parameters are slope-derived VS30, modeled water table depth, distance to coast, distance to river, distance to closest water body, and precipitation. We found that peak ground velocity (PGV) performs better than peak ground acceleration (PGA) as the shaking intensity parameter. We present two models which offer improved performance over prior models. We evaluate model performance using the area under the curve under the Receiver Operating Characteristic (ROC) curve (AUC) and the Brier score. The best-performing model in a coastal setting uses distance to coast but is problematic for regions away from the coast. The second best model, using PGV, VS30, water table depth, distance to closest water body, and precipitation, performs better in noncoastal regions and thus is the model we recommend for global implementation.

Validation of the thermal transport model used for ITER startup scenario predictions with DIII-D experimental data

DOE PAGES

Casper, T. A.; Meyer, W. H.; Jackson, G. L.; ...

2010-12-08

We are exploring characteristics of ITER startup scenarios in similarity experiments conducted on the DIII-D Tokamak. In these experiments, we have validated scenarios for the ITER current ramp up to full current and developed methods to control the plasma parameters to achieve stability. Predictive simulations of ITER startup using 2D free-boundary equilibrium and 1D transport codes rely on accurate estimates of the electron and ion temperature profiles that determine the electrical conductivity and pressure profiles during the current rise. Here we present results of validation studies that apply the transport model used by the ITER team to DIII-D discharge evolutionmore » and comparisons with data from our similarity experiments.« less

Source apportionment for fine particulate matter in a Chinese city using an improved gas-constrained method and comparison with multiple receptor models.

PubMed

Shi, Guoliang; Liu, Jiayuan; Wang, Haiting; Tian, Yingze; Wen, Jie; Shi, Xurong; Feng, Yinchang; Ivey, Cesunica E; Russell, Armistead G

2018-02-01

PM 2.5 is one of the most studied atmospheric pollutants due to its adverse impacts on human health and welfare and the environment. An improved model (the chemical mass balance gas constraint-Iteration: CMBGC-Iteration) is proposed and applied to identify source categories and estimate source contributions of PM 2.5. The CMBGC-Iteration model uses the ratio of gases to PM as constraints and considers the uncertainties of source profiles and receptor datasets, which is crucial information for source apportionment. To apply this model, samples of PM 2.5 were collected at Tianjin, a megacity in northern China. The ambient PM 2.5 dataset, source information, and gas-to-particle ratios (such as SO 2 /PM 2.5 , CO/PM 2.5 , and NOx/PM 2.5 ratios) were introduced into the CMBGC-Iteration to identify the potential sources and their contributions. Six source categories were identified by this model and the order based on their contributions to PM 2.5 was as follows: secondary sources (30%), crustal dust (25%), vehicle exhaust (16%), coal combustion (13%), SOC (7.6%), and cement dust (0.40%). In addition, the same dataset was also calculated by other receptor models (CMB, CMB-Iteration, CMB-GC, PMF, WALSPMF, and NCAPCA), and the results obtained were compared. Ensemble-average source impacts were calculated based on the seven source apportionment results: contributions of secondary sources (28%), crustal dust (20%), coal combustion (18%), vehicle exhaust (17%), SOC (11%), and cement dust (1.3%). The similar results of CMBGC-Iteration and ensemble method indicated that CMBGC-Iteration can produce relatively appropriate results. Copyright © 2017 Elsevier Ltd. All rights reserved.

The importance of mechanisms for the evolution of cooperation

PubMed Central

van den Berg, Pieter; Weissing, Franz J.

2015-01-01

Studies aimed at explaining the evolution of phenotypic traits have often solely focused on fitness considerations, ignoring underlying mechanisms. In recent years, there has been an increasing call for integrating mechanistic perspectives in evolutionary considerations, but it is not clear whether and how mechanisms affect the course and outcome of evolution. To study this, we compare four mechanistic implementations of two well-studied models for the evolution of cooperation, the Iterated Prisoner's Dilemma (IPD) game and the Iterated Snowdrift (ISD) game. Behavioural strategies are either implemented by a 1 : 1 genotype–phenotype mapping or by a simple neural network. Moreover, we consider two different scenarios for the effect of mutations. The same set of strategies is feasible in all four implementations, but the probability that a given strategy arises owing to mutation is largely dependent on the behavioural and genetic architecture. Our individual-based simulations show that this has major implications for the evolutionary outcome. In the ISD, different evolutionarily stable strategies are predominant in the four implementations, while in the IPD each implementation creates a characteristic dynamical pattern. As a consequence, the evolved average level of cooperation is also strongly dependent on the underlying mechanism. We argue that our findings are of general relevance for the evolution of social behaviour, pleading for the integration of a mechanistic perspective in models of social evolution. PMID:26246554

RF Sheath-Enhanced Plasma Surface Interaction Studies using Beryllium Optical Emission Spectroscopy in JET ITER-Like Wall

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarici, G.; Klepper, C Christopher; Colas, L.

A dedicated study on JET-ILW, deploying two types of ICRH antennas and spectroscopic observation spots at two outboard, beryllium limiters, has provided insight on long-range (up to 6m) RFenhanced plasma-surface interactions (RF-PSI) due to near-antenna electric fields. To aid in the interpretation of optical emission measurements of these effects, the antenna near-fields are computed using the TOPICA code, specifically run for the ITER-like antenna (ILA); similar modelling already existed for the standard JET antennas (A2). In the experiment, both antennas were operated in current drive mode, as RF-PSI tends to be higher in this phasing and at similar power (∼0.5more » MW). When sweeping the edge magnetic field pitch angle, peaked RF-PSI effects, in the form of 2-4 fold increase in the local Be source,are consistently measured with the observation spots magnetically connect to regions of TOPICAL-calculated high near-fields, particularly at the near-antenna limiters. It is also found that similar RF-PSI effects are produced by the two types of antenna on similarly distant limiters. Although this mapping of calculated near-fields to enhanced RF-PSI gives only qualitative interpretion of the data, the present dataset is expected to provide a sound experimental basis for emerging RF sheath simulation model validation.« less

FIREFLY (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code

NASA Astrophysics Data System (ADS)

Wilkinson, David M.; Maraston, Claudia; Goddard, Daniel; Thomas, Daniel; Parikh, Taniya

2017-12-01

We present a new spectral fitting code, FIREFLY, for deriving the stellar population properties of stellar systems. FIREFLY is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that FIREFLY is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1

MAP: an iterative experimental design methodology for the optimization of catalytic search space structure modeling.

PubMed

Baumes, Laurent A

2006-01-01

One of the main problems in high-throughput research for materials is still the design of experiments. At early stages of discovery programs, purely exploratory methodologies coupled with fast screening tools should be employed. This should lead to opportunities to find unexpected catalytic results and identify the "groups" of catalyst outputs, providing well-defined boundaries for future optimizations. However, very few new papers deal with strategies that guide exploratory studies. Mostly, traditional designs, homogeneous covering, or simple random samplings are exploited. Typical catalytic output distributions exhibit unbalanced datasets for which an efficient learning is hardly carried out, and interesting but rare classes are usually unrecognized. Here is suggested a new iterative algorithm for the characterization of the search space structure, working independently of learning processes. It enhances recognition rates by transferring catalysts to be screened from "performance-stable" space zones to "unsteady" ones which necessitate more experiments to be well-modeled. The evaluation of new algorithm attempts through benchmarks is compulsory due to the lack of past proofs about their efficiency. The method is detailed and thoroughly tested with mathematical functions exhibiting different levels of complexity. The strategy is not only empirically evaluated, the effect or efficiency of sampling on future Machine Learning performances is also quantified. The minimum sample size required by the algorithm for being statistically discriminated from simple random sampling is investigated.

WE-EF-207-07: Dual Energy CT with One Full Scan and a Second Sparse-View Scan Using Structure Preserving Iterative Reconstruction (SPIR)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, T; Zhu, L

Purpose: Conventional dual energy CT (DECT) reconstructs CT and basis material images from two full-size projection datasets with different energy spectra. To relax the data requirement, we propose an iterative DECT reconstruction algorithm using one full scan and a second sparse-view scan by utilizing redundant structural information of the same object acquired at two different energies. Methods: We first reconstruct a full-scan CT image using filtered-backprojection (FBP) algorithm. The material similarities of each pixel with other pixels are calculated by an exponential function about pixel value differences. We assume that the material similarities of pixels remains in the second CTmore » scan, although pixel values may vary. An iterative method is designed to reconstruct the second CT image from reduced projections. Under the data fidelity constraint, the algorithm minimizes the L2 norm of the difference between pixel value and its estimation, which is the average of other pixel values weighted by their similarities. The proposed algorithm, referred to as structure preserving iterative reconstruction (SPIR), is evaluated on physical phantoms. Results: On the Catphan600 phantom, SPIR-based DECT method with a second 10-view scan reduces the noise standard deviation of a full-scan FBP CT reconstruction by a factor of 4 with well-maintained spatial resolution, while iterative reconstruction using total-variation regularization (TVR) degrades the spatial resolution at the same noise level. The proposed method achieves less than 1% measurement difference on electron density map compared with the conventional two-full-scan DECT. On an anthropomorphic pediatric phantom, our method successfully reconstructs the complicated vertebra structures and decomposes bone and soft tissue. Conclusion: We develop an effective method to reduce the number of views and therefore data acquisition in DECT. We show that SPIR-based DECT using one full scan and a second 10-view scan can provide high-quality DECT images and accurate electron density maps as conventional two-full-scan DECT.« less

Collaborative damage mapping for emergency response: the role of Cognitive Systems Engineering

NASA Astrophysics Data System (ADS)

Kerle, N.; Hoffman, R. R.

2013-01-01

Remote sensing is increasingly used to assess disaster damage, traditionally by professional image analysts. A recent alternative is crowdsourcing by volunteers experienced in remote sensing, using internet-based mapping portals. We identify a range of problems in current approaches, including how volunteers can best be instructed for the task, ensuring that instructions are accurately understood and translate into valid results, or how the mapping scheme must be adapted for different map user needs. The volunteers, the mapping organizers, and the map users all perform complex cognitive tasks, yet little is known about the actual information needs of the users. We also identify problematic assumptions about the capabilities of the volunteers, principally related to the ability to perform the mapping, and to understand mapping instructions unambiguously. We propose that any robust scheme for collaborative damage mapping must rely on Cognitive Systems Engineering and its principal method, Cognitive Task Analysis (CTA), to understand the information and decision requirements of the map and image users, and how the volunteers can be optimally instructed and their mapping contributions merged into suitable map products. We recommend an iterative approach involving map users, remote sensing specialists, cognitive systems engineers and instructional designers, as well as experimental psychologists.

Iteration and Prototyping in Creating Technical Specifications.

ERIC Educational Resources Information Center

Flynt, John P.

1994-01-01

Claims that the development process for computer software can be greatly aided by the writers of specifications if they employ basic iteration and prototyping techniques. Asserts that computer software configuration management practices provide ready models for iteration and prototyping. (HB)

Analysis of LH Launcher Arrays (Like the ITER One) Using the TOPLHA Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maggiora, R.; Milanesio, D.; Vecchi, G.

2009-11-26

TOPLHA (Torino Polytechnic Lower Hybrid Antenna) code is an innovative tool for the 3D/1D simulation of Lower Hybrid (LH) antennas, i.e. accounting for realistic 3D waveguides geometry and for accurate 1D plasma models, and without restrictions on waveguide shape, including curvature. This tool provides a detailed performances prediction of any LH launcher, by computing the antenna scattering parameters, the current distribution, electric field maps and power spectra for any user-specified waveguide excitation. In addition, a fully parallelized and multi-cavity version of TOPLHA permits the analysis of large and complex waveguide arrays in a reasonable simulation time. A detailed analysis ofmore » the performances of the proposed ITER LH antenna geometry has been carried out, underlining the strong dependence of the antenna input parameters with respect to plasma conditions. A preliminary optimization of the antenna dimensions has also been accomplished. Electric current distribution on conductors, electric field distribution at the interface with plasma, and power spectra have been calculated as well. The analysis shows the strong capabilities of the TOPLHA code as a predictive tool and its usefulness to LH launcher arrays detailed design.« less

A decision support model for investment on P2P lending platform.

PubMed

Zeng, Xiangxiang; Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace-Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone.

A decision support model for investment on P2P lending platform

PubMed Central

Liu, Li; Leung, Stephen; Du, Jiangze; Wang, Xun; Li, Tao

2017-01-01

Peer-to-peer (P2P) lending, as a novel economic lending model, has triggered new challenges on making effective investment decisions. In a P2P lending platform, one lender can invest N loans and a loan may be accepted by M investors, thus forming a bipartite graph. Basing on the bipartite graph model, we built an iteration computation model to evaluate the unknown loans. To validate the proposed model, we perform extensive experiments on real-world data from the largest American P2P lending marketplace—Prosper. By comparing our experimental results with those obtained by Bayes and Logistic Regression, we show that our computation model can help borrowers select good loans and help lenders make good investment decisions. Experimental results also show that the Logistic classification model is a good complement to our iterative computation model, which motivates us to integrate the two classification models. The experimental results of the hybrid classification model demonstrate that the logistic classification model and our iteration computation model are complementary to each other. We conclude that the hybrid model (i.e., the integration of iterative computation model and Logistic classification model) is more efficient and stable than the individual model alone. PMID:28877234

A Discrete Global Grid System Programming Language Using MapReduce

NASA Astrophysics Data System (ADS)

Peterson, P.; Shatz, I.

2016-12-01

A discrete global grid system (DGGS) is a powerful mechanism for storing and integrating geospatial information. As a "pixelization" of the Earth, many image processing techniques lend themselves to the transformation of data values referenced to the DGGS cells. It has been shown that image algebra, as an example, and advanced algebra, like Fast Fourier Transformation, can be used on the DGGS tiling structure for geoprocessing and spatial analysis. MapReduce has been shown to provide advantages for processing and generating large data sets within distributed and parallel computing. The DGGS structure is ideally suited for big distributed Earth data. We proposed that basic expressions could be created to form the atoms of a generalized DGGS language using the MapReduce programming model. We created three very efficient expressions: Selectors (aka filter) - A selection function that generate a set of cells, cell collections, or geometries; Calculators (aka map) - A computational function (including quantization of raw measurements and data sources) that generate values in a DGGS cell; and Aggregators (aka reduce) - A function that generate spatial statistics from cell values within a cell. We found that these three basic MapReduce operations along with a forth function, the Iterator, for horizontal and vertical traversing of any DGGS structure, provided simple building block resulting in very efficient operations and processes that could be used with any DGGS. We provide examples and a demonstration of their effectiveness using the ISEA3H DGGS on the PYXIS Studio.

Potential mapping with charged-particle beams

NASA Technical Reports Server (NTRS)

Robinson, J. W.; Tillery, D. G.

1979-01-01

Experimental methods of mapping the equipotential surfaces near some structure of interest rely on the detection of charged particles which have traversed the regions of interest and are detected remotely. One method is the measurement of ion energies for ions created at a point of interest and expelled from the region by the fields. The ion energy at the detector in eV corresponds to the potential where the ion was created. An ionizing beam forms the ions from background neutrals. The other method is to inject charged particles into the region of interest and to locate their exit points. A set of several trajectories becomes a data base for a systematic mapping technique. An iterative solution of a boundary value problem establishes concepts and limitations pertaining to the mapping problem.

A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Warner, Harumi; Cress, Jill

2009-01-01

A new map of standardized, mesoscale (tens to thousands of hectares) terrestrial ecosystems for the conterminous United States was developed by using a biophysical stratification approach. The ecosystems delineated in this top-down, deductive modeling effort are described in NatureServe's classification of terrestrial ecological systems of the United States. The ecosystems were mapped as physically distinct areas and were associated with known distributions of vegetation assemblages by using a standardized methodology first developed for South America. This approach follows the geoecosystems concept of R.J. Huggett and the ecosystem geography approach of R.G. Bailey. Unique physical environments were delineated through a geospatial combination of national data layers for biogeography, bioclimate, surficial materials lithology, land surface forms, and topographic moisture potential. Combining these layers resulted in a comprehensive biophysical stratification of the conterminous United States, which produced 13,482 unique biophysical areas. These were considered as fundamental units of ecosystem structure and were aggregated into 419 potential terrestrial ecosystems. The ecosystems classification effort preceded the mapping effort and involved the independent development of diagnostic criteria, descriptions, and nomenclature for describing expert-derived ecological systems. The aggregation and labeling of the mapped ecosystem structure units into the ecological systems classification was accomplished in an iterative, expert-knowledge-based process using automated rulesets for identifying ecosystems on the basis of their biophysical and biogeographic attributes. The mapped ecosystems, at a 30-meter base resolution, represent an improvement in spatial and thematic (class) resolution over existing ecoregionalizations and are useful for a variety of applications, including ecosystem services assessments, climate change impact studies, biodiversity conservation, and resource management.

Composition of web services using Markov decision processes and dynamic programming.

PubMed

Uc-Cetina, Víctor; Moo-Mena, Francisco; Hernandez-Ucan, Rafael

2015-01-01

We propose a Markov decision process model for solving the Web service composition (WSC) problem. Iterative policy evaluation, value iteration, and policy iteration algorithms are used to experimentally validate our approach, with artificial and real data. The experimental results show the reliability of the model and the methods employed, with policy iteration being the best one in terms of the minimum number of iterations needed to estimate an optimal policy, with the highest Quality of Service attributes. Our experimental work shows how the solution of a WSC problem involving a set of 100,000 individual Web services and where a valid composition requiring the selection of 1,000 services from the available set can be computed in the worst case in less than 200 seconds, using an Intel Core i5 computer with 6 GB RAM. Moreover, a real WSC problem involving only 7 individual Web services requires less than 0.08 seconds, using the same computational power. Finally, a comparison with two popular reinforcement learning algorithms, sarsa and Q-learning, shows that these algorithms require one or two orders of magnitude and more time than policy iteration, iterative policy evaluation, and value iteration to handle WSC problems of the same complexity.

Overview of the JET results in support to ITER

NASA Astrophysics Data System (ADS)

Litaudon, X.; Abduallev, S.; Abhangi, M.; Abreu, P.; Afzal, M.; Aggarwal, K. M.; Ahlgren, T.; Ahn, J. H.; Aho-Mantila, L.; Aiba, N.; Airila, M.; Albanese, R.; Aldred, V.; Alegre, D.; Alessi, E.; Aleynikov, P.; Alfier, A.; Alkseev, A.; Allinson, M.; Alper, B.; Alves, E.; Ambrosino, G.; Ambrosino, R.; Amicucci, L.; Amosov, V.; Andersson Sundén, E.; Angelone, M.; Anghel, M.; Angioni, C.; Appel, L.; Appelbee, C.; Arena, P.; Ariola, M.; Arnichand, H.; Arshad, S.; Ash, A.; Ashikawa, N.; Aslanyan, V.; Asunta, O.; Auriemma, F.; Austin, Y.; Avotina, L.; Axton, M. D.; Ayres, C.; Bacharis, M.; Baciero, A.; Baião, D.; Bailey, S.; Baker, A.; Balboa, I.; Balden, M.; Balshaw, N.; Bament, R.; Banks, J. W.; Baranov, Y. F.; Barnard, M. A.; Barnes, D.; Barnes, M.; Barnsley, R.; Baron Wiechec, A.; Barrera Orte, L.; Baruzzo, M.; Basiuk, V.; Bassan, M.; Bastow, R.; Batista, A.; Batistoni, P.; Baughan, R.; Bauvir, B.; Baylor, L.; Bazylev, B.; Beal, J.; Beaumont, P. S.; Beckers, M.; Beckett, B.; Becoulet, A.; Bekris, N.; Beldishevski, M.; Bell, K.; Belli, F.; Bellinger, M.; Belonohy, É.; Ben Ayed, N.; Benterman, N. A.; Bergsåker, H.; Bernardo, J.; Bernert, M.; Berry, M.; Bertalot, L.; Besliu, C.; Beurskens, M.; Bieg, B.; Bielecki, J.; Biewer, T.; Bigi, M.; Bílková, P.; Binda, F.; Bisoffi, A.; Bizarro, J. P. S.; Björkas, C.; Blackburn, J.; Blackman, K.; Blackman, T. R.; Blanchard, P.; Blatchford, P.; Bobkov, V.; Boboc, A.; Bodnár, G.; Bogar, O.; Bolshakova, I.; Bolzonella, T.; Bonanomi, N.; Bonelli, F.; Boom, J.; Booth, J.; Borba, D.; Borodin, D.; Borodkina, I.; Botrugno, A.; Bottereau, C.; Boulting, P.; Bourdelle, C.; Bowden, M.; Bower, C.; Bowman, C.; Boyce, T.; Boyd, C.; Boyer, H. J.; Bradshaw, J. M. A.; Braic, V.; Bravanec, R.; Breizman, B.; Bremond, S.; Brennan, P. D.; Breton, S.; Brett, A.; Brezinsek, S.; Bright, M. D. J.; Brix, M.; Broeckx, W.; Brombin, M.; Brosławski, A.; Brown, D. P. D.; Brown, M.; Bruno, E.; Bucalossi, J.; Buch, J.; Buchanan, J.; Buckley, M. A.; Budny, R.; Bufferand, H.; Bulman, M.; Bulmer, N.; Bunting, P.; Buratti, P.; Burckhart, A.; Buscarino, A.; Busse, A.; Butler, N. K.; Bykov, I.; Byrne, J.; Cahyna, P.; Calabrò, G.; Calvo, I.; Camenen, Y.; Camp, P.; Campling, D. C.; Cane, J.; Cannas, B.; Capel, A. J.; Card, P. J.; Cardinali, A.; Carman, P.; Carr, M.; Carralero, D.; Carraro, L.; Carvalho, B. B.; Carvalho, I.; Carvalho, P.; Casson, F. J.; Castaldo, C.; Catarino, N.; Caumont, J.; Causa, F.; Cavazzana, R.; Cave-Ayland, K.; Cavinato, M.; Cecconello, M.; Ceccuzzi, S.; Cecil, E.; Cenedese, A.; Cesario, R.; Challis, C. D.; Chandler, M.; Chandra, D.; Chang, C. S.; Chankin, A.; Chapman, I. T.; Chapman, S. C.; Chernyshova, M.; Chitarin, G.; Ciraolo, G.; Ciric, D.; Citrin, J.; Clairet, F.; Clark, E.; Clark, M.; Clarkson, R.; Clatworthy, D.; Clements, C.; Cleverly, M.; Coad, J. P.; Coates, P. A.; Cobalt, A.; Coccorese, V.; Cocilovo, V.; Coda, S.; Coelho, R.; Coenen, J. W.; Coffey, I.; Colas, L.; Collins, S.; Conka, D.; Conroy, S.; Conway, N.; Coombs, D.; Cooper, D.; Cooper, S. R.; Corradino, C.; Corre, Y.; Corrigan, G.; Cortes, S.; Coster, D.; Couchman, A. S.; Cox, M. P.; Craciunescu, T.; Cramp, S.; Craven, R.; Crisanti, F.; Croci, G.; Croft, D.; Crombé, K.; Crowe, R.; Cruz, N.; Cseh, G.; Cufar, A.; Cullen, A.; Curuia, M.; Czarnecka, A.; Dabirikhah, H.; Dalgliesh, P.; Dalley, S.; Dankowski, J.; Darrow, D.; Davies, O.; Davis, W.; Day, C.; Day, I. E.; De Bock, M.; de Castro, A.; de la Cal, E.; de la Luna, E.; De Masi, G.; de Pablos, J. L.; De Temmerman, G.; De Tommasi, G.; de Vries, P.; Deakin, K.; Deane, J.; Degli Agostini, F.; Dejarnac, R.; Delabie, E.; den Harder, N.; Dendy, R. O.; Denis, J.; Denner, P.; Devaux, S.; Devynck, P.; Di Maio, F.; Di Siena, A.; Di Troia, C.; Dinca, P.; D'Inca, R.; Ding, B.; Dittmar, T.; Doerk, H.; Doerner, R. P.; Donné, T.; Dorling, S. E.; Dormido-Canto, S.; Doswon, S.; Douai, D.; Doyle, P. T.; Drenik, A.; Drewelow, P.; Drews, P.; Duckworth, Ph.; Dumont, R.; Dumortier, P.; Dunai, D.; Dunne, M.; Ďuran, I.; Durodié, F.; Dutta, P.; Duval, B. P.; Dux, R.; Dylst, K.; Dzysiuk, N.; Edappala, P. V.; Edmond, J.; Edwards, A. M.; Edwards, J.; Eich, Th.; Ekedahl, A.; El-Jorf, R.; Elsmore, C. G.; Enachescu, M.; Ericsson, G.; Eriksson, F.; Eriksson, J.; Eriksson, L. G.; Esposito, B.; Esquembri, S.; Esser, H. G.; Esteve, D.; Evans, B.; Evans, G. E.; Evison, G.; Ewart, G. D.; Fagan, D.; Faitsch, M.; Falie, D.; Fanni, A.; Fasoli, A.; Faustin, J. M.; Fawlk, N.; Fazendeiro, L.; Fedorczak, N.; Felton, R. C.; Fenton, K.; Fernades, A.; Fernandes, H.; Ferreira, J.; Fessey, J. A.; Février, O.; Ficker, O.; Field, A.; Fietz, S.; Figueiredo, A.; Figueiredo, J.; Fil, A.; Finburg, P.; Firdaouss, M.; Fischer, U.; Fittill, L.; Fitzgerald, M.; Flammini, D.; Flanagan, J.; Fleming, C.; Flinders, K.; Fonnesu, N.; Fontdecaba, J. M.; Formisano, A.; Forsythe, L.; Fortuna, L.; Fortuna-Zalesna, E.; Fortune, M.; Foster, S.; Franke, T.; Franklin, T.; Frasca, M.; Frassinetti, L.; Freisinger, M.; Fresa, R.; Frigione, D.; Fuchs, V.; Fuller, D.; Futatani, S.; Fyvie, J.; Gál, K.; Galassi, D.; Gałązka, K.; Galdon-Quiroga, J.; Gallagher, J.; Gallart, D.; Galvão, R.; Gao, X.; Gao, Y.; Garcia, J.; Garcia-Carrasco, A.; García-Muñoz, M.; Gardarein, J.-L.; Garzotti, L.; Gaudio, P.; Gauthier, E.; Gear, D. F.; Gee, S. J.; Geiger, B.; Gelfusa, M.; Gerasimov, S.; Gervasini, G.; Gethins, M.; Ghani, Z.; Ghate, M.; Gherendi, M.; Giacalone, J. C.; Giacomelli, L.; Gibson, C. S.; Giegerich, T.; Gil, C.; Gil, L.; Gilligan, S.; Gin, D.; Giovannozzi, E.; Girardo, J. B.; Giroud, C.; Giruzzi, G.; Glöggler, S.; Godwin, J.; Goff, J.; Gohil, P.; Goloborod'ko, V.; Gomes, R.; Gonçalves, B.; Goniche, M.; Goodliffe, M.; Goodyear, A.; Gorini, G.; Gosk, M.; Goulding, R.; Goussarov, A.; Gowland, R.; Graham, B.; Graham, M. E.; Graves, J. P.; Grazier, N.; Grazier, P.; Green, N. R.; Greuner, H.; Grierson, B.; Griph, F. S.; Grisolia, C.; Grist, D.; Groth, M.; Grove, R.; Grundy, C. N.; Grzonka, J.; Guard, D.; Guérard, C.; Guillemaut, C.; Guirlet, R.; Gurl, C.; Utoh, H. H.; Hackett, L. J.; Hacquin, S.; Hagar, A.; Hager, R.; Hakola, A.; Halitovs, M.; Hall, S. J.; Hallworth Cook, S. P.; Hamlyn-Harris, C.; Hammond, K.; Harrington, C.; Harrison, J.; Harting, D.; Hasenbeck, F.; Hatano, Y.; Hatch, D. R.; Haupt, T. D. V.; Hawes, J.; Hawkes, N. C.; Hawkins, J.; Hawkins, P.; Haydon, P. W.; Hayter, N.; Hazel, S.; Heesterman, P. J. L.; Heinola, K.; Hellesen, C.; Hellsten, T.; Helou, W.; Hemming, O. N.; Hender, T. C.; Henderson, M.; Henderson, S. S.; Henriques, R.; Hepple, D.; Hermon, G.; Hertout, P.; Hidalgo, C.; Highcock, E. G.; Hill, M.; Hillairet, J.; Hillesheim, J.; Hillis, D.; Hizanidis, K.; Hjalmarsson, A.; Hobirk, J.; Hodille, E.; Hogben, C. H. A.; Hogeweij, G. M. D.; Hollingsworth, A.; Hollis, S.; Homfray, D. A.; Horáček, J.; Hornung, G.; Horton, A. R.; Horton, L. D.; Horvath, L.; Hotchin, S. P.; Hough, M. R.; Howarth, P. J.; Hubbard, A.; Huber, A.; Huber, V.; Huddleston, T. M.; Hughes, M.; Huijsmans, G. T. A.; Hunter, C. L.; Huynh, P.; Hynes, A. M.; Iglesias, D.; Imazawa, N.; Imbeaux, F.; Imríšek, M.; Incelli, M.; Innocente, P.; Irishkin, M.; Ivanova-Stanik, I.; Jachmich, S.; Jacobsen, A. S.; Jacquet, P.; Jansons, J.; Jardin, A.; Järvinen, A.; Jaulmes, F.; Jednoróg, S.; Jenkins, I.; Jeong, C.; Jepu, I.; Joffrin, E.; Johnson, R.; Johnson, T.; Johnston, Jane; Joita, L.; Jones, G.; Jones, T. T. C.; Hoshino, K. K.; Kallenbach, A.; Kamiya, K.; Kaniewski, J.; Kantor, A.; Kappatou, A.; Karhunen, J.; Karkinsky, D.; Karnowska, I.; Kaufman, M.; Kaveney, G.; Kazakov, Y.; Kazantzidis, V.; Keeling, D. L.; Keenan, T.; Keep, J.; Kempenaars, M.; Kennedy, C.; Kenny, D.; Kent, J.; Kent, O. N.; Khilkevich, E.; Kim, H. T.; Kim, H. S.; Kinch, A.; king, C.; King, D.; King, R. F.; Kinna, D. J.; Kiptily, V.; Kirk, A.; Kirov, K.; Kirschner, A.; Kizane, G.; Klepper, C.; Klix, A.; Knight, P.; Knipe, S. J.; Knott, S.; Kobuchi, T.; Köchl, F.; Kocsis, G.; Kodeli, I.; Kogan, L.; Kogut, D.; Koivuranta, S.; Kominis, Y.; Köppen, M.; Kos, B.; Koskela, T.; Koslowski, H. R.; Koubiti, M.; Kovari, M.; Kowalska-Strzęciwilk, E.; Krasilnikov, A.; Krasilnikov, V.; Krawczyk, N.; Kresina, M.; Krieger, K.; Krivska, A.; Kruezi, U.; Książek, I.; Kukushkin, A.; Kundu, A.; Kurki-Suonio, T.; Kwak, S.; Kwiatkowski, R.; Kwon, O. J.; Laguardia, L.; Lahtinen, A.; Laing, A.; Lam, N.; Lambertz, H. T.; Lane, C.; Lang, P. T.; Lanthaler, S.; Lapins, J.; Lasa, A.; Last, J. R.; Łaszyńska, E.; Lawless, R.; Lawson, A.; Lawson, K. D.; Lazaros, A.; Lazzaro, E.; Leddy, J.; Lee, S.; Lefebvre, X.; Leggate, H. J.; Lehmann, J.; Lehnen, M.; Leichtle, D.; Leichuer, P.; Leipold, F.; Lengar, I.; Lennholm, M.; Lerche, E.; Lescinskis, A.; Lesnoj, S.; Letellier, E.; Leyland, M.; Leysen, W.; Li, L.; Liang, Y.; Likonen, J.; Linke, J.; Linsmeier, Ch.; Lipschultz, B.; Liu, G.; Liu, Y.; Lo Schiavo, V. P.; Loarer, T.; Loarte, A.; Lobel, R. C.; Lomanowski, B.; Lomas, P. J.; Lönnroth, J.; López, J. M.; López-Razola, J.; Lorenzini, R.; Losada, U.; Lovell, J. J.; Loving, A. B.; Lowry, C.; Luce, T.; Lucock, R. M. A.; Lukin, A.; Luna, C.; Lungaroni, M.; Lungu, C. P.; Lungu, M.; Lunniss, A.; Lupelli, I.; Lyssoivan, A.; Macdonald, N.; Macheta, P.; Maczewa, K.; Magesh, B.; Maget, P.; Maggi, C.; Maier, H.; Mailloux, J.; Makkonen, T.; Makwana, R.; Malaquias, A.; Malizia, A.; Manas, P.; Manning, A.; Manso, M. E.; Mantica, P.; Mantsinen, M.; Manzanares, A.; Maquet, Ph.; Marandet, Y.; Marcenko, N.; Marchetto, C.; Marchuk, O.; Marinelli, M.; Marinucci, M.; Markovič, T.; Marocco, D.; Marot, L.; Marren, C. A.; Marshal, R.; Martin, A.; Martin, Y.; Martín de Aguilera, A.; Martínez, F. J.; Martín-Solís, J. R.; Martynova, Y.; Maruyama, S.; Masiello, A.; Maslov, M.; Matejcik, S.; Mattei, M.; Matthews, G. F.; Maviglia, F.; Mayer, M.; Mayoral, M. L.; May-Smith, T.; Mazon, D.; Mazzotta, C.; McAdams, R.; McCarthy, P. J.; McClements, K. G.; McCormack, O.; McCullen, P. A.; McDonald, D.; McIntosh, S.; McKean, R.; McKehon, J.; Meadows, R. C.; Meakins, A.; Medina, F.; Medland, M.; Medley, S.; Meigh, S.; Meigs, A. G.; Meisl, G.; Meitner, S.; Meneses, L.; Menmuir, S.; Mergia, K.; Merrigan, I. R.; Mertens, Ph.; Meshchaninov, S.; Messiaen, A.; Meyer, H.; Mianowski, S.; Michling, R.; Middleton-Gear, D.; Miettunen, J.; Militello, F.; Militello-Asp, E.; Miloshevsky, G.; Mink, F.; Minucci, S.; Miyoshi, Y.; Mlynář, J.; Molina, D.; Monakhov, I.; Moneti, M.; Mooney, R.; Moradi, S.; Mordijck, S.; Moreira, L.; Moreno, R.; Moro, F.; Morris, A. W.; Morris, J.; Moser, L.; Mosher, S.; Moulton, D.; Murari, A.; Muraro, A.; Murphy, S.; Asakura, N. N.; Na, Y. S.; Nabais, F.; Naish, R.; Nakano, T.; Nardon, E.; Naulin, V.; Nave, M. F. F.; Nedzelski, I.; Nemtsev, G.; Nespoli, F.; Neto, A.; Neu, R.; Neverov, V. S.; Newman, M.; Nicholls, K. J.; Nicolas, T.; Nielsen, A. H.; Nielsen, P.; Nilsson, E.; Nishijima, D.; Noble, C.; Nocente, M.; Nodwell, D.; Nordlund, K.; Nordman, H.; Nouailletas, R.; Nunes, I.; Oberkofler, M.; Odupitan, T.; Ogawa, M. T.; O'Gorman, T.; Okabayashi, M.; Olney, R.; Omolayo, O.; O'Mullane, M.; Ongena, J.; Orsitto, F.; Orszagh, J.; Oswuigwe, B. I.; Otin, R.; Owen, A.; Paccagnella, R.; Pace, N.; Pacella, D.; Packer, L. W.; Page, A.; Pajuste, E.; Palazzo, S.; Pamela, S.; Panja, S.; Papp, P.; Paprok, R.; Parail, V.; Park, M.; Parra Diaz, F.; Parsons, M.; Pasqualotto, R.; Patel, A.; Pathak, S.; Paton, D.; Patten, H.; Pau, A.; Pawelec, E.; Soldan, C. Paz; Peackoc, A.; Pearson, I. J.; Pehkonen, S.-P.; Peluso, E.; Penot, C.; Pereira, A.; Pereira, R.; Pereira Puglia, P. P.; Perez von Thun, C.; Peruzzo, S.; Peschanyi, S.; Peterka, M.; Petersson, P.; Petravich, G.; Petre, A.; Petrella, N.; Petržilka, V.; Peysson, Y.; Pfefferlé, D.; Philipps, V.; Pillon, M.; Pintsuk, G.; Piovesan, P.; Pires dos Reis, A.; Piron, L.; Pironti, A.; Pisano, F.; Pitts, R.; Pizzo, F.; Plyusnin, V.; Pomaro, N.; Pompilian, O. G.; Pool, P. J.; Popovichev, S.; Porfiri, M. T.; Porosnicu, C.; Porton, M.; Possnert, G.; Potzel, S.; Powell, T.; Pozzi, J.; Prajapati, V.; Prakash, R.; Prestopino, G.; Price, D.; Price, M.; Price, R.; Prior, P.; Proudfoot, R.; Pucella, G.; Puglia, P.; Puiatti, M. E.; Pulley, D.; Purahoo, K.; Pütterich, Th.; Rachlew, E.; Rack, M.; Ragona, R.; Rainford, M. S. J.; Rakha, A.; Ramogida, G.; Ranjan, S.; Rapson, C. J.; Rasmussen, J. J.; Rathod, K.; Rattá, G.; Ratynskaia, S.; Ravera, G.; Rayner, C.; Rebai, M.; Reece, D.; Reed, A.; Réfy, D.; Regan, B.; Regaña, J.; Reich, M.; Reid, N.; Reimold, F.; Reinhart, M.; Reinke, M.; Reiser, D.; Rendell, D.; Reux, C.; Reyes Cortes, S. D. A.; Reynolds, S.; Riccardo, V.; Richardson, N.; Riddle, K.; Rigamonti, D.; Rimini, F. G.; Risner, J.; Riva, M.; Roach, C.; Robins, R. J.; Robinson, S. A.; Robinson, T.; Robson, D. W.; Roccella, R.; Rodionov, R.; Rodrigues, P.; Rodriguez, J.; Rohde, V.; Romanelli, F.; Romanelli, M.; Romanelli, S.; Romazanov, J.; Rowe, S.; Rubel, M.; Rubinacci, G.; Rubino, G.; Ruchko, L.; Ruiz, M.; Ruset, C.; Rzadkiewicz, J.; Saarelma, S.; Sabot, R.; Safi, E.; Sagar, P.; Saibene, G.; Saint-Laurent, F.; Salewski, M.; Salmi, A.; Salmon, R.; Salzedas, F.; Samaddar, D.; Samm, U.; Sandiford, D.; Santa, P.; Santala, M. I. K.; Santos, B.; Santucci, A.; Sartori, F.; Sartori, R.; Sauter, O.; Scannell, R.; Schlummer, T.; Schmid, K.; Schmidt, V.; Schmuck, S.; Schneider, M.; Schöpf, K.; Schwörer, D.; Scott, S. D.; Sergienko, G.; Sertoli, M.; Shabbir, A.; Sharapov, S. E.; Shaw, A.; Shaw, R.; Sheikh, H.; Shepherd, A.; Shevelev, A.; Shumack, A.; Sias, G.; Sibbald, M.; Sieglin, B.; Silburn, S.; Silva, A.; Silva, C.; Simmons, P. A.; Simpson, J.; Simpson-Hutchinson, J.; Sinha, A.; Sipilä, S. K.; Sips, A. C. C.; Sirén, P.; Sirinelli, A.; Sjöstrand, H.; Skiba, M.; Skilton, R.; Slabkowska, K.; Slade, B.; Smith, N.; Smith, P. G.; Smith, R.; Smith, T. J.; Smithies, M.; Snoj, L.; Soare, S.; Solano, E. R.; Somers, A.; Sommariva, C.; Sonato, P.; Sopplesa, A.; Sousa, J.; Sozzi, C.; Spagnolo, S.; Spelzini, T.; Spineanu, F.; Stables, G.; Stamatelatos, I.; Stamp, M. F.; Staniec, P.; Stankūnas, G.; Stan-Sion, C.; Stead, M. J.; Stefanikova, E.; Stepanov, I.; Stephen, A. V.; Stephen, M.; Stevens, A.; Stevens, B. D.; Strachan, J.; Strand, P.; Strauss, H. R.; Ström, P.; Stubbs, G.; Studholme, W.; Subba, F.; Summers, H. P.; Svensson, J.; Świderski, Ł.; Szabolics, T.; Szawlowski, M.; Szepesi, G.; Suzuki, T. T.; Tál, B.; Tala, T.; Talbot, A. R.; Talebzadeh, S.; Taliercio, C.; Tamain, P.; Tame, C.; Tang, W.; Tardocchi, M.; Taroni, L.; Taylor, D.; Taylor, K. A.; Tegnered, D.; Telesca, G.; Teplova, N.; Terranova, D.; Testa, D.; Tholerus, E.; Thomas, J.; Thomas, J. D.; Thomas, P.; Thompson, A.; Thompson, C.-A.; Thompson, V. K.; Thorne, L.; Thornton, A.; Thrysøe, A. S.; Tigwell, P. A.; Tipton, N.; Tiseanu, I.; Tojo, H.; Tokitani, M.; Tolias, P.; Tomeš, M.; Tonner, P.; Towndrow, M.; Trimble, P.; Tripsky, M.; Tsalas, M.; Tsavalas, P.; Tskhakaya jun, D.; Turner, I.; Turner, M. M.; Turnyanskiy, M.; Tvalashvili, G.; Tyrrell, S. G. J.; Uccello, A.; Ul-Abidin, Z.; Uljanovs, J.; Ulyatt, D.; Urano, H.; Uytdenhouwen, I.; Vadgama, A. P.; Valcarcel, D.; Valentinuzzi, M.; Valisa, M.; Vallejos Olivares, P.; Valovic, M.; Van De Mortel, M.; Van Eester, D.; Van Renterghem, W.; van Rooij, G. J.; Varje, J.; Varoutis, S.; Vartanian, S.; Vasava, K.; Vasilopoulou, T.; Vega, J.; Verdoolaege, G.; Verhoeven, R.; Verona, C.; Verona Rinati, G.; Veshchev, E.; Vianello, N.; Vicente, J.; Viezzer, E.; Villari, S.; Villone, F.; Vincenzi, P.; Vinyar, I.; Viola, B.; Vitins, A.; Vizvary, Z.; Vlad, M.; Voitsekhovitch, I.; Vondráček, P.; Vora, N.; Vu, T.; Pires de Sa, W. W.; Wakeling, B.; Waldon, C. W. F.; Walkden, N.; Walker, M.; Walker, R.; Walsh, M.; Wang, E.; Wang, N.; Warder, S.; Warren, R. J.; Waterhouse, J.; Watkins, N. W.; Watts, C.; Wauters, T.; Weckmann, A.; Weiland, J.; Weisen, H.; Weiszflog, M.; Wellstood, C.; West, A. T.; Wheatley, M. R.; Whetham, S.; Whitehead, A. M.; Whitehead, B. D.; Widdowson, A. M.; Wiesen, S.; Wilkinson, J.; Williams, J.; Williams, M.; Wilson, A. R.; Wilson, D. J.; Wilson, H. R.; Wilson, J.; Wischmeier, M.; Withenshaw, G.; Withycombe, A.; Witts, D. M.; Wood, D.; Wood, R.; Woodley, C.; Wray, S.; Wright, J.; Wright, J. C.; Wu, J.; Wukitch, S.; Wynn, A.; Xu, T.; Yadikin, D.; Yanling, W.; Yao, L.; Yavorskij, V.; Yoo, M. G.; Young, C.; Young, D.; Young, I. D.; Young, R.; Zacks, J.; Zagorski, R.; Zaitsev, F. S.; Zanino, R.; Zarins, A.; Zastrow, K. D.; Zerbini, M.; Zhang, W.; Zhou, Y.; Zilli, E.; Zoita, V.; Zoletnik, S.; Zychor, I.; JET Contributors

2017-10-01

The 2014-2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L-H power threshold in Deuterium and Hydrogen are given, stressing the importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H  =  1 at β N ~ 1.8 and n/n GW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D-T campaign and 14 MeV neutron calibration strategy are reviewed.

Ensemble Kalman Filter versus Ensemble Smoother for Data Assimilation in Groundwater Modeling

NASA Astrophysics Data System (ADS)

Li, L.; Cao, Z.; Zhou, H.

2017-12-01

Groundwater modeling calls for an effective and robust integrating method to fill the gap between the model and data. The Ensemble Kalman Filter (EnKF), a real-time data assimilation method, has been increasingly applied in multiple disciplines such as petroleum engineering and hydrogeology. In this approach, the groundwater models are sequentially updated using measured data such as hydraulic head and concentration data. As an alternative to the EnKF, the Ensemble Smoother (ES) was proposed with updating models using all the data together, and therefore needs a much less computational cost. To further improve the performance of the ES, an iterative ES was proposed for continuously updating the models by assimilating measurements together. In this work, we compare the performance of the EnKF, the ES and the iterative ES using a synthetic example in groundwater modeling. The hydraulic head data modeled on the basis of the reference conductivity field are utilized to inversely estimate conductivities at un-sampled locations. Results are evaluated in terms of the characterization of conductivity and groundwater flow and solute transport predictions. It is concluded that: (1) the iterative ES could achieve a comparable result with the EnKF, but needs a less computational cost; (2) the iterative ES has the better performance than the ES through continuously updating. These findings suggest that the iterative ES should be paid much more attention for data assimilation in groundwater modeling.

Registration of Heat Capacity Mapping Mission day and night images

NASA Technical Reports Server (NTRS)

Watson, K.; Hummer-Miller, S.; Sawatzky, D. L. (Principal Investigator)

1982-01-01

Neither iterative registration, using drainage intersection maps for control, nor cross correlation techniques were satisfactory in registering day and night HCMM imagery. A procedure was developed which registers the image pairs by selecting control points and mapping the night thermal image to the daytime thermal and reflectance images using an affine transformation on a 1300 by 1100 pixel image. The resulting image registration is accurate to better than two pixels (RMS) and does not exhibit the significant misregistration that was noted in the temperature-difference and thermal-inertia products supplied by NASA. The affine transformation was determined using simple matrix arithmetic, a step that can be performed rapidly on a minicomputer.

Period adding cascades: experiment and modeling in air bubbling.

PubMed

Pereira, Felipe Augusto Cardoso; Colli, Eduardo; Sartorelli, José Carlos

2012-03-01

Period adding cascades have been observed experimentally/numerically in the dynamics of neurons and pancreatic cells, lasers, electric circuits, chemical reactions, oceanic internal waves, and also in air bubbling. We show that the period adding cascades appearing in bubbling from a nozzle submerged in a viscous liquid can be reproduced by a simple model, based on some hydrodynamical principles, dealing with the time evolution of two variables, bubble position and pressure of the air chamber, through a system of differential equations with a rule of detachment based on force balance. The model further reduces to an iterating one-dimensional map giving the pressures at the detachments, where time between bubbles come out as an observable of the dynamics. The model has not only good agreement with experimental data, but is also able to predict the influence of the main parameters involved, like the length of the hose connecting the air supplier with the needle, the needle radius and the needle length.

Consistency of different tropospheric models and mapping functions for precise GNSS processing

NASA Astrophysics Data System (ADS)

Graffigna, Victoria; Hernández-Pajares, Manuel; García-Rigo, Alberto; Gende, Mauricio

2017-04-01

The TOmographic Model of the IONospheric electron content (TOMION) software implements a simultaneous precise geodetic and ionospheric modeling, which can be used to test new approaches for real-time precise GNSS modeling (positioning, ionospheric and tropospheric delays, clock errors, among others). In this work, the software is used to estimate the Zenith Tropospheric Delay (ZTD) emulating real time and its performance is evaluated through a comparative analysis with a built-in GIPSY estimation and IGS final troposphere product, exemplified in a two-day experiment performed in East Australia. Furthermore, the troposphere mapping function was upgraded from Niell to Vienna approach. On a first scenario, only forward processing was activated and the coordinates of the Wide Area GNSS network were loosely constrained, without fixing the carrier phase ambiguities, for both reference and rover receivers. On a second one, precise point positioning (PPP) was implemented, iterating for a fixed coordinates set for the second day. Comparisons between TOMION, IGS and GIPSY estimates have been performed and for the first one, IGS clocks and orbits were considered. The agreement with GIPSY results seems to be 10 times better than with the IGS final ZTD product, despite having considered IGS products for the computations. Hence, the subsequent analysis was carried out with respect to the GIPSY computations. The estimates show a typical bias of 2cm for the first strategy and of 7mm for PPP, in the worst cases. Moreover, Vienna mapping function showed in general a fairly better agreement than Niell one for both strategies. The RMS values' were found to be around 1cm for all studied situations, with a slightly fitter performance for the Niell one. Further improvement could be achieved for such estimations with coefficients for the Vienna mapping function calculated from raytracing as well as integrating meteorological comparative parameters.

An Overview of Plume Tracker: Mapping Volcanic Emissions with Interactive Radiative Transfer Modeling

NASA Astrophysics Data System (ADS)

Realmuto, V. J.; Berk, A.; Guiang, C.

2014-12-01

Infrared remote sensing is a vital tool for the study of volcanic plumes, and radiative transfer (RT) modeling is required to derive quantitative estimation of the sulfur dioxide (SO2), sulfate aerosol (SO4), and silicate ash (pulverized rock) content of these plumes. In the thermal infrared, we must account for the temperature, emissivity, and elevation of the surface beneath the plume, plume altitude and thickness, and local atmospheric temperature and humidity. Our knowledge of these parameters is never perfect, and interactive mapping allows us to evaluate the impact of these uncertainties on our estimates of plume composition. To enable interactive mapping, the Jet Propulsion Laboratory is collaborating with Spectral Sciences, Inc., (SSI) to develop the Plume Tracker toolkit. This project is funded by a NASA AIST Program Grant (AIST-11-0053) to SSI. Plume Tracker integrates (1) retrieval procedures for surface temperature and emissivity, SO2, NH3, or CH4 column abundance, and scaling factors for H2O vapor and O3 profiles, (2) a RT modeling engine based on MODTRAN, and (3) interactive visualization and analysis utilities under a single graphics user interface. The principal obstacle to interactive mapping is the computational overhead of the RT modeling engine. Under AIST-11-0053 we have achieved a 300-fold increase in the performance of the retrieval procedures through the use of indexed caches of model spectra, optimization of the minimization procedures, and scaling of the effects of surface temperature and emissivity on model radiance spectra. In the final year of AIST-11-0053 we will implement parallel processing to exploit multi-core CPUs and cluster computing, and optimize the RT engine to eliminate redundant calculations when iterating over a range of gas concentrations. These enhancements will result in an additional 8 - 12X increase in performance. In addition to the improvements in performance, we have improved the accuracy of the Plume Tracker retrievals through refinements in the description of surface emissivity and use of vector projection to define the misfit between model and observed spectra. Portions of this research were conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Serial turbo trellis coded modulation using a serially concatenated coder

NASA Technical Reports Server (NTRS)

Divsalar, Dariush (Inventor); Dolinar, Samuel J. (Inventor); Pollara, Fabrizio (Inventor)

2010-01-01

Serial concatenated trellis coded modulation (SCTCM) includes an outer coder, an interleaver, a recursive inner coder and a mapping element. The outer coder receives data to be coded and produces outer coded data. The interleaver permutes the outer coded data to produce interleaved data. The recursive inner coder codes the interleaved data to produce inner coded data. The mapping element maps the inner coded data to a symbol. The recursive inner coder has a structure which facilitates iterative decoding of the symbols at a decoder system. The recursive inner coder and the mapping element are selected to maximize the effective free Euclidean distance of a trellis coded modulator formed from the recursive inner coder and the mapping element. The decoder system includes a demodulation unit, an inner SISO (soft-input soft-output) decoder, a deinterleaver, an outer SISO decoder, and an interleaver.

A new computer approach to mixed feature classification for forestry application

NASA Technical Reports Server (NTRS)

Kan, E. P.

1976-01-01

A computer approach for mapping mixed forest features (i.e., types, classes) from computer classification maps is discussed. Mixed features such as mixed softwood/hardwood stands are treated as admixtures of softwood and hardwood areas. Large-area mixed features are identified and small-area features neglected when the nominal size of a mixed feature can be specified. The computer program merges small isolated areas into surrounding areas by the iterative manipulation of the postprocessing algorithm that eliminates small connected sets. For a forestry application, computer-classified LANDSAT multispectral scanner data of the Sam Houston National Forest were used to demonstrate the proposed approach. The technique was successful in cleaning the salt-and-pepper appearance of multiclass classification maps and in mapping admixtures of softwood areas and hardwood areas. However, the computer-mapped mixed areas matched very poorly with the ground truth because of inadequate resolution and inappropriate definition of mixed features.

Basin boundaries and focal points in a map coming from Bairstow's method.

PubMed

Gardini, Laura; Bischi, Gian-Italo; Fournier-Prunaret, Daniele

1999-06-01

This paper is devoted to the study of the global dynamical properties of a two-dimensional noninvertible map, with a denominator which can vanish, obtained by applying Bairstow's method to a cubic polynomial. It is shown that the complicated structure of the basins of attraction of the fixed points is due to the existence of singularities such as sets of nondefinition, focal points, and prefocal curves, which are specific to maps with a vanishing denominator, and have been recently introduced in the literature. Some global bifurcations that change the qualitative structure of the basin boundaries, are explained in terms of contacts among these singularities. The techniques used in this paper put in evidence some new dynamic behaviors and bifurcations, which are peculiar of maps with denominator; hence they can be applied to the analysis of other classes of maps coming from iterative algorithms (based on Newton's method, or others). (c) 1999 American Institute of Physics.

Inversion of Acoustic and Electromagnetic Recordings for Mapping Current Flow in Lightning Strikes

NASA Astrophysics Data System (ADS)

Anderson, J.; Johnson, J.; Arechiga, R. O.; Thomas, R. J.

2012-12-01

Acoustic recordings can be used to map current-carrying conduits in lightning strikes. Unlike stepped leaders, whose very high frequency (VHF) radio emissions have short (meter-scale) wavelengths and can be located by lightning-mapping arrays, current pulses emit longer (kilometer-scale) waves and cannot be mapped precisely by electromagnetic observations alone. While current pulses are constrained to conductive channels created by stepped leaders, these leaders often branch as they propagate, and most branches fail to carry current. Here, we present a method to use thunder recordings to map current pulses, and we apply it to acoustic and VHF data recorded in 2009 in the Magdalena mountains in central New Mexico, USA. Thunder is produced by rapid heating and expansion of the atmosphere along conductive channels in response to current flow, and therefore can be used to recover the geometry of the current-carrying channel. Toward this goal, we use VHF pulse maps to identify candidate conductive channels where we treat each channel as a superposition of finely-spaced acoustic point sources. We apply ray tracing in variable atmospheric structures to forward model the thunder that our microphone network would record for each candidate channel. Because multiple channels could potentially carry current, a non-linear inversion is performed to determine the acoustic source strength of each channel. For each combination of acoustic source strengths, synthetic thunder is modeled as a superposition of thunder signals produced by each channel, and a power envelope of this stack is then calculated. The inversion iteratively minimizes the misfit between power envelopes of recorded and modeled thunder. Because the atmospheric sound speed structure through which the waves propagate during these events is unknown, we repeat the procedure on many plausible atmospheres to find an optimal fit. We then determine the candidate channel, or channels, that minimizes residuals between synthetic and acoustic recordings. We demonstrate the usefulness of this method on both intracloud and cloud-to-ground strikes, and discuss factors affecting our ability to replicate recorded thunder.

ANOTHER LOOK AT THE FAST ITERATIVE SHRINKAGE/THRESHOLDING ALGORITHM (FISTA)*

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2017-01-01

This paper provides a new way of developing the “Fast Iterative Shrinkage/Thresholding Algorithm (FISTA)” [3] that is widely used for minimizing composite convex functions with a nonsmooth term such as the ℓ1 regularizer. In particular, this paper shows that FISTA corresponds to an optimized approach to accelerating the proximal gradient method with respect to a worst-case bound of the cost function. This paper then proposes a new algorithm that is derived by instead optimizing the step coefficients of the proximal gradient method with respect to a worst-case bound of the composite gradient mapping. The proof is based on the worst-case analysis called Performance Estimation Problem in [11]. PMID:29805242

Gaussian-input Gaussian mixture model for representing density maps and atomic models.

PubMed

Kawabata, Takeshi

2018-07-01

A new Gaussian mixture model (GMM) has been developed for better representations of both atomic models and electron microscopy 3D density maps. The standard GMM algorithm employs an EM algorithm to determine the parameters. It accepted a set of 3D points with weights, corresponding to voxel or atomic centers. Although the standard algorithm worked reasonably well; however, it had three problems. First, it ignored the size (voxel width or atomic radius) of the input, and thus it could lead to a GMM with a smaller spread than the input. Second, the algorithm had a singularity problem, as it sometimes stopped the iterative procedure due to a Gaussian function with almost zero variance. Third, a map with a large number of voxels required a long computation time for conversion to a GMM. To solve these problems, we have introduced a Gaussian-input GMM algorithm, which considers the input atoms or voxels as a set of Gaussian functions. The standard EM algorithm of GMM was extended to optimize the new GMM. The new GMM has identical radius of gyration to the input, and does not suddenly stop due to the singularity problem. For fast computation, we have introduced a down-sampled Gaussian functions (DSG) by merging neighboring voxels into an anisotropic Gaussian function. It provides a GMM with thousands of Gaussian functions in a short computation time. We also have introduced a DSG-input GMM: the Gaussian-input GMM with the DSG as the input. This new algorithm is much faster than the standard algorithm. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Extended estimator approach for 2×2 games and its mapping to the Ising Hamiltonian

NASA Astrophysics Data System (ADS)

Ariosa, D.; Fort, H.

2005-01-01

We consider a system of adaptive self-interested agents interacting by playing an iterated pairwise prisoner’s dilemma (PD) game. Each player has two options: either cooperate (C) or defect (D). Agents have no (long term) memory to reciprocate nor identifying tags to distinguish C from D. We show how their 16 possible elementary Markovian (one-step memory) strategies can be cast in a simple general formalism in terms of an estimator of expected utilities Δ* . This formalism is helpful to map a subset of these strategies into an Ising Hamiltonian in a straightforward way. This connection in turn serves to shed light on the evolution of the iterated games played by agents, which can represent a broad variety of individuals from firms of a market to species coexisting in an ecosystem. Additionally, this magnetic description may be useful to introduce noise in a natural and simple way. The equilibrium states reached by the system depend strongly on whether the dynamics are synchronous or asynchronous and also on the system connectivity.

A fast feedback method to design easy-molding freeform optical system with uniform illuminance and high light control efficiency.

PubMed

Hongtao, Li; Shichao, Chen; Yanjun, Han; Yi, Luo

2013-01-14

A feedback method combined with fitting technique based on variable separation mapping is proposed to design freeform optical systems for an extended LED source with prescribed illumination patterns, especially with uniform illuminance distribution. Feedback process performs well with extended sources, while fitting technique contributes not only to the decrease of pieces of sub-surfaces in discontinuous freeform lenses which may cause loss in manufacture, but also the reduction in the number of feedback iterations. It is proved that light control efficiency can be improved by 5%, while keeping a high uniformity of 82%, with only two feedback iterations and one fitting operation can improve. Furthermore, the polar angle θ and azimuthal angle φ is used to specify the light direction from the light source, and the (θ,φ)-(x,y) based mapping and feedback strategy makes sure that even few discontinuous sections along the equi-φ plane exist in the system, they are perpendicular to the base plane, making it eligible for manufacturing the surfaces using injection molding.

Reducing sick leave of Dutch vocational school students: adaptation of a sick leave protocol using the intervention mapping process.

PubMed

de Kroon, Marlou L A; Bulthuis, Jozien; Mulder, Wico; Schaafsma, Frederieke G; Anema, Johannes R

2016-12-01

Since the extent of sick leave and the problems of vocational school students are relatively large, we aimed to tailor a sick leave protocol at Dutch lower secondary education schools to the particular context of vocational schools. Four steps of the iterative process of Intervention Mapping (IM) to adapt this protocol were carried out: (1) performing a needs assessment and defining a program objective, (2) determining the performance and change objectives, (3) identifying theory-based methods and practical strategies and (4) developing a program plan. Interviews with students using structured questionnaires, in-depth interviews with relevant stakeholders, a literature research and, finally, a pilot implementation were carried out. A sick leave protocol was developed that was feasible and acceptable for all stakeholders. The main barriers for widespread implementation are time constraints in both monitoring and acting upon sick leave by school and youth health care. The iterative process of IM has shown its merits in the adaptation of the manual 'A quick return to school is much better' to a sick leave protocol for vocational school students.

Efficient full-chip SRAF placement using machine learning for best accuracy and improved consistency

NASA Astrophysics Data System (ADS)

Wang, Shibing; Baron, Stanislas; Kachwala, Nishrin; Kallingal, Chidam; Sun, Dezheng; Shu, Vincent; Fong, Weichun; Li, Zero; Elsaid, Ahmad; Gao, Jin-Wei; Su, Jing; Ser, Jung-Hoon; Zhang, Quan; Chen, Been-Der; Howell, Rafael; Hsu, Stephen; Luo, Larry; Zou, Yi; Zhang, Gary; Lu, Yen-Wen; Cao, Yu

2018-03-01

Various computational approaches from rule-based to model-based methods exist to place Sub-Resolution Assist Features (SRAF) in order to increase process window for lithography. Each method has its advantages and drawbacks, and typically requires the user to make a trade-off between time of development, accuracy, consistency and cycle time. Rule-based methods, used since the 90 nm node, require long development time and struggle to achieve good process window performance for complex patterns. Heuristically driven, their development is often iterative and involves significant engineering time from multiple disciplines (Litho, OPC and DTCO). Model-based approaches have been widely adopted since the 20 nm node. While the development of model-driven placement methods is relatively straightforward, they often become computationally expensive when high accuracy is required. Furthermore these methods tend to yield less consistent SRAFs due to the nature of the approach: they rely on a model which is sensitive to the pattern placement on the native simulation grid, and can be impacted by such related grid dependency effects. Those undesirable effects tend to become stronger when more iterations or complexity are needed in the algorithm to achieve required accuracy. ASML Brion has developed a new SRAF placement technique on the Tachyon platform that is assisted by machine learning and significantly improves the accuracy of full chip SRAF placement while keeping consistency and runtime under control. A Deep Convolutional Neural Network (DCNN) is trained using the target wafer layout and corresponding Continuous Transmission Mask (CTM) images. These CTM images have been fully optimized using the Tachyon inverse mask optimization engine. The neural network generated SRAF guidance map is then used to place SRAF on full-chip. This is different from our existing full-chip MB-SRAF approach which utilizes a SRAF guidance map (SGM) of mask sensitivity to improve the contrast of optical image at the target pattern edges. In this paper, we demonstrate that machine learning assisted SRAF placement can achieve a superior process window compared to the SGM model-based SRAF method, while keeping the full-chip runtime affordable, and maintain consistency of SRAF placement . We describe the current status of this machine learning assisted SRAF technique and demonstrate its application to full chip mask synthesis and discuss how it can extend the computational lithography roadmap.

Controle d'attitude d'un lanceur en phase atmospherique approche par applications gardiennes

NASA Astrophysics Data System (ADS)

Dubanchet, Vincent

In a first phase, the modelling process underlines the presence of highly time varying parameters during the ascent, due to a fast mass variation along with propellant consumption. Linearizing the dynamical equations at six main flight instants yields linear time invariant models to be considered during control design. Each of them is to be stabilized by one control law, while respecting given specifications. The synthesis becomes even more complex when the bending modes are taken into account. Moreover, scheduling appears necessary to deal with the time variations. Indeed it is shown that no single gain setting is able to respect all the specifications along the trajectory. Furthermore, increasing complexity when modelling a whole launch vehicle pushes one to consider the model's errors and uncertainties. They represent a major issue in this study since it is asked to ensure the nominal performances in a robust fashion. Owing to their properties, guardian maps appear to be the most suitable tool to deal with such a problem of scheduling with robust performances. In light of this, the development of synthesis methods based on guardian maps is the main contribution of the project. It appears that actual state of the art in this field is focused on theoretical issues, whereas practical ones could be improved. Two approches are presented in the memoire. The first one is based on a graphical approach consisting in drawing the vanishing locus of guardian maps. A program using image analysis techniques is devised to check automatically which gain settings satisfy the constraints. The second one is based on an optimisation procedure involving guardian maps. Starting with the open loop system, the iterative process proposed ends up with a satisfactory gain setting for the closed-loop. These methods are tried and tested for the launch vehicle, with specifications from ASTRIUM-ST. Their practical application is motivated by the system complexity, the different kinds of constraints and the essential need for robustness. Many restrictions that finally bring about the interest and the efficiency of guardian maps for such a problem.

A pseudoinverse deformation vector field generator and its applications

PubMed Central

Yan, C.; Zhong, H.; Murphy, M.; Weiss, E.; Siebers, J. V.

2010-01-01

Purpose: To present, implement, and test a self-consistent pseudoinverse displacement vector field (PIDVF) generator, which preserves the location of information mapped back-and-forth between image sets. Methods: The algorithm is an iterative scheme based on nearest neighbor interpolation and a subsequent iterative search. Performance of the algorithm is benchmarked using a lung 4DCT data set with six CT images from different breathing phases and eight CT images for a single prostrate patient acquired on different days. A diffeomorphic deformable image registration is used to validate our PIDVFs. Additionally, the PIDVF is used to measure the self-consistency of two nondiffeomorphic algorithms which do not use a self-consistency constraint: The ITK Demons algorithm for the lung patient images and an in-house B-Spline algorithm for the prostate patient images. Both Demons and B-Spline have been QAed through contour comparison. Self-consistency is determined by using a DIR to generate a displacement vector field (DVF) between reference image R and study image S (DVFR–S). The same DIR is used to generate DVFS–R. Additionally, our PIDVF generator is used to create PIDVFS–R. Back-and-forth mapping of a set of points (used as surrogates of contours) using DVFR–S and DVFS–R is compared to back-and-forth mapping performed with DVFR–S and PIDVFS–R. The Euclidean distances between the original unmapped points and the mapped points are used as a self-consistency measure. Results: Test results demonstrate that the consistency error observed in back-and-forth mappings can be reduced two to nine times in point mapping and 1.5 to three times in dose mapping when the PIDVF is used in place of the B-Spline algorithm. These self-consistency improvements are not affected by the exchanging of R and S. It is also demonstrated that differences between DVFS–R and PIDVFS–R can be used as a criteria to check the quality of the DVF. Conclusions: Use of DVF and its PIDVF will improve the self-consistency of points, contour, and dose mappings in image guided adaptive therapy. PMID:20384247

Writing and compiling code into biochemistry.

PubMed

Shea, Adam; Fett, Brian; Riedel, Marc D; Parhi, Keshab

2010-01-01

This paper presents a methodology for translating iterative arithmetic computation, specified as high-level programming constructs, into biochemical reactions. From an input/output specification, we generate biochemical reactions that produce output quantities of proteins as a function of input quantities performing operations such as addition, subtraction, and scalar multiplication. Iterative constructs such as "while" loops and "for" loops are implemented by transferring quantities between protein types, based on a clocking mechanism. Synthesis first is performed at a conceptual level, in terms of abstract biochemical reactions - a task analogous to high-level program compilation. Then the results are mapped onto specific biochemical reactions selected from libraries - a task analogous to machine language compilation. We demonstrate our approach through the compilation of a variety of standard iterative functions: multiplication, exponentiation, discrete logarithms, raising to a power, and linear transforms on time series. The designs are validated through transient stochastic simulation of the chemical kinetics. We are exploring DNA-based computation via strand displacement as a possible experimental chassis.

Iterative methods for mixed finite element equations

NASA Technical Reports Server (NTRS)

Nakazawa, S.; Nagtegaal, J. C.; Zienkiewicz, O. C.

1985-01-01

Iterative strategies for the solution of indefinite system of equations arising from the mixed finite element method are investigated in this paper with application to linear and nonlinear problems in solid and structural mechanics. The augmented Hu-Washizu form is derived, which is then utilized to construct a family of iterative algorithms using the displacement method as the preconditioner. Two types of iterative algorithms are implemented. Those are: constant metric iterations which does not involve the update of preconditioner; variable metric iterations, in which the inverse of the preconditioning matrix is updated. A series of numerical experiments is conducted to evaluate the numerical performance with application to linear and nonlinear model problems.

Single-shot spiral imaging enabled by an expanded encoding model: Demonstration in diffusion MRI.

PubMed

Wilm, Bertram J; Barmet, Christoph; Gross, Simon; Kasper, Lars; Vannesjo, S Johanna; Haeberlin, Max; Dietrich, Benjamin E; Brunner, David O; Schmid, Thomas; Pruessmann, Klaas P

2017-01-01

The purpose of this work was to improve the quality of single-shot spiral MRI and demonstrate its application for diffusion-weighted imaging. Image formation is based on an expanded encoding model that accounts for dynamic magnetic fields up to third order in space, nonuniform static B 0 , and coil sensitivity encoding. The encoding model is determined by B 0 mapping, sensitivity mapping, and concurrent field monitoring. Reconstruction is performed by iterative inversion of the expanded signal equations. Diffusion-tensor imaging with single-shot spiral readouts is performed in a phantom and in vivo, using a clinical 3T instrument. Image quality is assessed in terms of artefact levels, image congruence, and the influence of the different encoding factors. Using the full encoding model, diffusion-weighted single-shot spiral imaging of high quality is accomplished both in vitro and in vivo. Accounting for actual field dynamics, including higher orders, is found to be critical to suppress blurring, aliasing, and distortion. Enhanced image congruence permitted data fusion and diffusion tensor analysis without coregistration. Use of an expanded signal model largely overcomes the traditional vulnerability of spiral imaging with long readouts. It renders single-shot spirals competitive with echo-planar readouts and thus deploys shorter echo times and superior readout efficiency for diffusion imaging and further prospective applications. Magn Reson Med 77:83-91, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Subpixel Mapping of Hyperspectral Image Based on Linear Subpixel Feature Detection and Object Optimization

NASA Astrophysics Data System (ADS)

Liu, Zhaoxin; Zhao, Liaoying; Li, Xiaorun; Chen, Shuhan

2018-04-01

Owing to the limitation of spatial resolution of the imaging sensor and the variability of ground surfaces, mixed pixels are widesperead in hyperspectral imagery. The traditional subpixel mapping algorithms treat all mixed pixels as boundary-mixed pixels while ignoring the existence of linear subpixels. To solve this question, this paper proposed a new subpixel mapping method based on linear subpixel feature detection and object optimization. Firstly, the fraction value of each class is obtained by spectral unmixing. Secondly, the linear subpixel features are pre-determined based on the hyperspectral characteristics and the linear subpixel feature; the remaining mixed pixels are detected based on maximum linearization index analysis. The classes of linear subpixels are determined by using template matching method. Finally, the whole subpixel mapping results are iteratively optimized by binary particle swarm optimization algorithm. The performance of the proposed subpixel mapping method is evaluated via experiments based on simulated and real hyperspectral data sets. The experimental results demonstrate that the proposed method can improve the accuracy of subpixel mapping.

Composition of Web Services Using Markov Decision Processes and Dynamic Programming

PubMed Central

Uc-Cetina, Víctor; Moo-Mena, Francisco; Hernandez-Ucan, Rafael

2015-01-01

We propose a Markov decision process model for solving the Web service composition (WSC) problem. Iterative policy evaluation, value iteration, and policy iteration algorithms are used to experimentally validate our approach, with artificial and real data. The experimental results show the reliability of the model and the methods employed, with policy iteration being the best one in terms of the minimum number of iterations needed to estimate an optimal policy, with the highest Quality of Service attributes. Our experimental work shows how the solution of a WSC problem involving a set of 100,000 individual Web services and where a valid composition requiring the selection of 1,000 services from the available set can be computed in the worst case in less than 200 seconds, using an Intel Core i5 computer with 6 GB RAM. Moreover, a real WSC problem involving only 7 individual Web services requires less than 0.08 seconds, using the same computational power. Finally, a comparison with two popular reinforcement learning algorithms, sarsa and Q-learning, shows that these algorithms require one or two orders of magnitude and more time than policy iteration, iterative policy evaluation, and value iteration to handle WSC problems of the same complexity. PMID:25874247

Overview of the JET results in support to ITER

DOE PAGES

Litaudon, X.; Abduallev, S.; Abhangi, M.; ...

2017-06-15

Here, the 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing themore » importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at β N ~ 1.8 and n/n GW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed.« less

Overview of the JET results in support to ITER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Litaudon, X.; Abduallev, S.; Abhangi, M.

Here, the 2014–2016 JET results are reviewed in the light of their significance for optimising the ITER research plan for the active and non-active operation. More than 60 h of plasma operation with ITER first wall materials successfully took place since its installation in 2011. New multi-machine scaling of the type I-ELM divertor energy flux density to ITER is supported by first principle modelling. ITER relevant disruption experiments and first principle modelling are reported with a set of three disruption mitigation valves mimicking the ITER setup. Insights of the L–H power threshold in Deuterium and Hydrogen are given, stressing themore » importance of the magnetic configurations and the recent measurements of fine-scale structures in the edge radial electric. Dimensionless scans of the core and pedestal confinement provide new information to elucidate the importance of the first wall material on the fusion performance. H-mode plasmas at ITER triangularity (H = 1 at β N ~ 1.8 and n/n GW ~ 0.6) have been sustained at 2 MA during 5 s. The ITER neutronics codes have been validated on high performance experiments. Prospects for the coming D–T campaign and 14 MeV neutron calibration strategy are reviewed.« less

Accelerated iterative beam angle selection in IMRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bangert, Mark, E-mail: m.bangert@dkfz.de; Unkelbach, Jan

2016-03-15

Purpose: Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n − 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based onmore » surrogates for the FMO objective function value. Methods: We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Results: Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. Conclusions: We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.« less

Accelerated iterative beam angle selection in IMRT.

PubMed

Bangert, Mark; Unkelbach, Jan

2016-03-01

Iterative methods for beam angle selection (BAS) for intensity-modulated radiation therapy (IMRT) planning sequentially construct a beneficial ensemble of beam directions. In a naïve implementation, the nth beam is selected by adding beam orientations one-by-one from a discrete set of candidates to an existing ensemble of (n - 1) beams. The best beam orientation is identified in a time consuming process by solving the fluence map optimization (FMO) problem for every candidate beam and selecting the beam that yields the largest improvement to the objective function value. This paper evaluates two alternative methods to accelerate iterative BAS based on surrogates for the FMO objective function value. We suggest to select candidate beams not based on the FMO objective function value after convergence but (1) based on the objective function value after five FMO iterations of a gradient based algorithm and (2) based on a projected gradient of the FMO problem in the first iteration. The performance of the objective function surrogates is evaluated based on the resulting objective function values and dose statistics in a treatment planning study comprising three intracranial, three pancreas, and three prostate cases. Furthermore, iterative BAS is evaluated for an application in which a small number of noncoplanar beams complement a set of coplanar beam orientations. This scenario is of practical interest as noncoplanar setups may require additional attention of the treatment personnel for every couch rotation. Iterative BAS relying on objective function surrogates yields similar results compared to naïve BAS with regard to the objective function values and dose statistics. At the same time, early stopping of the FMO and using the projected gradient during the first iteration enable reductions in computation time by approximately one to two orders of magnitude. With regard to the clinical delivery of noncoplanar IMRT treatments, we could show that optimized beam ensembles using only a few noncoplanar beam orientations often approach the plan quality of fully noncoplanar ensembles. We conclude that iterative BAS in combination with objective function surrogates can be a viable option to implement automated BAS at clinically acceptable computation times.

Integrated Collaborative Model in Research and Education with Emphasis on Small Satellite Technology

DTIC Science & Technology

1996-01-01

feedback; the number of iterations in a complete iteration is referred to as loop depth or iteration depth, g (i). A data packet or packet is data...loop depth, g (i)) is either a finite (constant or variable) or an infinite value. 1) Finite loop depth, variable number of iterations Some problems...design time. The time needed for the first packet to leave and a new initial data to be introduced to the iteration is min(R * ( g (k) * (N+I) + k-1

Separation of Undersampled Composite Signals Using the Dantzig Selector with Overcomplete Dictionaries

DTIC Science & Technology

2014-06-02

2011). [22] Li, Q., Micchelli, C., Shen, L., and Xu, Y. A proximity algorithm acelerated by Gauss - Seidel iterations for L1/TV denoising models. Inverse...system of equations and their relationship to the solution of Model (2) and present an algorithm with an iterative approach for finding these solutions...Using the fixed-point characterization above, the (k + 1)th iteration of the prox- imity operator algorithm to find the solution of the Dantzig

A Novel Real-Time Reference Key Frame Scan Matching Method

PubMed Central

Mohamed, Haytham; Moussa, Adel; Elhabiby, Mohamed; El-Sheimy, Naser; Sesay, Abu

2017-01-01

Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF). RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems. PMID:28481285

Ice Shape Characterization Using Self-Organizing Maps

NASA Technical Reports Server (NTRS)

McClain, Stephen T.; Tino, Peter; Kreeger, Richard E.

2011-01-01

A method for characterizing ice shapes using a self-organizing map (SOM) technique is presented. Self-organizing maps are neural-network techniques for representing noisy, multi-dimensional data aligned along a lower-dimensional and possibly nonlinear manifold. For a large set of noisy data, each element of a finite set of codebook vectors is iteratively moved in the direction of the data closest to the winner codebook vector. Through successive iterations, the codebook vectors begin to align with the trends of the higher-dimensional data. In information processing, the intent of SOM methods is to transmit the codebook vectors, which contains far fewer elements and requires much less memory or bandwidth, than the original noisy data set. When applied to airfoil ice accretion shapes, the properties of the codebook vectors and the statistical nature of the SOM methods allows for a quantitative comparison of experimentally measured mean or average ice shapes to ice shapes predicted using computer codes such as LEWICE. The nature of the codebook vectors also enables grid generation and surface roughness descriptions for use with the discrete-element roughness approach. In the present study, SOM characterizations are applied to a rime ice shape, a glaze ice shape at an angle of attack, a bi-modal glaze ice shape, and a multi-horn glaze ice shape. Improvements and future explorations will be discussed.

Low dose dynamic CT myocardial perfusion imaging using a statistical iterative reconstruction method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tao, Yinghua; Chen, Guang-Hong; Hacker, Timothy A.

Purpose: Dynamic CT myocardial perfusion imaging has the potential to provide both functional and anatomical information regarding coronary artery stenosis. However, radiation dose can be potentially high due to repeated scanning of the same region. The purpose of this study is to investigate the use of statistical iterative reconstruction to improve parametric maps of myocardial perfusion derived from a low tube current dynamic CT acquisition. Methods: Four pigs underwent high (500 mA) and low (25 mA) dose dynamic CT myocardial perfusion scans with and without coronary occlusion. To delineate the affected myocardial territory, an N-13 ammonia PET perfusion scan wasmore » performed for each animal in each occlusion state. Filtered backprojection (FBP) reconstruction was first applied to all CT data sets. Then, a statistical iterative reconstruction (SIR) method was applied to data sets acquired at low dose. Image voxel noise was matched between the low dose SIR and high dose FBP reconstructions. CT perfusion maps were compared among the low dose FBP, low dose SIR and high dose FBP reconstructions. Numerical simulations of a dynamic CT scan at high and low dose (20:1 ratio) were performed to quantitatively evaluate SIR and FBP performance in terms of flow map accuracy, precision, dose efficiency, and spatial resolution. Results: Forin vivo studies, the 500 mA FBP maps gave −88.4%, −96.0%, −76.7%, and −65.8% flow change in the occluded anterior region compared to the open-coronary scans (four animals). The percent changes in the 25 mA SIR maps were in good agreement, measuring −94.7%, −81.6%, −84.0%, and −72.2%. The 25 mA FBP maps gave unreliable flow measurements due to streaks caused by photon starvation (percent changes of +137.4%, +71.0%, −11.8%, and −3.5%). Agreement between 25 mA SIR and 500 mA FBP global flow was −9.7%, 8.8%, −3.1%, and 26.4%. The average variability of flow measurements in a nonoccluded region was 16.3%, 24.1%, and 937.9% for the 500 mA FBP, 25 mA SIR, and 25 mA FBP, respectively. In numerical simulations, SIR mitigated streak artifacts in the low dose data and yielded flow maps with mean error <7% and standard deviation <9% of mean, for 30×30 pixel ROIs (12.9 × 12.9 mm{sup 2}). In comparison, low dose FBP flow errors were −38% to +258%, and standard deviation was 6%–93%. Additionally, low dose SIR achieved 4.6 times improvement in flow map CNR{sup 2} per unit input dose compared to low dose FBP. Conclusions: SIR reconstruction can reduce image noise and mitigate streaking artifacts caused by photon starvation in dynamic CT myocardial perfusion data sets acquired at low dose (low tube current), and improve perfusion map quality in comparison to FBP reconstruction at the same dose.« less

Model-based estimation and control for off-axis parabolic mirror alignment

NASA Astrophysics Data System (ADS)

Fang, Joyce; Savransky, Dmitry

2018-02-01

This paper propose an model-based estimation and control method for an off-axis parabolic mirror (OAP) alignment. Current studies in automated optical alignment systems typically require additional wavefront sensors. We propose a self-aligning method using only focal plane images captured by the existing camera. Image processing methods and Karhunen-Loève (K-L) decomposition are used to extract measurements for the observer in closed-loop control system. Our system has linear dynamic in state transition, and a nonlinear mapping from the state to the measurement. An iterative extended Kalman filter (IEKF) is shown to accurately predict the unknown states, and nonlinear observability is discussed. Linear-quadratic regulator (LQR) is applied to correct the misalignments. The method is validated experimentally on the optical bench with a commercial OAP. We conduct 100 tests in the experiment to demonstrate the consistency in between runs.

Dual regression physiological modeling of resting-state EPI power spectra: Effects of healthy aging.

PubMed

Viessmann, Olivia; Möller, Harald E; Jezzard, Peter

2018-02-02

Aging and disease-related changes in the arteriovasculature have been linked to elevated levels of cardiac cycle-induced pulsatility in the cerebral microcirculation. Functional magnetic resonance imaging (fMRI), acquired fast enough to unalias the cardiac frequency contributions, can be used to study these physiological signals in the brain. Here, we propose an iterative dual regression analysis in the frequency domain to model single voxel power spectra of echo planar imaging (EPI) data using external recordings of the cardiac and respiratory cycles as input. We further show that a data-driven variant, without external physiological traces, produces comparable results. We use this framework to map and quantify cardiac and respiratory contributions in healthy aging. We found a significant increase in the spatial extent of cardiac modulated white matter voxels with age, whereas the overall strength of cardiac-related EPI power did not show an age effect. Copyright © 2018. Published by Elsevier Inc.

Animating streamlines with repeated asymmetric patterns for steady flow visualization

NASA Astrophysics Data System (ADS)

Yeh, Chih-Kuo; Liu, Zhanping; Lee, Tong-Yee

2012-01-01

Animation provides intuitive cueing for revealing essential spatial-temporal features of data in scientific visualization. This paper explores the design of Repeated Asymmetric Patterns (RAPs) in animating evenly-spaced color-mapped streamlines for dense accurate visualization of complex steady flows. We present a smooth cyclic variable-speed RAP animation model that performs velocity (magnitude) integral luminance transition on streamlines. This model is extended with inter-streamline synchronization in luminance varying along the tangential direction to emulate orthogonal advancing waves from a geometry-based flow representation, and then with evenly-spaced hue differing in the orthogonal direction to construct tangential flow streaks. To weave these two mutually dual sets of patterns, we propose an energy-decreasing strategy that adopts an iterative yet efficient procedure for determining the luminance phase and hue of each streamline in HSL color space. We also employ adaptive luminance interleaving in the direction perpendicular to the flow to increase the contrast between streamlines.

The Chlamydomonas genome project: a decade on.

PubMed

Blaby, Ian K; Blaby-Haas, Crysten E; Tourasse, Nicolas; Hom, Erik F Y; Lopez, David; Aksoy, Munevver; Grossman, Arthur; Umen, James; Dutcher, Susan; Porter, Mary; King, Stephen; Witman, George B; Stanke, Mario; Harris, Elizabeth H; Goodstein, David; Grimwood, Jane; Schmutz, Jeremy; Vallon, Olivier; Merchant, Sabeeha S; Prochnik, Simon

2014-10-01

The green alga Chlamydomonas reinhardtii is a popular unicellular organism for studying photosynthesis, cilia biogenesis, and micronutrient homeostasis. Ten years since its genome project was initiated an iterative process of improvements to the genome and gene predictions has propelled this organism to the forefront of the omics era. Housed at Phytozome, the plant genomics portal of the Joint Genome Institute (JGI), the most up-to-date genomic data include a genome arranged on chromosomes and high-quality gene models with alternative splice forms supported by an abundance of whole transcriptome sequencing (RNA-Seq) data. We present here the past, present, and future of Chlamydomonas genomics. Specifically, we detail progress on genome assembly and gene model refinement, discuss resources for gene annotations, functional predictions, and locus ID mapping between versions and, importantly, outline a standardized framework for naming genes. Copyright © 2014 Elsevier Ltd. All rights reserved.

SOM-based nonlinear least squares twin SVM via active contours for noisy image segmentation

NASA Astrophysics Data System (ADS)

Xie, Xiaomin; Wang, Tingting

2017-02-01

In this paper, a nonlinear least square twin support vector machine (NLSTSVM) with the integration of active contour model (ACM) is proposed for noisy image segmentation. Efforts have been made to seek the kernel-generated surfaces instead of hyper-planes for the pixels belonging to the foreground and background, respectively, using the kernel trick to enhance the performance. The concurrent self organizing maps (SOMs) are applied to approximate the intensity distributions in a supervised way, so as to establish the original training sets for the NLSTSVM. Further, the two sets are updated by adding the global region average intensities at each iteration. Moreover, a local variable regional term rather than edge stop function is adopted in the energy function to ameliorate the noise robustness. Experiment results demonstrate that our model holds the higher segmentation accuracy and more noise robustness.

Elastic and inelastic collisions of swarms

NASA Astrophysics Data System (ADS)

Armbruster, Dieter; Martin, Stephan; Thatcher, Andrea

2017-04-01

Scattering interactions of swarms in potentials that are generated by an attraction-repulsion model are studied. In free space, swarms in this model form a well-defined steady state describing the translation of a stable formation of the particles whose shape depends on the interaction potential. Thus, the collision between a swarm and a boundary or between two swarms can be treated as (quasi)-particle scattering. Such scattering experiments result in internal excitations of the swarm or in bound states, respectively. In addition, varying a parameter linked to the relative importance of damping and potential forces drives transitions between elastic and inelastic scattering of the particles. By tracking the swarm's center of mass, a refraction rule is derived via simulations relating the incoming and outgoing directions of a swarm hitting the wall. Iterating the map derived from the refraction law allows us to predict and understand the dynamics and bifurcations of swarms in square boxes and in channels.

Crustal thickness of Antarctica estimated using data from gravimetric satellites

NASA Astrophysics Data System (ADS)

Llubes, Muriel; Seoane, Lucia; Bruinsma, Sean; Rémy, Frédérique

2018-04-01

Computing a better crustal thickness model is still a necessary improvement in Antarctica. In this remote continent where almost all the bedrock is covered by the ice sheet, seismic investigations do not reach a sufficient spatial resolution for geological and geophysical purposes. Here, we present a global map of Antarctic crustal thickness computed from space gravity observations. The DIR5 gravity field model, built from GOCE and GRACE gravimetric data, is inverted with the Parker-Oldenburg iterative algorithm. The BEDMAP products are used to estimate the gravity effect of the ice and the rocky surface. Our result is compared to crustal thickness calculated from seismological studies and the CRUST1.0 and AN1 models. Although the CRUST1.0 model shows a very good agreement with ours, its spatial resolution is larger than the one we obtain with gravimetric data. Finally, we compute a model in which the crust-mantle density contrast is adjusted to fit the Moho depth from the CRUST1.0 model. In East Antarctica, the resulting density contrast clearly shows higher values than in West Antarctica.

Modifications to risk-targeted seismic design maps for subduction and near-fault hazards

USGS Publications Warehouse

Liel, Abbie B.; Luco, Nicolas; Raghunandan, Meera; Champion, C.; Haukaas, Terje

2015-01-01

ASCE 7-10 introduced new seismic design maps that define risk-targeted ground motions such that buildings designed according to these maps will have 1% chance of collapse in 50 years. These maps were developed by iterative risk calculation, wherein a generic building collapse fragility curve is convolved with the U.S. Geological Survey hazard curve until target risk criteria are met. Recent research shows that this current approach may be unconservative at locations where the tectonic environment is much different than that used to develop the generic fragility curve. This study illustrates how risk-targeted ground motions at selected sites would change if generic building fragility curve and hazard assessment were modified to account for seismic risk from subduction earthquakes and near-fault pulses. The paper also explores the difficulties in implementing these changes.

Quasiperiodicity and Frequency Locking in Electronic Conduction in Germanium.

NASA Astrophysics Data System (ADS)

Gwinn, Elisabeth Gray

1987-09-01

This thesis presents an experimental study of a driven spatio-temporal instability in high-field transport in cooled, p-type Ge. The instability is produced at liquid He temperatures by d.c. voltage bias above the threshold for breakdown by impurity impact ionization, and is associated experimentally with voltage-controlled negative differential conductivity. The instability is coupled to an external oscillator by applying a sinusoidal voltage bias across the Ge sample. The driven instability exhibits frequency locking, quasiperiodicity, and chaos as the frequency and amplitude of the sinusoidal bias are varied. An iterative map of the circle provides a simple model for such a coupled, dissipative nonlinear oscillator system. The transition from quasiperiodicity to chaos in this model system occurs in a universal way; for example, the circle map has a universal, self-similar power spectrum at the onset of chaos with the golden mean winding number. When normalized appropriately, the power spectrum at the onset of chaos in the driven instability in Ge displays the same structure, with good agreement between the amplitudes of the experimental and theoretical spectral peaks. The relevance of universal theory to experiment can also be tested with a spectrum of scaling indices f( alpha), which is used to compare the probability distribution for the circle map at the onset of chaos with the golden mean winding number to the distribution of probability on a Poincare section of the experimental attractor. The procedure used to find f(alpha ) for the driven transport instability overcomes the sensitivity of f(alpha) to noise and to deviation from the critical amplitude. The f( alpha) curve for the driven instability in Ge is found to be in good agreement with the universal circle map result.

Control of particle and power exhaust in pellet fuelled ITER DT scenarios employing integrated models

NASA Astrophysics Data System (ADS)

Wiesen, S.; Köchl, F.; Belo, P.; Kotov, V.; Loarte, A.; Parail, V.; Corrigan, G.; Garzotti, L.; Harting, D.

2017-07-01

The integrated model JINTRAC is employed to assess the dynamic density evolution of the ITER baseline scenario when fuelled by discrete pellets. The consequences on the core confinement properties, α-particle heating due to fusion and the effect on the ITER divertor operation, taking into account the material limitations on the target heat loads, are discussed within the integrated model. Using the model one can observe that stable but cyclical operational regimes can be achieved for a pellet-fuelled ITER ELMy H-mode scenario with Q  =  10 maintaining partially detached conditions in the divertor. It is shown that the level of divertor detachment is inversely correlated with the core plasma density due to α-particle heating, and thus depends on the density evolution cycle imposed by pellet ablations. The power crossing the separatrix to be dissipated depends on the enhancement of the transport in the pedestal region being linked with the pressure gradient evolution after pellet injection. The fuelling efficacy of the deposited pellet material is strongly dependent on the E  ×  B plasmoid drift. It is concluded that integrated models like JINTRAC, if validated and supported by realistic physics constraints, may help to establish suitable control schemes of particle and power exhaust in burning ITER DT-plasma scenarios.

Generation of real-time mode high-resolution water vapor fields from GPS observations

NASA Astrophysics Data System (ADS)

Yu, Chen; Penna, Nigel T.; Li, Zhenhong

2017-02-01

Pointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high-resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real-time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real-time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high-resolution tropospheric delay maps compared with previous tropospheric turbulence- and elevation-dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near-IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.

Project APhiD: A Lorenz-gauged A-Φ decomposition for parallelized computation of ultra-broadband electromagnetic induction in a fully heterogeneous Earth

NASA Astrophysics Data System (ADS)

Weiss, Chester J.

2013-08-01

An essential element for computational hypothesis testing, data inversion and experiment design for electromagnetic geophysics is a robust forward solver, capable of easily and quickly evaluating the electromagnetic response of arbitrary geologic structure. The usefulness of such a solver hinges on the balance among competing desires like ease of use, speed of forward calculation, scalability to large problems or compute clusters, parsimonious use of memory access, accuracy and by necessity, the ability to faithfully accommodate a broad range of geologic scenarios over extremes in length scale and frequency content. This is indeed a tall order. The present study addresses recent progress toward the development of a forward solver with these properties. Based on the Lorenz-gauged Helmholtz decomposition, a new finite volume solution over Cartesian model domains endowed with complex-valued electrical properties is shown to be stable over the frequency range 10-2-1010 Hz and range 10-3-105 m in length scale. Benchmark examples are drawn from magnetotellurics, exploration geophysics, geotechnical mapping and laboratory-scale analysis, showing excellent agreement with reference analytic solutions. Computational efficiency is achieved through use of a matrix-free implementation of the quasi-minimum-residual (QMR) iterative solver, which eliminates explicit storage of finite volume matrix elements in favor of "on the fly" computation as needed by the iterative Krylov sequence. Further efficiency is achieved through sparse coupling matrices between the vector and scalar potentials whose non-zero elements arise only in those parts of the model domain where the conductivity gradient is non-zero. Multi-thread parallelization in the QMR solver through OpenMP pragmas is used to reduce the computational cost of its most expensive step: the single matrix-vector product at each iteration. High-level MPI communicators farm independent processes to available compute nodes for simultaneous computation of multi-frequency or multi-transmitter responses.

Influence of Primary Gage Sensitivities on the Convergence of Balance Load Iterations

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2012-01-01

The connection between the convergence of wind tunnel balance load iterations and the existence of the primary gage sensitivities of a balance is discussed. First, basic elements of two load iteration equations that the iterative method uses in combination with results of a calibration data analysis for the prediction of balance loads are reviewed. Then, the connection between the primary gage sensitivities, the load format, the gage output format, and the convergence characteristics of the load iteration equation choices is investigated. A new criterion is also introduced that may be used to objectively determine if the primary gage sensitivity of a balance gage exists. Then, it is shown that both load iteration equations will converge as long as a suitable regression model is used for the analysis of the balance calibration data, the combined influence of non linear terms of the regression model is very small, and the primary gage sensitivities of all balance gages exist. The last requirement is fulfilled, e.g., if force balance calibration data is analyzed in force balance format. Finally, it is demonstrated that only one of the two load iteration equation choices, i.e., the iteration equation used by the primary load iteration method, converges if one or more primary gage sensitivities are missing. This situation may occur, e.g., if force balance calibration data is analyzed in direct read format using the original gage outputs. Data from the calibration of a six component force balance is used to illustrate the connection between the convergence of the load iteration equation choices and the existence of the primary gage sensitivities.

3D single point imaging with compressed sensing provides high temporal resolution R 2* mapping for in vivo preclinical applications.

PubMed

Rioux, James A; Beyea, Steven D; Bowen, Chris V

2017-02-01

Purely phase-encoded techniques such as single point imaging (SPI) are generally unsuitable for in vivo imaging due to lengthy acquisition times. Reconstruction of highly undersampled data using compressed sensing allows SPI data to be quickly obtained from animal models, enabling applications in preclinical cellular and molecular imaging. TurboSPI is a multi-echo single point technique that acquires hundreds of images with microsecond spacing, enabling high temporal resolution relaxometry of large-R 2 * systems such as iron-loaded cells. TurboSPI acquisitions can be pseudo-randomly undersampled in all three dimensions to increase artifact incoherence, and can provide prior information to improve reconstruction. We evaluated the performance of CS-TurboSPI in phantoms, a rat ex vivo, and a mouse in vivo. An algorithm for iterative reconstruction of TurboSPI relaxometry time courses does not affect image quality or R 2 * mapping in vitro at acceleration factors up to 10. Imaging ex vivo is possible at similar acceleration factors, and in vivo imaging is demonstrated at an acceleration factor of 8, such that acquisition time is under 1 h. Accelerated TurboSPI enables preclinical R 2 * mapping without loss of data quality, and may show increased specificity to iron oxide compared to other sequences.

The Battlefield Environment Division Modeling Framework (BMF). Part 1: Optimizing the Atmospheric Boundary Layer Environment Model for Cluster Computing

DTIC Science & Technology

2014-02-01

idle waiting for the wavefront to reach it. To overcome this, Reeve et al. (2001) 3 developed a scheme in analogy to the red-black Gauss - Seidel iterative ...understandable procedure calls. Parallelization of the SIMPLE iterative scheme with SIP used a red-black scheme similar to the red-black Gauss - Seidel ...scheme, the SIMPLE method, for pressure-velocity coupling. The result is a slowing convergence of the outer iterations . The red-black scheme excites a 2

Generation of High Resolution Water Vapour Fields from GPS Observations and Integration With ECMWF and MODIS

NASA Astrophysics Data System (ADS)

Yu, C.; Li, Z.; Penna, N. T.

2016-12-01

Precipitable water vapour (PWV) can be routinely retrieved from ground-based GPS arrays in all-weather conditions and also in real-time. But to provide dense spatial coverage maps, for example for calibrating SAR images, for correcting atmospheric effects in Network RTK GPS positioning and which may be used for numerical weather prediction, the pointwise GPS PWV measurements must be interpolated. Several previous interpolation studies have addressed the importance of the elevation dependency of water vapour, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. We present a tropospheric turbulence iterative decomposition model that decouples the total PWV into (i) a stratified component highly correlated with topography which therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. We will demonstrate that the iterative decoupled interpolation model generates improved dense tropospheric water vapour fields compared with elevation dependent models, with similar accuracies obtained over both flat and mountainous terrain, as well as for both inland and coastal areas. We will also show that our GPS-based model may be enhanced with ECMWF zenith tropospheric delay and MODIS PWV, producing multi-data sources high temporal-spatial resolution PWV fields. These fields were applied to Sentinel-1 SAR interferograms over the Los Angeles region, for which a maximum noise reduction due to atmosphere artifacts reached 85%. The results reveal that the turbulent troposphere noise, especially those in a SAR image, often occupy more than 50% of the total zenith tropospheric delay and exert systematic, rather than random patterns.

Active machine learning for rapid landslide inventory mapping with VHR satellite images (Invited)

NASA Astrophysics Data System (ADS)

Stumpf, A.; Lachiche, N.; Malet, J.; Kerle, N.; Puissant, A.

2013-12-01

VHR satellite images have become a primary source for landslide inventory mapping after major triggering events such as earthquakes and heavy rainfalls. Visual image interpretation is still the prevailing standard method for operational purposes but is time-consuming and not well suited to fully exploit the increasingly better supply of remote sensing data. Recent studies have addressed the development of more automated image analysis workflows for landslide inventory mapping. In particular object-oriented approaches that account for spatial and textural image information have been demonstrated to be more adequate than pixel-based classification but manually elaborated rule-based classifiers are difficult to adapt under changing scene characteristics. Machine learning algorithm allow learning classification rules for complex image patterns from labelled examples and can be adapted straightforwardly with available training data. In order to reduce the amount of costly training data active learning (AL) has evolved as a key concept to guide the sampling for many applications. The underlying idea of AL is to initialize a machine learning model with a small training set, and to subsequently exploit the model state and data structure to iteratively select the most valuable samples that should be labelled by the user. With relatively few queries and labelled samples, an AL strategy yields higher accuracies than an equivalent classifier trained with many randomly selected samples. This study addressed the development of an AL method for landslide mapping from VHR remote sensing images with special consideration of the spatial distribution of the samples. Our approach [1] is based on the Random Forest algorithm and considers the classifier uncertainty as well as the variance of potential sampling regions to guide the user towards the most valuable sampling areas. The algorithm explicitly searches for compact regions and thereby avoids a spatially disperse sampling pattern inherent to most other AL methods. The accuracy, the sampling time and the computational runtime of the algorithm were evaluated on multiple satellite images capturing recent large scale landslide events. Sampling between 1-4% of the study areas the accuracies between 74% and 80% were achieved, whereas standard sampling schemes yielded only accuracies between 28% and 50% with equal sampling costs. Compared to commonly used point-wise AL algorithm the proposed approach significantly reduces the number of iterations and hence the computational runtime. Since the user can focus on relatively few compact areas (rather than on hundreds of distributed points) the overall labeling time is reduced by more than 50% compared to point-wise queries. An experimental evaluation of multiple expert mappings demonstrated strong relationships between the uncertainties of the experts and the machine learning model. It revealed that the achieved accuracies are within the range of the inter-expert disagreement and that it will be indispensable to consider ground truth uncertainties to truly achieve further enhancements in the future. The proposed method is generally applicable to a wide range of optical satellite images and landslide types. [1] A. Stumpf, N. Lachiche, J.-P. Malet, N. Kerle, and A. Puissant, Active learning in the spatial domain for remote sensing image classification, IEEE Transactions on Geosciece and Remote Sensing. 2013, DOI 10.1109/TGRS.2013.2262052.

Super-resolution Time-Lapse Seismic Waveform Inversion

NASA Astrophysics Data System (ADS)

Ovcharenko, O.; Kazei, V.; Peter, D. B.; Alkhalifah, T.

2017-12-01

Time-lapse seismic waveform inversion is a technique, which allows tracking changes in the reservoirs over time. Such monitoring is relatively computationally extensive and therefore it is barely feasible to perform it on-the-fly. Most of the expenses are related to numerous FWI iterations at high temporal frequencies, which is inevitable since the low-frequency components can not resolve fine scale features of a velocity model. Inverted velocity changes are also blurred when there is noise in the data, so the problem of low-resolution images is widely known. One of the problems intensively tackled by computer vision research community is the recovering of high-resolution images having their low-resolution versions. Usage of artificial neural networks to reach super-resolution from a single downsampled image is one of the leading solutions for this problem. Each pixel of the upscaled image is affected by all the pixels of its low-resolution version, which enables the workflow to recover features that are likely to occur in the corresponding environment. In the present work, we adopt machine learning image enhancement technique to improve the resolution of time-lapse full-waveform inversion. We first invert the baseline model with conventional FWI. Then we run a few iterations of FWI on a set of the monitoring data to find desired model changes. These changes are blurred and we enhance their resolution by using a deep neural network. The network is trained to map low-resolution model updates predicted by FWI into the real perturbations of the baseline model. For supervised training of the network we generate a set of random perturbations in the baseline model and perform FWI on the noisy data from the perturbed models. We test the approach on a realistic perturbation of Marmousi II model and demonstrate that it outperforms conventional convolution-based deblurring techniques.

Digital computer program for generating dynamic turbofan engine models (DIGTEM)

NASA Technical Reports Server (NTRS)

Daniele, C. J.; Krosel, S. M.; Szuch, J. R.; Westerkamp, E. J.

1983-01-01

This report describes DIGTEM, a digital computer program that simulates two spool, two-stream turbofan engines. The turbofan engine model in DIGTEM contains steady-state performance maps for all of the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. Altogether there are 16 state variables and state equations. DIGTEM features a backward-differnce integration scheme for integrating stiff systems. It trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off-design points and iterates to a balanced engine condition. Transients can also be run. They are generated by defining controls as a function of time (open-loop control) in a user-written subroutine (TMRSP). DIGTEM has run on the IBM 370/3033 computer using implicit integration with time steps ranging from 1.0 msec to 1.0 sec. DIGTEM is generalized in the aerothermodynamic treatment of components.

Temperature-Dependent Implicit-Solvent Model of Polyethylene Glycol in Aqueous Solution.

PubMed

Chudoba, Richard; Heyda, Jan; Dzubiella, Joachim

2017-12-12

A temperature (T)-dependent coarse-grained (CG) Hamiltonian of polyethylene glycol/oxide (PEG/PEO) in aqueous solution is reported to be used in implicit-solvent material models in a wide temperature (i.e., solvent quality) range. The T-dependent nonbonded CG interactions are derived from a combined "bottom-up" and "top-down" approach. The pair potentials calculated from atomistic replica-exchange molecular dynamics simulations in combination with the iterative Boltzmann inversion are postrefined by benchmarking to experimental data of the radius of gyration. For better handling and a fully continuous transferability in T-space, the pair potentials are conveniently truncated and mapped to an analytic formula with three structural parameters expressed as explicit continuous functions of T. It is then demonstrated that this model without further adjustments successfully reproduces other experimentally known key thermodynamic properties of semidilute PEG solutions such as the full equation of state (i.e., T-dependent osmotic pressure) for various chain lengths as well as their cloud point (or collapse) temperature.

GoFFish: A Sub-Graph Centric Framework for Large-Scale Graph Analytics1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simmhan, Yogesh; Kumbhare, Alok; Wickramaarachchi, Charith

2014-08-25

Large scale graph processing is a major research area for Big Data exploration. Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally. However, there are limitations to this approach which cause vertex centric algorithms to under-perform due to poor compute to communication overhead ratio and slow convergence of iterative superstep. In this paper we introduce GoFFish a scalable sub-graph centric framework co-designed with a distributed persistent graph storage for large scale graph analytics on commodity clusters. We introduce a sub-graph centric programming abstraction that combines themore » scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation. We map Connected Components, SSSP and PageRank algorithms to this model to illustrate its flexibility. Further, we empirically analyze GoFFish using several real world graphs and demonstrate its significant performance improvement, orders of magnitude in some cases, compared to Apache Giraph, the leading open source vertex centric implementation.« less

A novel algorithm for fast and efficient multifocus wavefront shaping

NASA Astrophysics Data System (ADS)

Fayyaz, Zahra; Nasiriavanaki, Mohammadreza

2018-02-01

Wavefront shaping using spatial light modulator (SLM) is a popular method for focusing light through a turbid media, such as biological tissues. Usually, in iterative optimization methods, due to the very large number of pixels in SLM, larger pixels are formed, bins, and the phase value of the bins are changed to obtain an optimum phase map, hence a focus. In this study an efficient optimization algorithm is proposed to obtain an arbitrary map of focus utilizing all the SLM pixels or small bin sizes. The application of such methodology in dermatology, hair removal in particular, is explored and discussed

Split-step eigenvector-following technique for exploring enthalpy landscapes at absolute zero.

PubMed

Mauro, John C; Loucks, Roger J; Balakrishnan, Jitendra

2006-03-16

The mapping of enthalpy landscapes is complicated by the coupling of particle position and volume coordinates. To address this issue, we have developed a new split-step eigenvector-following technique for locating minima and transition points in an enthalpy landscape at absolute zero. Each iteration is split into two steps in order to independently vary system volume and relative atomic coordinates. A separate Lagrange multiplier is used for each eigendirection in order to provide maximum flexibility in determining step sizes. This technique will be useful for mapping the enthalpy landscapes of bulk systems such as supercooled liquids and glasses.

Thermal modeling of W rod armor.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nygren, Richard Einar

2004-09-01

Sandia has developed and tested mockups armored with W rods over the last decade and pioneered the initial development of W rod armor for International Thermonuclear Experimental Reactor (ITER) in the 1990's. We have also developed 2D and 3D thermal and stress models of W rod-armored plasma facing components (PFCs) and test mockups and are applying the models to both short pulses, i.e. edge localized modes (ELMs), and thermal performance in steady state for applications in C-MOD, DiMES testing and ITER. This paper briefly describes the 2D and 3D models and their applications with emphasis on modeling for an ongoingmore » test program that simulates repeated heat loads from ITER ELMs.« less

Feature Based Retention Time Alignment for Improved HDX MS Analysis

NASA Astrophysics Data System (ADS)

Venable, John D.; Scuba, William; Brock, Ansgar

2013-04-01

An algorithm for retention time alignment of mass shifted hydrogen-deuterium exchange (HDX) data based on an iterative distance minimization procedure is described. The algorithm performs pairwise comparisons in an iterative fashion between a list of features from a reference file and a file to be time aligned to calculate a retention time mapping function. Features are characterized by their charge, retention time and mass of the monoisotopic peak. The algorithm is able to align datasets with mass shifted features, which is a prerequisite for aligning hydrogen-deuterium exchange mass spectrometry datasets. Confidence assignments from the fully automated processing of a commercial HDX software package are shown to benefit significantly from retention time alignment prior to extraction of deuterium incorporation values.

Development of a stereo analysis algorithm for generating topographic maps using interactive techniques of the MPP

NASA Technical Reports Server (NTRS)

Strong, James P.

1987-01-01

A local area matching algorithm was developed on the Massively Parallel Processor (MPP). It is an iterative technique that first matches coarse or low resolution areas and at each iteration performs matches of higher resolution. Results so far show that when good matches are possible in the two images, the MPP algorithm matches corresponding areas as well as a human observer. To aid in developing this algorithm, a control or shell program was developed for the MPP that allows interactive experimentation with various parameters and procedures to be used in the matching process. (This would not be possible without the high speed of the MPP). With the system, optimal techniques can be developed for different types of matching problems.

On the self-similar solution to the Euler equations for an incompressible fluid in three dimensions

NASA Astrophysics Data System (ADS)

Pomeau, Yves

2018-03-01

The equations for a self-similar solution to an inviscid incompressible fluid are mapped into an integral equation that hopefully can be solved by iteration. It is argued that the exponents of the similarity are ruled by Kelvin's theorem of conservation of circulation. The end result is an iteration with a nonlinear term entering a kernel given by a 3D integral for a swirling flow, likely within reach of present-day computational power. Because of the slow decay of the similarity solution at large distances, its kinetic energy diverges, and some mathematical results excluding non-trivial solutions of the Euler equations in the self-similar case do not apply. xml:lang="fr"

A Survey of the Use of Iterative Reconstruction Algorithms in Electron Microscopy

PubMed Central

Otón, J.; Vilas, J. L.; Kazemi, M.; Melero, R.; del Caño, L.; Cuenca, J.; Conesa, P.; Gómez-Blanco, J.; Marabini, R.; Carazo, J. M.

2017-01-01

One of the key steps in Electron Microscopy is the tomographic reconstruction of a three-dimensional (3D) map of the specimen being studied from a set of two-dimensional (2D) projections acquired at the microscope. This tomographic reconstruction may be performed with different reconstruction algorithms that can be grouped into several large families: direct Fourier inversion methods, back-projection methods, Radon methods, or iterative algorithms. In this review, we focus on the latter family of algorithms, explaining the mathematical rationale behind the different algorithms in this family as they have been introduced in the field of Electron Microscopy. We cover their use in Single Particle Analysis (SPA) as well as in Electron Tomography (ET). PMID:29312997

Low-rank Atlas Image Analyses in the Presence of Pathologies

PubMed Central

Liu, Xiaoxiao; Niethammer, Marc; Kwitt, Roland; Singh, Nikhil; McCormick, Matt; Aylward, Stephen

2015-01-01

We present a common framework, for registering images to an atlas and for forming an unbiased atlas, that tolerates the presence of pathologies such as tumors and traumatic brain injury lesions. This common framework is particularly useful when a sufficient number of protocol-matched scans from healthy subjects cannot be easily acquired for atlas formation and when the pathologies in a patient cause large appearance changes. Our framework combines a low-rank-plus-sparse image decomposition technique with an iterative, diffeomorphic, group-wise image registration method. At each iteration of image registration, the decomposition technique estimates a “healthy” version of each image as its low-rank component and estimates the pathologies in each image as its sparse component. The healthy version of each image is used for the next iteration of image registration. The low-rank and sparse estimates are refined as the image registrations iteratively improve. When that framework is applied to image-to-atlas registration, the low-rank image is registered to a pre-defined atlas, to establish correspondence that is independent of the pathologies in the sparse component of each image. Ultimately, image-to-atlas registrations can be used to define spatial priors for tissue segmentation and to map information across subjects. When that framework is applied to unbiased atlas formation, at each iteration, the average of the low-rank images from the patients is used as the atlas image for the next iteration, until convergence. Since each iteration’s atlas is comprised of low-rank components, it provides a population-consistent, pathology-free appearance. Evaluations of the proposed methodology are presented using synthetic data as well as simulated and clinical tumor MRI images from the brain tumor segmentation (BRATS) challenge from MICCAI 2012. PMID:26111390

3D numerical simulations of negative hydrogen ion extraction using realistic plasma parameters, geometry of the extraction aperture and full 3D magnetic field map

NASA Astrophysics Data System (ADS)

Mochalskyy, S.; Wünderlich, D.; Ruf, B.; Franzen, P.; Fantz, U.; Minea, T.

2014-02-01

Decreasing the co-extracted electron current while simultaneously keeping negative ion (NI) current sufficiently high is a crucial issue on the development plasma source system for ITER Neutral Beam Injector. To support finding the best extraction conditions the 3D Particle-in-Cell Monte Carlo Collision electrostatic code ONIX (Orsay Negative Ion eXtraction) has been developed. Close collaboration with experiments and other numerical models allows performing realistic simulations with relevant input parameters: plasma properties, geometry of the extraction aperture, full 3D magnetic field map, etc. For the first time ONIX has been benchmarked with commercial positive ions tracing code KOBRA3D. A very good agreement in terms of the meniscus position and depth has been found. Simulation of NI extraction with different e/NI ratio in bulk plasma shows high relevance of the direct negative ion extraction from the surface produced NI in order to obtain extracted NI current as in the experimental results from BATMAN testbed.

Fixing convergence of Gaussian belief propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jason K; Bickson, Danny; Dolev, Danny

Gaussian belief propagation (GaBP) is an iterative message-passing algorithm for inference in Gaussian graphical models. It is known that when GaBP converges it converges to the correct MAP estimate of the Gaussian random vector and simple sufficient conditions for its convergence have been established. In this paper we develop a double-loop algorithm for forcing convergence of GaBP. Our method computes the correct MAP estimate even in cases where standard GaBP would not have converged. We further extend this construction to compute least-squares solutions of over-constrained linear systems. We believe that our construction has numerous applications, since the GaBP algorithm ismore » linked to solution of linear systems of equations, which is a fundamental problem in computer science and engineering. As a case study, we discuss the linear detection problem. We show that using our new construction, we are able to force convergence of Montanari's linear detection algorithm, in cases where it would originally fail. As a consequence, we are able to increase significantly the number of users that can transmit concurrently.« less

Chaotic Dynamics of Linguistic-Like Processes at the Syntactical and Semantic Levels: in the Pursuit of a Multifractal Attractor

NASA Astrophysics Data System (ADS)

Nicolis, John S.; Katsikas, Anastassis A.

Collective parameters such as the Zipf's law-like statistics, the Transinformation, the Block Entropy and the Markovian character are compared for natural, genetic, musical and artificially generated long texts from generating partitions (alphabets) on homogeneous as well as on multifractal chaotic maps. It appears that minimal requirements for a language at the syntactical level such as memory, selectivity of few keywords and broken symmetry in one dimension (polarity) are more or less met by dynamically iterating simple maps or flows e.g. very simple chaotic hardware. The same selectivity is observed at the semantic level where the aim refers to partitioning a set of enviromental impinging stimuli onto coexisting attractors-categories. Under the regime of pattern recognition and classification, few key features of a pattern or few categories claim the lion's share of the information stored in this pattern and practically, only these key features are persistently scanned by the cognitive processor. A multifractal attractor model can in principle explain this high selectivity, both at the syntactical and the semantic levels.

Information theory applications for biological sequence analysis.

PubMed

Vinga, Susana

2014-05-01

Information theory (IT) addresses the analysis of communication systems and has been widely applied in molecular biology. In particular, alignment-free sequence analysis and comparison greatly benefited from concepts derived from IT, such as entropy and mutual information. This review covers several aspects of IT applications, ranging from genome global analysis and comparison, including block-entropy estimation and resolution-free metrics based on iterative maps, to local analysis, comprising the classification of motifs, prediction of transcription factor binding sites and sequence characterization based on linguistic complexity and entropic profiles. IT has also been applied to high-level correlations that combine DNA, RNA or protein features with sequence-independent properties, such as gene mapping and phenotype analysis, and has also provided models based on communication systems theory to describe information transmission channels at the cell level and also during evolutionary processes. While not exhaustive, this review attempts to categorize existing methods and to indicate their relation with broader transversal topics such as genomic signatures, data compression and complexity, time series analysis and phylogenetic classification, providing a resource for future developments in this promising area.

The use of process mapping in healthcare quality improvement projects.

PubMed

Antonacci, Grazia; Reed, Julie E; Lennox, Laura; Barlow, James

2018-05-01

Introduction Process mapping provides insight into systems and processes in which improvement interventions are introduced and is seen as useful in healthcare quality improvement projects. There is little empirical evidence on the use of process mapping in healthcare practice. This study advances understanding of the benefits and success factors of process mapping within quality improvement projects. Methods Eight quality improvement projects were purposively selected from different healthcare settings within the UK's National Health Service. Data were gathered from multiple data-sources, including interviews exploring participants' experience of using process mapping in their projects and perceptions of benefits and challenges related to its use. These were analysed using inductive analysis. Results Eight key benefits related to process mapping use were reported by participants (gathering a shared understanding of the reality; identifying improvement opportunities; engaging stakeholders in the project; defining project's objectives; monitoring project progress; learning; increased empathy; simplicity of the method) and five factors related to successful process mapping exercises (simple and appropriate visual representation, information gathered from multiple stakeholders, facilitator's experience and soft skills, basic training, iterative use of process mapping throughout the project). Conclusions Findings highlight benefits and versatility of process mapping and provide practical suggestions to improve its use in practice.

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

NASA Technical Reports Server (NTRS)

Daniele, C. J.

1984-01-01

This paper describes DIGTEM (digital turbofan engine model), a computer program that simulates two spool, two stream (turbofan) engines. DIGTEM was developed to support the development of a real time multiprocessor based engine simulator being designed at the Lewis Research Center. The turbofan engine model in DIGTEM contains steady state performance maps for all the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. DIGTEM features an implicit integration scheme for integrating stiff systems and trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off design points and iterates to a balanced engine condition. Transients are generated by defining the engine inputs as functions of time in a user written subroutine (TMRSP). Closed loop controls can also be simulated. DIGTEM is generalized in the aerothermodynamic treatment of components. This feature, along with DIGTEM's trimming at a design point, make it a very useful tool for developing a model of a specific turbofan engine.

A generalized computer code for developing dynamic gas turbine engine models (DIGTEM)

NASA Technical Reports Server (NTRS)

Daniele, C. J.

1983-01-01

This paper describes DIGTEM (digital turbofan engine model), a computer program that simulates two spool, two stream (turbofan) engines. DIGTEM was developed to support the development of a real time multiprocessor based engine simulator being designed at the Lewis Research Center. The turbofan engine model in DIGTEM contains steady state performance maps for all the components and has control volumes where continuity and energy balances are maintained. Rotor dynamics and duct momentum dynamics are also included. DIGTEM features an implicit integration scheme for integrating stiff systems and trims the model equations to match a prescribed design point by calculating correction coefficients that balance out the dynamic equations. It uses the same coefficients at off design points and iterates to a balanced engine condition. Transients are generated by defining the engine inputs as functions of time in a user written subroutine (TMRSP). Closed loop controls can also be simulated. DIGTEM is generalized in the aerothermodynamic treatment of components. This feature, along with DIGTEM's trimming at a design point, make it a very useful tool for developing a model of a specific turbofan engine.

SU-E-I-33: Initial Evaluation of Model-Based Iterative CT Reconstruction Using Standard Image Quality Phantoms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gingold, E; Dave, J

2014-06-01

Purpose: The purpose of this study was to compare a new model-based iterative reconstruction with existing reconstruction methods (filtered backprojection and basic iterative reconstruction) using quantitative analysis of standard image quality phantom images. Methods: An ACR accreditation phantom (Gammex 464) and a CATPHAN600 phantom were scanned using 3 routine clinical acquisition protocols (adult axial brain, adult abdomen, and pediatric abdomen) on a Philips iCT system. Each scan was acquired using default conditions and 75%, 50% and 25% dose levels. Images were reconstructed using standard filtered backprojection (FBP), conventional iterative reconstruction (iDose4) and a prototype model-based iterative reconstruction (IMR). Phantom measurementsmore » included CT number accuracy, contrast to noise ratio (CNR), modulation transfer function (MTF), low contrast detectability (LCD), and noise power spectrum (NPS). Results: The choice of reconstruction method had no effect on CT number accuracy, or MTF (p<0.01). The CNR of a 6 HU contrast target was improved by 1–67% with iDose4 relative to FBP, while IMR improved CNR by 145–367% across all protocols and dose levels. Within each scan protocol, the CNR improvement from IMR vs FBP showed a general trend of greater improvement at lower dose levels. NPS magnitude was greatest for FBP and lowest for IMR. The NPS of the IMR reconstruction showed a pronounced decrease with increasing spatial frequency, consistent with the unusual noise texture seen in IMR images. Conclusion: Iterative Model Reconstruction reduces noise and improves contrast-to-noise ratio without sacrificing spatial resolution in CT phantom images. This offers the possibility of radiation dose reduction and improved low contrast detectability compared with filtered backprojection or conventional iterative reconstruction.« less

Evaluation of integration methods for hybrid simulation of complex structural systems through collapse

NASA Astrophysics Data System (ADS)

Del Carpio R., Maikol; Hashemi, M. Javad; Mosqueda, Gilberto

2017-10-01

This study examines the performance of integration methods for hybrid simulation of large and complex structural systems in the context of structural collapse due to seismic excitations. The target application is not necessarily for real-time testing, but rather for models that involve large-scale physical sub-structures and highly nonlinear numerical models. Four case studies are presented and discussed. In the first case study, the accuracy of integration schemes including two widely used methods, namely, modified version of the implicit Newmark with fixed-number of iteration (iterative) and the operator-splitting (non-iterative) is examined through pure numerical simulations. The second case study presents the results of 10 hybrid simulations repeated with the two aforementioned integration methods considering various time steps and fixed-number of iterations for the iterative integration method. The physical sub-structure in these tests consists of a single-degree-of-freedom (SDOF) cantilever column with replaceable steel coupons that provides repeatable highlynonlinear behavior including fracture-type strength and stiffness degradations. In case study three, the implicit Newmark with fixed-number of iterations is applied for hybrid simulations of a 1:2 scale steel moment frame that includes a relatively complex nonlinear numerical substructure. Lastly, a more complex numerical substructure is considered by constructing a nonlinear computational model of a moment frame coupled to a hybrid model of a 1:2 scale steel gravity frame. The last two case studies are conducted on the same porotype structure and the selection of time steps and fixed number of iterations are closely examined in pre-test simulations. The generated unbalance forces is used as an index to track the equilibrium error and predict the accuracy and stability of the simulations.

Mean-variance analysis of block-iterative reconstruction algorithms modeling 3D detector response in SPECT

NASA Astrophysics Data System (ADS)

Lalush, D. S.; Tsui, B. M. W.

1998-06-01

We study the statistical convergence properties of two fast iterative reconstruction algorithms, the rescaled block-iterative (RBI) and ordered subset (OS) EM algorithms, in the context of cardiac SPECT with 3D detector response modeling. The Monte Carlo method was used to generate nearly noise-free projection data modeling the effects of attenuation, detector response, and scatter from the MCAT phantom. One thousand noise realizations were generated with an average count level approximating a typical T1-201 cardiac study. Each noise realization was reconstructed using the RBI and OS algorithms for cases with and without detector response modeling. For each iteration up to twenty, we generated mean and variance images, as well as covariance images for six specific locations. Both OS and RBI converged in the mean to results that were close to the noise-free ML-EM result using the same projection model. When detector response was not modeled in the reconstruction, RBI exhibited considerably lower noise variance than OS for the same resolution. When 3D detector response was modeled, the RBI-EM provided a small improvement in the tradeoff between noise level and resolution recovery, primarily in the axial direction, while OS required about half the number of iterations of RBI to reach the same resolution. We conclude that OS is faster than RBI, but may be sensitive to errors in the projection model. Both OS-EM and RBI-EM are effective alternatives to the EVIL-EM algorithm, but noise level and speed of convergence depend on the projection model used.

A Two-Dimensional Helmholtz Equation Solution for the Multiple Cavity Scattering Problem

DTIC Science & Technology

2013-02-01

obtained by using the block Gauss – Seidel iterative meth- od. To show the convergence of the iterative method, we define the error between two...models to the general multiple cavity setting. Numerical examples indicate that the convergence of the Gauss – Seidel iterative method depends on the...variational approach. A block Gauss – Seidel iterative method is introduced to solve the cou- pled system of the multiple cavity scattering problem, where

CORSICA modelling of ITER hybrid operation scenarios

NASA Astrophysics Data System (ADS)

Kim, S. H.; Bulmer, R. H.; Campbell, D. J.; Casper, T. A.; LoDestro, L. L.; Meyer, W. H.; Pearlstein, L. D.; Snipes, J. A.

2016-12-01

The hybrid operating mode observed in several tokamaks is characterized by further enhancement over the high plasma confinement (H-mode) associated with reduced magneto-hydro-dynamic (MHD) instabilities linked to a stationary flat safety factor (q ) profile in the core region. The proposed ITER hybrid operation is currently aiming at operating for a long burn duration (>1000 s) with a moderate fusion power multiplication factor, Q , of at least 5. This paper presents candidate ITER hybrid operation scenarios developed using a free-boundary transport modelling code, CORSICA, taking all relevant physics and engineering constraints into account. The ITER hybrid operation scenarios have been developed by tailoring the 15 MA baseline ITER inductive H-mode scenario. Accessible operation conditions for ITER hybrid operation and achievable range of plasma parameters have been investigated considering uncertainties on the plasma confinement and transport. ITER operation capability for avoiding the poloidal field coil current, field and force limits has been examined by applying different current ramp rates, flat-top plasma currents and densities, and pre-magnetization of the poloidal field coils. Various combinations of heating and current drive (H&CD) schemes have been applied to study several physics issues, such as the plasma current density profile tailoring, enhancement of the plasma energy confinement and fusion power generation. A parameterized edge pedestal model based on EPED1 added to the CORSICA code has been applied to hybrid operation scenarios. Finally, fully self-consistent free-boundary transport simulations have been performed to provide information on the poloidal field coil voltage demands and to study the controllability with the ITER controllers. Extended from Proc. 24th Int. Conf. on Fusion Energy (San Diego, 2012) IT/P1-13.

An Undergraduate Research Experience that Integrates Traditional Field Mapping, LiDAR, and 3D Numerical Modeling: Applying Lessons from a Recent Report from the National Academies of Sciences, Engineering, and Medicine in an Intermediate-Level Tectonic Landscapes Course

NASA Astrophysics Data System (ADS)

Reinen, L. A.; Brenner, K.

2017-12-01

Ongoing efforts to improve undergraduate education in science, technology, engineering, and mathematics (STEM) fields focus on increasing active student participation and decreasing traditional lecture-based teaching. Undergraduate research experiences (UREs), which engage students in the work of STEM professionals, are an example of these efforts. A recent report from the National Academies of Sciences, Engineering and Medicine (Undergraduate Research Experiences for STEM Students: Successes, Challenges, and Opportunities; 2017) provides characteristics of UREs, and indicates that participation in UREs increases student interest and persistence in STEM as well as provides opportunities to broaden student participation in these fields. UREs offer an excellent opportunity to engage students in research using the rapidly evolving technologies used by STEM professionals. In the fall of 2016, students in the Tectonic Landscapes class at Pomona College participated in a course-based URE that combined traditional field mapping methods with analysis of high-resolution topographic data (LiDAR) and 3D numerical modeling to investigate questions of active local faulting. During the first ten weeks students developed skills in: creation of fault maps from both field observations (GPS included) and high-resolution digital elevation models (DEMs), assessment of tectonic activity through analyses of DEMs of hill slope diffusion models and geomorphic indices, and evaluation of fault geometry hypotheses via 3D elastic modeling. Most of these assignments were focused on a single research site. While students primarily used Excel, ArcMap, and Poly3D, no previous knowledge of these was required or assumed. Through this iterative approach, students used increasingly more complex methods as well as gained greater ownership of the research process with time. The course culminated with a 4-week independent research project in which each student investigated a question of their own choosing using skills developed earlier in the course. We will provide details of the course, scaffolding of the technical skills, growing the independence of students in the research process, and discuss early outcomes of student confidence, engagement and retention.

ROAD MAP FOR DEVELOPMENT OF CRYSTAL-TOLERANT HIGH LEVEL WASTE GLASSES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fox, K.; Peeler, D.; Herman, C.

The U.S. Department of Energy (DOE) is building a Tank Waste Treatment and Immobilization Plant (WTP) at the Hanford Site in Washington to remediate 55 million gallons of radioactive waste that is being temporarily stored in 177 underground tanks. Efforts are being made to increase the loading of Hanford tank wastes in glass while meeting melter lifetime expectancies and process, regulatory, and product quality requirements. This road map guides the research and development for formulation and processing of crystaltolerant glasses, identifying near- and long-term activities that need to be completed over the period from 2014 to 2019. The primary objectivemore » is to maximize waste loading for Hanford waste glasses without jeopardizing melter operation by crystal accumulation in the melter or melter discharge riser. The potential applicability to the Savannah River Site (SRS) Defense Waste Processing Facility (DWPF) will also be addressed in this road map. The planned research described in this road map is motivated by the potential for substantial economic benefits (significant reductions in glass volumes) that will be realized if the current constraints (T1% for WTP and TL for DWPF) are approached in an appropriate and technically defensible manner for defense waste and current melter designs. The basis of this alternative approach is an empirical model predicting the crystal accumulation in the WTP glass discharge riser and melter bottom as a function of glass composition, time, and temperature. When coupled with an associated operating limit (e.g., the maximum tolerable thickness of an accumulated layer of crystals), this model could then be integrated into the process control algorithms to formulate crystal-tolerant high-level waste (HLW) glasses targeting high waste loadings while still meeting process related limits and melter lifetime expectancies. The modeling effort will be an iterative process, where model form and a broader range of conditions, e.g., glass composition and temperature, will evolve as additional data on crystal accumulation are gathered. Model validation steps will be included to guide the development process and ensure the value of the effort (i.e., increased waste loading and waste throughput). A summary of the stages of the road map for developing the crystal-tolerant glass approach, their estimated durations, and deliverables is provided.« less

Development of an Ultrasonic Phased Array System for Wellbore Integrity Evaluation and Near-Wellbore Fracture Network Mapping of Injection and Production Wells in Geothermal Energy Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Almansouri, Hani; Foster, Benjamin; Kisner, Roger A

2016-01-01

This paper documents our progress developing an ultrasound phased array system in combination with a model-based iterative reconstruction (MBIR) algorithm to inspect the health of and characterize the composition of the near-wellbore region for geothermal reservoirs. The main goal for this system is to provide a near-wellbore in-situ characterization capability that will significantly improve wellbore integrity evaluation and near well-bore fracture network mapping. A more detailed image of the fracture network near the wellbore in particular will enable the selection of optimal locations for stimulation along the wellbore, provide critical data that can be used to improve stimulation design, andmore » provide a means for measuring evolution of the fracture network to support long term management of reservoir operations. Development of such a measurement capability supports current hydrothermal operations as well as the successful demonstration of Engineered Geothermal Systems (EGS). The paper will include the design of the phased array system, the performance specifications, and characterization methodology. In addition, we will describe the MBIR forward model derived for the phased array system and the propagation of compressional waves through a pseudo-homogenous medium.« less

Solving coupled groundwater flow systems using a Jacobian Free Newton Krylov method

NASA Astrophysics Data System (ADS)

Mehl, S.

2012-12-01

Jacobian Free Newton Kyrlov (JFNK) methods can have several advantages for simulating coupled groundwater flow processes versus conventional methods. Conventional methods are defined here as those based on an iterative coupling (rather than a direct coupling) and/or that use Picard iteration rather than Newton iteration. In an iterative coupling, the systems are solved separately, coupling information is updated and exchanged between the systems, and the systems are re-solved, etc., until convergence is achieved. Trusted simulators, such as Modflow, are based on these conventional methods of coupling and work well in many cases. An advantage of the JFNK method is that it only requires calculation of the residual vector of the system of equations and thus can make use of existing simulators regardless of how the equations are formulated. This opens the possibility of coupling different process models via augmentation of a residual vector by each separate process, which often requires substantially fewer changes to the existing source code than if the processes were directly coupled. However, appropriate perturbation sizes need to be determined for accurate approximations of the Frechet derivative, which is not always straightforward. Furthermore, preconditioning is necessary for reasonable convergence of the linear solution required at each Kyrlov iteration. Existing preconditioners can be used and applied separately to each process which maximizes use of existing code and robust preconditioners. In this work, iteratively coupled parent-child local grid refinement models of groundwater flow and groundwater flow models with nonlinear exchanges to streams are used to demonstrate the utility of the JFNK approach for Modflow models. Use of incomplete Cholesky preconditioners with various levels of fill are examined on a suite of nonlinear and linear models to analyze the effect of the preconditioner. Comparisons of convergence and computer simulation time are made using conventional iteratively coupled methods and those based on Picard iteration to those formulated with JFNK to gain insights on the types of nonlinearities and system features that make one approach advantageous. Results indicate that nonlinearities associated with stream/aquifer exchanges are more problematic than those resulting from unconfined flow.

A Block Preconditioned Conjugate Gradient-type Iterative Solver for Linear Systems in Thermal Reservoir Simulation

NASA Astrophysics Data System (ADS)

Betté, Srinivas; Diaz, Julio C.; Jines, William R.; Steihaug, Trond

1986-11-01

A preconditioned residual-norm-reducing iterative solver is described. Based on a truncated form of the generalized-conjugate-gradient method for nonsymmetric systems of linear equations, the iterative scheme is very effective for linear systems generated in reservoir simulation of thermal oil recovery processes. As a consequence of employing an adaptive implicit finite-difference scheme to solve the model equations, the number of variables per cell-block varies dynamically over the grid. The data structure allows for 5- and 9-point operators in the areal model, 5-point in the cross-sectional model, and 7- and 11-point operators in the three-dimensional model. Block-diagonal-scaling of the linear system, done prior to iteration, is found to have a significant effect on the rate of convergence. Block-incomplete-LU-decomposition (BILU) and block-symmetric-Gauss-Seidel (BSGS) methods, which result in no fill-in, are used as preconditioning procedures. A full factorization is done on the well terms, and the cells are ordered in a manner which minimizes the fill-in in the well-column due to this factorization. The convergence criterion for the linear (inner) iteration is linked to that of the nonlinear (Newton) iteration, thereby enhancing the efficiency of the computation. The algorithm, with both BILU and BSGS preconditioners, is evaluated in the context of a variety of thermal simulation problems. The solver is robust and can be used with little or no user intervention.

Tuning without over-tuning: parametric uncertainty quantification for the NEMO ocean model

NASA Astrophysics Data System (ADS)

Williamson, Daniel B.; Blaker, Adam T.; Sinha, Bablu

2017-04-01

In this paper we discuss climate model tuning and present an iterative automatic tuning method from the statistical science literature. The method, which we refer to here as iterative refocussing (though also known as history matching), avoids many of the common pitfalls of automatic tuning procedures that are based on optimisation of a cost function, principally the over-tuning of a climate model due to using only partial observations. This avoidance comes by seeking to rule out parameter choices that we are confident could not reproduce the observations, rather than seeking the model that is closest to them (a procedure that risks over-tuning). We comment on the state of climate model tuning and illustrate our approach through three waves of iterative refocussing of the NEMO (Nucleus for European Modelling of the Ocean) ORCA2 global ocean model run at 2° resolution. We show how at certain depths the anomalies of global mean temperature and salinity in a standard configuration of the model exceeds 10 standard deviations away from observations and show the extent to which this can be alleviated by iterative refocussing without compromising model performance spatially. We show how model improvements can be achieved by simultaneously perturbing multiple parameters, and illustrate the potential of using low-resolution ensembles to tune NEMO ORCA configurations at higher resolutions.

Ottawa Model of Implementation Leadership and Implementation Leadership Scale: mapping concepts for developing and evaluating theory-based leadership interventions.

PubMed

Gifford, Wendy; Graham, Ian D; Ehrhart, Mark G; Davies, Barbara L; Aarons, Gregory A

2017-01-01

Leadership in health care is instrumental to creating a supportive organizational environment and positive staff attitudes for implementing evidence-based practices to improve patient care and outcomes. The purpose of this study is to demonstrate the alignment of the Ottawa Model of Implementation Leadership (O-MILe), a theoretical model for developing implementation leadership, with the Implementation Leadership Scale (ILS), an empirically validated tool for measuring implementation leadership. A secondary objective is to describe the methodological process for aligning concepts of a theoretical model with an independently established measurement tool for evaluating theory-based interventions. Modified template analysis was conducted to deductively map items of the ILS onto concepts of the O-MILe. An iterative process was used in which the model and scale developers (n=5) appraised the relevance, conceptual clarity, and fit of each ILS items with the O-MILe concepts through individual feedback and group discussions until consensus was reached. All 12 items of the ILS correspond to at least one O-MILe concept, demonstrating compatibility of the ILS as a measurement tool for the O-MILe theoretical constructs. The O-MILe provides a theoretical basis for developing implementation leadership, and the ILS is a compatible tool for measuring leadership based on the O-MILe. Used together, the O-MILe and ILS provide an evidence- and theory-based approach for developing and measuring leadership for implementing evidence-based practices in health care. Template analysis offers a convenient approach for determining the compatibility of independently developed evaluation tools to test theoretical models.

Ottawa Model of Implementation Leadership and Implementation Leadership Scale: mapping concepts for developing and evaluating theory-based leadership interventions

PubMed Central

Gifford, Wendy; Graham, Ian D; Ehrhart, Mark G; Davies, Barbara L; Aarons, Gregory A

2017-01-01

Purpose Leadership in health care is instrumental to creating a supportive organizational environment and positive staff attitudes for implementing evidence-based practices to improve patient care and outcomes. The purpose of this study is to demonstrate the alignment of the Ottawa Model of Implementation Leadership (O-MILe), a theoretical model for developing implementation leadership, with the Implementation Leadership Scale (ILS), an empirically validated tool for measuring implementation leadership. A secondary objective is to describe the methodological process for aligning concepts of a theoretical model with an independently established measurement tool for evaluating theory-based interventions. Methods Modified template analysis was conducted to deductively map items of the ILS onto concepts of the O-MILe. An iterative process was used in which the model and scale developers (n=5) appraised the relevance, conceptual clarity, and fit of each ILS items with the O-MILe concepts through individual feedback and group discussions until consensus was reached. Results All 12 items of the ILS correspond to at least one O-MILe concept, demonstrating compatibility of the ILS as a measurement tool for the O-MILe theoretical constructs. Conclusion The O-MILe provides a theoretical basis for developing implementation leadership, and the ILS is a compatible tool for measuring leadership based on the O-MILe. Used together, the O-MILe and ILS provide an evidence- and theory-based approach for developing and measuring leadership for implementing evidence-based practices in health care. Template analysis offers a convenient approach for determining the compatibility of independently developed evaluation tools to test theoretical models. PMID:29355212

Calibration and compensation method of three-axis geomagnetic sensor based on pre-processing total least square iteration

NASA Astrophysics Data System (ADS)

Zhou, Y.; Zhang, X.; Xiao, W.

2018-04-01

As the geomagnetic sensor is susceptible to interference, a pre-processing total least square iteration method is proposed for calibration compensation. Firstly, the error model of the geomagnetic sensor is analyzed and the correction model is proposed, then the characteristics of the model are analyzed and converted into nine parameters. The geomagnetic data is processed by Hilbert transform (HHT) to improve the signal-to-noise ratio, and the nine parameters are calculated by using the combination of Newton iteration method and the least squares estimation method. The sifter algorithm is used to filter the initial value of the iteration to ensure that the initial error is as small as possible. The experimental results show that this method does not need additional equipment and devices, can continuously update the calibration parameters, and better than the two-step estimation method, it can compensate geomagnetic sensor error well.

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

PubMed Central

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-01-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of TOF scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (Direct Image Reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias vs. variance performance to iterative TOF reconstruction with a matched resolution model. PMID:27032968

Analytic TOF PET reconstruction algorithm within DIRECT data partitioning framework

NASA Astrophysics Data System (ADS)

Matej, Samuel; Daube-Witherspoon, Margaret E.; Karp, Joel S.

2016-05-01

Iterative reconstruction algorithms are routinely used for clinical practice; however, analytic algorithms are relevant candidates for quantitative research studies due to their linear behavior. While iterative algorithms also benefit from the inclusion of accurate data and noise models the widespread use of time-of-flight (TOF) scanners with less sensitivity to noise and data imperfections make analytic algorithms even more promising. In our previous work we have developed a novel iterative reconstruction approach (DIRECT: direct image reconstruction for TOF) providing convenient TOF data partitioning framework and leading to very efficient reconstructions. In this work we have expanded DIRECT to include an analytic TOF algorithm with confidence weighting incorporating models of both TOF and spatial resolution kernels. Feasibility studies using simulated and measured data demonstrate that analytic-DIRECT with appropriate resolution and regularization filters is able to provide matched bias versus variance performance to iterative TOF reconstruction with a matched resolution model.

Geologic Mapping of Vesta

NASA Technical Reports Server (NTRS)

Yingst, R. A.; Mest, S. C.; Berman, D. C.; Garry, W. B.; Williams, D. A.; Buczkowski, D.; Jaumann, R.; Pieters, C. M.; De Sanctis, M. C.; Frigeri, A.;

Predictive vs. Empiric Assessment of Schistosomiasis: Implications for Treatment Projections in Ghana

PubMed Central

Kabore, Achille; Biritwum, Nana-Kwadwo; Downs, Philip W.; Soares Magalhaes, Ricardo J.; Zhang, Yaobi; Ottesen, Eric A.

2013-01-01

Background Mapping the distribution of schistosomiasis is essential to determine where control programs should operate, but because it is impractical to assess infection prevalence in every potentially endemic community, model-based geostatistics (MBG) is increasingly being used to predict prevalence and determine intervention strategies. Methodology/Principal Findings To assess the accuracy of MBG predictions for Schistosoma haematobium infection in Ghana, school surveys were evaluated at 79 sites to yield empiric prevalence values that could be compared with values derived from recently published MBG predictions. Based on these findings schools were categorized according to WHO guidelines so that practical implications of any differences could be determined. Using the mean predicted values alone, 21 of the 25 empirically determined ‘high-risk’ schools requiring yearly praziquantel would have been undertreated and almost 20% of the remaining schools would have been treated despite empirically-determined absence of infection – translating into 28% of the children in the 79 schools being undertreated and 12% receiving treatment in the absence of any demonstrated need. Conclusions/Significance Using the current predictive map for Ghana as a spatial decision support tool by aggregating prevalence estimates to the district level was clearly not adequate for guiding the national program, but the alternative of assessing each school in potentially endemic areas of Ghana or elsewhere is not at all feasible; modelling must be a tool complementary to empiric assessments. Thus for practical usefulness, predictive risk mapping should not be thought of as a one-time exercise but must, as in the current study, be an iterative process that incorporates empiric testing and model refining to create updated versions that meet the needs of disease control operational managers. PMID:23505584

RADARSAT-2 Polarimetric Radar Imaging for Lake Ice Mapping

NASA Astrophysics Data System (ADS)

Pan, F.; Kang, K.; Duguay, C. R.

2016-12-01

Changes in lake ice dates and duration are useful indicators for assessing long-term climate trends and variability in northern countries. Lake ice cover observations are also a valuable data source for predictions with numerical ice and weather forecasting models. In recent years, satellite remote sensing has assumed a greater role in providing observations of lake ice cover extent for both modeling and climate monitoring purposes. Polarimetric radar imaging has become a promising tool for lake ice mapping at high latitudes where meteorological conditions and polar darkness severely limit observations from optical sensors. In this study, we assessed and characterized the physical scattering mechanisms of lake ice from fully polarimetric RADARSAT-2 datasets obtained over Great Bear Lake, Canada, with the intent of classifying open water and different ice types during the freeze-up and break-up periods. Model-based and eigen-based decompositions were employed to construct the coherency matrix into deterministic scattering mechanisms. These procedures as well as basic polarimetric parameters were integrated into modified convolutional neural networks (CNN). The CNN were modified via introduction of a Markov random field into the higher iterative layers of networks for acquiring updated priors and classifying ice and open water areas over the lake. We show that the selected polarimetric parameters can help with interpretation of radar-ice/water interactions and can be used successfully for water-ice segmentation, including different ice types. As more satellite SAR sensors are being launched or planned, such as the Sentinel-1a/b series and the upcoming RADARSAT Constellation Mission, the rapid volume growth of data and their analysis require the development of robust automated algorithms. The approach developed in this study was therefore designed with the intent of moving towards fully automated mapping of lake ice for consideration by ice services.

Installation and Testing of ITER Integrated Modeling and Analysis Suite (IMAS) on DIII-D

NASA Astrophysics Data System (ADS)

Lao, L.; Kostuk, M.; Meneghini, O.; Smith, S.; Staebler, G.; Kalling, R.; Pinches, S.

2017-10-01

A critical objective of the ITER Integrated Modeling Program is the development of IMAS to support ITER plasma operation and research activities. An IMAS framework has been established based on the earlier work carried out within the EU. It consists of a physics data model and a workflow engine. The data model is capable of representing both simulation and experimental data and is applicable to ITER and other devices. IMAS has been successfully installed on a local DIII-D server using a flexible installer capable of managing the core data access tools (Access Layer and Data Dictionary) and optionally the Kepler workflow engine and coupling tools. A general adaptor for OMFIT (a workflow engine) is being built for adaptation of any analysis code to IMAS using a new IMAS universal access layer (UAL) interface developed from an existing OMFIT EU Integrated Tokamak Modeling UAL. Ongoing work includes development of a general adaptor for EFIT and TGLF based on this new UAL that can be readily extended for other physics codes within OMFIT. Work supported by US DOE under DE-FC02-04ER54698.

Function representation with circle inversion map systems

NASA Astrophysics Data System (ADS)

Boreland, Bryson; Kunze, Herb

2017-01-01

The fractals literature develops the now well-known concept of local iterated function systems (using affine maps) with grey-level maps (LIFSM) as an approach to function representation in terms of the associated fixed point of the so-called fractal transform. While originally explored as a method to achieve signal (and 2-D image) compression, more recent work has explored various aspects of signal and image processing using this machinery. In this paper, we develop a similar framework for function representation using circle inversion map systems. Given a circle C with centre õ and radius r, inversion with respect to C transforms the point p˜ to the point p˜', such that p˜ and p˜' lie on the same radial half-line from õ and d(õ, p˜)d(õ, p˜') = r2, where d is Euclidean distance. We demonstrate the results with an example.

Quantitative evaluation for small surface damage based on iterative difference and triangulation of 3D point cloud

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Guo, Quanli; Wang, Zhenchun; Yang, Degong

2018-03-01

This paper proposes a non-contact, non-destructive evaluation method for the surface damage of high-speed sliding electrical contact rails. The proposed method establishes a model of damage identification and calculation. A laser scanning system is built to obtain the 3D point cloud data of the rail surface. In order to extract the damage region of the rail surface, the 3D point cloud data are processed using iterative difference, nearest neighbours search and a data registration algorithm. The curvature of the point cloud data in the damage region is mapped to RGB color information, which can directly reflect the change trend of the curvature of the point cloud data in the damage region. The extracted damage region is divided into three prism elements by a method of triangulation. The volume and mass of a single element are calculated by the method of geometric segmentation. Finally, the total volume and mass of the damage region are obtained by the principle of superposition. The proposed method is applied to several typical injuries and the results are discussed. The experimental results show that the algorithm can identify damage shapes and calculate damage mass with milligram precision, which are useful for evaluating the damage in a further research stage.

2D modeling of DC potential structures induced by RF sheaths with transverse currents in front of ICRF antenna

NASA Astrophysics Data System (ADS)

Faudot, E.; Heuraux, S.; Colas, L.

2005-09-01

Understanding DC potential generation in front of ICRF antennas is crucial for long pulse high RF power systems. DC potentials are produced by sheath rectification of these RF potentials. To reach this goal, near RF parallel electric fields have to be computed in 3D and integrated along open magnetic field lines to yield a 2D RF potential map in a transverse plane. DC potentials are produced by sheath rectification of these RF potentials. As RF potentials are spatially inhomogeneous, transverse polarization currents are created, modifying RF and DC maps. Such modifications are quantified on a `test map' having initially a Gaussian shape and assuming that the map remains Gaussian near its summit,the time behavior of the peak can be estimated analytically in presence of polarization current as a function of its width r0 and amplitude φ0 (normalized to a characteristic length for transverse transport and to the local temperature). A `peaking factor' is built from the DC peak potential normalized to φ0, and validated with a 2D fluid code and a 2D PIC code (XOOPIC). In an unexpected way transverse currents can increase this factor. Realistic situations of a Tore Supra antenna are also studied, with self-consistent near fields provided by ICANT code. Basic processes will be detailed and an evaluation of the `peaking factor' for ITER will be presented for a given configuration.

2D modeling of DC potential structures induced by RF sheaths with transverse currents in front of ICRF antenna

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faudot, E.; Heuraux, S.; Colas, L.

2005-09-26

Understanding DC potential generation in front of ICRF antennas is crucial for long pulse high RF power systems. DC potentials are produced by sheath rectification of these RF potentials. To reach this goal, near RF parallel electric fields have to be computed in 3D and integrated along open magnetic field lines to yield a 2D RF potential map in a transverse plane. DC potentials are produced by sheath rectification of these RF potentials. As RF potentials are spatially inhomogeneous, transverse polarization currents are created, modifying RF and DC maps. Such modifications are quantified on a 'test map' having initially amore » Gaussian shape and assuming that the map remains Gaussian near its summit,the time behavior of the peak can be estimated analytically in presence of polarization current as a function of its width r0 and amplitude {phi}0 (normalized to a characteristic length for transverse transport and to the local temperature). A 'peaking factor' is built from the DC peak potential normalized to {phi}0, and validated with a 2D fluid code and a 2D PIC code (XOOPIC). In an unexpected way transverse currents can increase this factor. Realistic situations of a Tore Supra antenna are also studied, with self-consistent near fields provided by ICANT code. Basic processes will be detailed and an evaluation of the 'peaking factor' for ITER will be presented for a given configuration.« less

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Direct determination of one-dimensional interphase structures using normalized crystal truncation rod analysis

DOE PAGES

Kawaguchi, Tomoya; Liu, Yihua; Reiter, Anthony; ...

2018-04-20

Here, a one-dimensional non-iterative direct method was employed for normalized crystal truncation rod analysis. The non-iterative approach, utilizing the Kramers–Kronig relation, avoids the ambiguities due to an improper initial model or incomplete convergence in the conventional iterative methods. The validity and limitations of the present method are demonstrated through both numerical simulations and experiments with Pt(111) in a 0.1 M CsF aqueous solution. The present method is compared with conventional iterative phase-retrieval methods.

Numerical reconstruction of unknown Robin inclusions inside a heat conductor by a non-iterative method

NASA Astrophysics Data System (ADS)

Nakamura, Gen; Wang, Haibing

2017-05-01

Consider the problem of reconstructing unknown Robin inclusions inside a heat conductor from boundary measurements. This problem arises from active thermography and is formulated as an inverse boundary value problem for the heat equation. In our previous works, we proposed a sampling-type method for reconstructing the boundary of the Robin inclusion and gave its rigorous mathematical justification. This method is non-iterative and based on the characterization of the solution to the so-called Neumann- to-Dirichlet map gap equation. In this paper, we give a further investigation of the reconstruction method from both the theoretical and numerical points of view. First, we clarify the solvability of the Neumann-to-Dirichlet map gap equation and establish a relation of its solution to the Green function associated with an initial-boundary value problem for the heat equation inside the Robin inclusion. This naturally provides a way of computing this Green function from the Neumann-to-Dirichlet map and explains what is the input for the linear sampling method. Assuming that the Neumann-to-Dirichlet map gap equation has a unique solution, we also show the convergence of our method for noisy measurements. Second, we give the numerical implementation of the reconstruction method for two-dimensional spatial domains. The measurements for our inverse problem are simulated by solving the forward problem via the boundary integral equation method. Numerical results are presented to illustrate the efficiency and stability of the proposed method. By using a finite sequence of transient input over a time interval, we propose a new sampling method over the time interval by single measurement which is most likely to be practical.

High-resolution myocardial T1 mapping using single-shot inversion recovery fast low-angle shot MRI with radial undersampling and iterative reconstruction

PubMed Central

Joseph, Arun A; Kalentev, Oleksandr; Merboldt, Klaus-Dietmar; Voit, Dirk; Roeloffs, Volkert B; van Zalk, Maaike; Frahm, Jens

2016-01-01

Objective: To develop a novel method for rapid myocardial T1 mapping at high spatial resolution. Methods: The proposed strategy represents a single-shot inversion recovery experiment triggered to early diastole during a brief breath-hold. The measurement combines an adiabatic inversion pulse with a real-time readout by highly undersampled radial FLASH, iterative image reconstruction and T1 fitting with automatic deletion of systolic frames. The method was implemented on a 3-T MRI system using a graphics processing unit-equipped bypass computer for online application. Validations employed a T1 reference phantom including analyses at simulated heart rates from 40 to 100 beats per minute. In vivo applications involved myocardial T1 mapping in short-axis views of healthy young volunteers. Results: At 1-mm in-plane resolution and 6-mm section thickness, the inversion recovery measurement could be shortened to 3 s without compromising T1 quantitation. Phantom studies demonstrated T1 accuracy and high precision for values ranging from 300 to 1500 ms and up to a heart rate of 100 beats per minute. Similar results were obtained in vivo yielding septal T1 values of 1246 ± 24 ms (base), 1256 ± 33 ms (mid-ventricular) and 1288 ± 30 ms (apex), respectively (mean ± standard deviation, n = 6). Conclusion: Diastolic myocardial T1 mapping with use of single-shot inversion recovery FLASH offers high spatial resolution, T1 accuracy and precision, and practical robustness and speed. Advances in knowledge: The proposed method will be beneficial for clinical applications relying on native and post-contrast T1 quantitation. PMID:27759423

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Characterization of the ITER model negative ion source during long pulse operation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hemsworth, R.S.; Boilson, D.; Crowley, B.

2006-03-15

It is foreseen to operate the neutral beam system of the International Thermonuclear Experimental Reactor (ITER) for pulse lengths extending up to 1 h. The performance of the KAMABOKO III negative ion source, which is a model of the source designed for ITER, is being studied on the MANTIS test bed at Cadarache. This article reports the latest results from the characterization of the ion source, in particular electron energy distribution measurements and the comparison between positive ion and negative ion extraction from the source.

Idealized digital models for conical reed instruments, with focus on the internal pressure waveform.

PubMed

Kergomard, J; Guillemain, P; Silva, F; Karkar, S

2016-02-01

Two models for the generation of self-oscillations of reed conical woodwinds are presented. The models use the fewest parameters (of either the resonator or the exciter), whose influence can be quickly explored. The formulation extends iterated maps obtained for lossless cylindrical pipes without reed dynamics. It uses spherical wave variables in idealized resonators, with one parameter more than for cylinders: the missing length of the cone. The mouthpiece volume equals that of the missing part of the cone, and is implemented as either a cylindrical pipe (first model) or a lumped element (second model). Only the first model adds a length parameter for the mouthpiece and leads to the solving of an implicit equation. For the second model, any shape of nonlinear characteristic can be directly considered. The complex characteristic impedance for spherical waves requires sampling times smaller than a round trip in the resonator. The convergence of the two models is shown when the length of the cylindrical mouthpiece tends to zero. The waveform is in semi-quantitative agreement with experiment. It is concluded that the oscillations of the positive episode of the mouthpiece pressure are related to the length of the missing part, not to the reed dynamics.

Comparative Reannotation of 21 Aspergillus Genomes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Salamov, Asaf; Riley, Robert; Kuo, Alan

2013-03-08

We used comparative gene modeling to reannotate 21 Aspergillus genomes. Initial automatic annotation of individual genomes may contain some errors of different nature, e.g. missing genes, incorrect exon-intron structures, 'chimeras', which fuse 2 or more real genes or alternatively splitting some real genes into 2 or more models. The main premise behind the comparative modeling approach is that for closely related genomes most orthologous families have the same conserved gene structure. The algorithm maps all gene models predicted in each individual Aspergillus genome to the other genomes and, for each locus, selects from potentially many competing models, the one whichmore » most closely resembles the orthologous genes from other genomes. This procedure is iterated until no further change in gene models is observed. For Aspergillus genomes we predicted in total 4503 new gene models ( ~;;2percent per genome), supported by comparative analysis, additionally correcting ~;;18percent of old gene models. This resulted in a total of 4065 more genes with annotated PFAM domains (~;;3percent increase per genome). Analysis of a few genomes with EST/transcriptomics data shows that the new annotation sets also have a higher number of EST-supported splice sites at exon-intron boundaries.« less

RJMCMC based Text Placement to Optimize Label Placement and Quantity

NASA Astrophysics Data System (ADS)

Touya, Guillaume; Chassin, Thibaud

2018-05-01

Label placement is a tedious task in map design, and its automation has long been a goal for researchers in cartography, but also in computational geometry. Methods that search for an optimal or nearly optimal solution that satisfies a set of constraints, such as label overlapping, have been proposed in the literature. Most of these methods mainly focus on finding the optimal position for a given set of labels, but rarely allow the removal of labels as part of the optimization. This paper proposes to apply an optimization technique called Reversible-Jump Markov Chain Monte Carlo that enables to easily model the removal or addition during the optimization iterations. The method, quite preliminary for now, is tested on a real dataset, and the first results are encouraging.

Automated multiplex genome-scale engineering in yeast

PubMed Central

Si, Tong; Chao, Ran; Min, Yuhao; Wu, Yuying; Ren, Wen; Zhao, Huimin

2017-01-01

Genome-scale engineering is indispensable in understanding and engineering microorganisms, but the current tools are mainly limited to bacterial systems. Here we report an automated platform for multiplex genome-scale engineering in Saccharomyces cerevisiae, an important eukaryotic model and widely used microbial cell factory. Standardized genetic parts encoding overexpression and knockdown mutations of >90% yeast genes are created in a single step from a full-length cDNA library. With the aid of CRISPR-Cas, these genetic parts are iteratively integrated into the repetitive genomic sequences in a modular manner using robotic automation. This system allows functional mapping and multiplex optimization on a genome scale for diverse phenotypes including cellulase expression, isobutanol production, glycerol utilization and acetic acid tolerance, and may greatly accelerate future genome-scale engineering endeavours in yeast. PMID:28469255

Computer-assisted map projection research

USGS Publications Warehouse

Snyder, John Parr

1985-01-01

Computers have opened up areas of map projection research which were previously too complicated to utilize, for example, using a least-squares fit to a very large number of points. One application has been in the efficient transfer of data between maps on different projections. While the transfer of moderate amounts of data is satisfactorily accomplished using the analytical map projection formulas, polynomials are more efficient for massive transfers. Suitable coefficients for the polynomials may be determined more easily for general cases using least squares instead of Taylor series. A second area of research is in the determination of a map projection fitting an unlabeled map, so that accurate data transfer can take place. The computer can test one projection after another, and include iteration where required. A third area is in the use of least squares to fit a map projection with optimum parameters to the region being mapped, so that distortion is minimized. This can be accomplished for standard conformal, equalarea, or other types of projections. Even less distortion can result if complex transformations of conformal projections are utilized. This bulletin describes several recent applications of these principles, as well as historical usage and background.

Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

NASA Astrophysics Data System (ADS)

Halligan, K. Q.; Roberts, D. A.

2006-12-01

Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation vigor or senescence. Additionally, the strength of hyperspectral data for vegetation classification suggests these data have additional utility for modeling carbon flux dynamics by allowing more accurate plant functional type mapping.

An Iterative Needs Assessment/Evaluation Model for a Japanese University English-Language Program

ERIC Educational Resources Information Center

Brown, Kathleen A.

2009-01-01

The focus of this study is the development and implementation of the Iterative Needs Assessment/Evaluation Model for use as part of an English curriculum reform project at a four-year university in Japan. Three questions were addressed in this study: (a) what model components were necessary for use in a Japanese university setting; (b) what survey…

Learning Efficient Sparse and Low Rank Models.

PubMed

Sprechmann, P; Bronstein, A M; Sapiro, G

2015-09-01

Parsimony, including sparsity and low rank, has been shown to successfully model data in numerous machine learning and signal processing tasks. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with parsimony-promoting terms. The inherently sequential structure and data-dependent complexity and latency of iterative optimization constitute a major limitation in many applications requiring real-time performance or involving large-scale data. Another limitation encountered by these modeling techniques is the difficulty of their inclusion in discriminative learning scenarios. In this work, we propose to move the emphasis from the model to the pursuit algorithm, and develop a process-centric view of parsimonious modeling, in which a learned deterministic fixed-complexity pursuit process is used in lieu of iterative optimization. We show a principled way to construct learnable pursuit process architectures for structured sparse and robust low rank models, derived from the iteration of proximal descent algorithms. These architectures learn to approximate the exact parsimonious representation at a fraction of the complexity of the standard optimization methods. We also show that appropriate training regimes allow to naturally extend parsimonious models to discriminative settings. State-of-the-art results are demonstrated on several challenging problems in image and audio processing with several orders of magnitude speed-up compared to the exact optimization algorithms.

Video encryption using chaotic masks in joint transform correlator

NASA Astrophysics Data System (ADS)

Saini, Nirmala; Sinha, Aloka

2015-03-01

A real-time optical video encryption technique using a chaotic map has been reported. In the proposed technique, each frame of video is encrypted using two different chaotic random phase masks in the joint transform correlator architecture. The different chaotic random phase masks can be obtained either by using different iteration levels or by using different seed values of the chaotic map. The use of different chaotic random phase masks makes the decryption process very complex for an unauthorized person. Optical, as well as digital, methods can be used for video encryption but the decryption is possible only digitally. To further enhance the security of the system, the key parameters of the chaotic map are encoded using RSA (Rivest-Shamir-Adleman) public key encryption. Numerical simulations are carried out to validate the proposed technique.

A semi-automatic method for analysis of landscape elements using Shuttle Radar Topography Mission and Landsat ETM+ data

NASA Astrophysics Data System (ADS)

Ehsani, Amir Houshang; Quiel, Friedrich

2009-02-01

In this paper, we demonstrate artificial neural networks—self-organizing map (SOM)—as a semi-automatic method for extraction and analysis of landscape elements in the man and biosphere reserve "Eastern Carpathians". The Shuttle Radar Topography Mission (SRTM) collected data to produce generally available digital elevation models (DEM). Together with Landsat Thematic Mapper data, this provides a unique, consistent and nearly worldwide data set. To integrate the DEM with Landsat data, it was re-projected from geographic coordinates to UTM with 28.5 m spatial resolution using cubic convolution interpolation. To provide quantitative morphometric parameters, first-order (slope) and second-order derivatives of the DEM—minimum curvature, maximum curvature and cross-sectional curvature—were calculated by fitting a bivariate quadratic surface with a window size of 9×9 pixels. These surface curvatures are strongly related to landform features and geomorphological processes. Four morphometric parameters and seven Landsat-enhanced thematic mapper (ETM+) bands were used as input for the SOM algorithm. Once the network weights have been randomly initialized, different learning parameter sets, e.g. initial radius, final radius and number of iterations, were investigated. An optimal SOM with 20 classes using 1000 iterations and a final neighborhood radius of 0.05 provided a low average quantization error of 0.3394 and was used for further analysis. The effect of randomization of initial weights for optimal SOM was also studied. Feature space analysis, three-dimensional inspection and auxiliary data facilitated the assignment of semantic meaning to the output classes in terms of landform, based on morphometric analysis, and land use, based on spectral properties. Results were displayed as thematic map of landscape elements according to form, cover and slope. Spectral and morphometric signature analysis with corresponding zoom samples superimposed by contour lines were compared in detail to clarify the role of morphometric parameters to separate landscape elements. The results revealed the efficiency of SOM to integrate SRTM and Landsat data in landscape analysis. Despite the stochastic nature of SOM, the results in this particular study are not sensitive to randomization of initial weight vectors if many iterations are used. This procedure is reproducible for the same application with consistent results.

Attenuation correction strategies for multi-energy photon emitters using SPECT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pretorius, P.H.; King, M.A.; Pan, T.S.

1996-12-31

The aim of this study was to investigate whether the photopeak window projections from different energy photons can be combined into a single window for reconstruction or if it is better to not combine the projections due to differences in the attenuation maps required for each photon energy. The mathematical cardiac torso (MCAT) phantom was modified to simulate the uptake of Ga-67 in the human body. Four spherical hot tumors were placed in locations which challenged attenuation correction. An analytical 3D projector with attenuation and detector response included was used to generate projection sets. Data were reconstructed using filtered backprojectionmore » (FBP) reconstruction with Butterworth filtering in conjunction with one iteration of Chang attenuation correction, and with 5 and 10 iterations of ordered-subset maximum-likelihood expectation-maximization reconstruction. To serve as a standard for comparison, the projection sets obtained from the two energies were first reconstructed separately using their own attenuation maps. The emission data obtained from both energies were added and reconstructed using the following attenuation strategies: (1) the 93 keV attenuation map for attenuation correction, (2) the 185 keV attenuation map for attenuation correction, (3) using a weighted mean obtained from combining the 93 keV and 185 keV maps, and (4) an ordered subset approach which combines both energies. The central count ratio (CCR) and total count ratio (TCR) were used to compare the performance of the different strategies. Compared to the standard method, results indicate an over-estimation with strategy 1, an under-estimation with strategy 2 and comparable results with strategies 3 and 4. In all strategies, the CCR`s of sphere 4 were under-estimated, although TCR`s were comparable to that of the other locations. The weighted mean and ordered subset strategies for attenuation correction were of comparable accuracy to reconstruction of the windows separately.« less

Improvements in metabolic flux analysis using carbon bond labeling experiments: bondomer balancing and Boolean function mapping.

PubMed

Sriram, Ganesh; Shanks, Jacqueline V

2004-04-01

The biosynthetically directed fractional (13)C labeling method for metabolic flux evaluation relies on performing a 2-D [(13)C, (1)H] NMR experiment on extracts from organisms cultured on a uniformly labeled carbon substrate. This article focuses on improvements in the interpretation of data obtained from such an experiment by employing the concept of bondomers. Bondomers take into account the natural abundance of (13)C; therefore many bondomers in a real network are zero, and can be precluded a priori--thus resulting in fewer balances. Using this method, we obtained a set of linear equations which can be solved to obtain analytical formulas for NMR-measurable quantities in terms of fluxes in glycolysis and the pentose phosphate pathways. For a specific case of this network with four degrees of freedom, a priori identifiability of the fluxes was shown possible for any set of fluxes. For a more general case with five degrees of freedom, the fluxes were shown identifiable for a representative set of fluxes. Minimal sets of measurements which best identify the fluxes are listed. Furthermore, we have delineated Boolean function mapping, a new method to iteratively simulate bondomer abundances or efficiently convert carbon skeleton rearrangement information to mapping matrices. The efficiency of this method is expected to be valuable while analyzing metabolic networks which are not completely known (such as in plant metabolism) or while implementing iterative bondomer balancing methods.

Sequence analysis by iterated maps, a review.

PubMed

Almeida, Jonas S

2014-05-01

Among alignment-free methods, Iterated Maps (IMs) are on a particular extreme: they are also scale free (order free). The use of IMs for sequence analysis is also distinct from other alignment-free methodologies in being rooted in statistical mechanics instead of computational linguistics. Both of these roots go back over two decades to the use of fractal geometry in the characterization of phase-space representations. The time series analysis origin of the field is betrayed by the title of the manuscript that started this alignment-free subdomain in 1990, 'Chaos Game Representation'. The clash between the analysis of sequences as continuous series and the better established use of Markovian approaches to discrete series was almost immediate, with a defining critique published in same journal 2 years later. The rest of that decade would go by before the scale-free nature of the IM space was uncovered. The ensuing decade saw this scalability generalized for non-genomic alphabets as well as an interest in its use for graphic representation of biological sequences. Finally, in the past couple of years, in step with the emergence of BigData and MapReduce as a new computational paradigm, there is a surprising third act in the IM story. Multiple reports have described gains in computational efficiency of multiple orders of magnitude over more conventional sequence analysis methodologies. The stage appears to be now set for a recasting of IMs with a central role in processing nextgen sequencing results.

Automated main-chain model building by template matching and iterative fragment extension.

PubMed

Terwilliger, Thomas C

2003-01-01

An algorithm for the automated macromolecular model building of polypeptide backbones is described. The procedure is hierarchical. In the initial stages, many overlapping polypeptide fragments are built. In subsequent stages, the fragments are extended and then connected. Identification of the locations of helical and beta-strand regions is carried out by FFT-based template matching. Fragment libraries of helices and beta-strands from refined protein structures are then positioned at the potential locations of helices and strands and the longest segments that fit the electron-density map are chosen. The helices and strands are then extended using fragment libraries consisting of sequences three amino acids long derived from refined protein structures. The resulting segments of polypeptide chain are then connected by choosing those which overlap at two or more C(alpha) positions. The fully automated procedure has been implemented in RESOLVE and is capable of model building at resolutions as low as 3.5 A. The algorithm is useful for building a preliminary main-chain model that can serve as a basis for refinement and side-chain addition.

An efficient method for model refinement in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zirak, A. R.; Khademi, M.

2007-11-01

Diffuse optical tomography (DOT) is a non-linear, ill-posed, boundary value and optimization problem which necessitates regularization. Also, Bayesian methods are suitable owing to measurements data are sparse and correlated. In such problems which are solved with iterative methods, for stabilization and better convergence, the solution space must be small. These constraints subject to extensive and overdetermined system of equations which model retrieving criteria specially total least squares (TLS) must to refine model error. Using TLS is limited to linear systems which is not achievable when applying traditional Bayesian methods. This paper presents an efficient method for model refinement using regularized total least squares (RTLS) for treating on linearized DOT problem, having maximum a posteriori (MAP) estimator and Tikhonov regulator. This is done with combination Bayesian and regularization tools as preconditioner matrices, applying them to equations and then using RTLS to the resulting linear equations. The preconditioning matrixes are guided by patient specific information as well as a priori knowledge gained from the training set. Simulation results illustrate that proposed method improves the image reconstruction performance and localize the abnormally well.

František Nábělek's Iter Turcico-Persicum 1909-1910 - database and digitized herbarium collection.

PubMed

Kempa, Matúš; Edmondson, John; Lack, Hans Walter; Smatanová, Janka; Marhold, Karol

2016-01-01

The Czech botanist František Nábělek (1884-1965) explored the Middle East in 1909-1910, visiting what are now Israel, Palestine, Jordan, Syria, Lebanon, Iraq, Bahrain, Iran and Turkey. He described four new genera, 78 species, 69 varieties and 38 forms of vascular plants, most of these in his work Iter Turcico-Persicum (1923-1929). The main herbarium collection of Iter Turcico-Persicum comprises 4163 collection numbers (some with duplicates), altogether 6465 specimens. It is currently deposited in the herbarium SAV. In addition, some fragments and duplicates are found in B, E, W and WU. The whole collection at SAV was recently digitized and both images and metadata are available via web portal www.nabelek.sav.sk, and through JSTOR Global Plants and the Biological Collection Access Service. Most localities were georeferenced and the web portal provides a mapping facility. Annotation of specimens is available via the AnnoSys facility. For each specimen a CETAF stable identifier is provided enabling the correct reference to the image and metadata.

Dynamics of a new family of iterative processes for quadratic polynomials

NASA Astrophysics Data System (ADS)

Gutiérrez, J. M.; Hernández, M. A.; Romero, N.

2010-03-01

In this work we show the presence of the well-known Catalan numbers in the study of the convergence and the dynamical behavior of a family of iterative methods for solving nonlinear equations. In fact, we introduce a family of methods, depending on a parameter . These methods reach the order of convergence m+2 when they are applied to quadratic polynomials with different roots. Newton's and Chebyshev's methods appear as particular choices of the family appear for m=0 and m=1, respectively. We make both analytical and graphical studies of these methods, which give rise to rational functions defined in the extended complex plane. Firstly, we prove that the coefficients of the aforementioned family of iterative processes can be written in terms of the Catalan numbers. Secondly, we make an incursion into its dynamical behavior. In fact, we show that the rational maps related to these methods can be written in terms of the entries of the Catalan triangle. Next we analyze its general convergence, by including some computer plots showing the intricate structure of the Universal Julia sets associated with the methods.

František Nábělek’s Iter Turcico-Persicum 1909–1910 – database and digitized herbarium collection

PubMed Central

Kempa, Matúš; Edmondson, John; Lack, Hans Walter; Smatanová, Janka; Marhold, Karol

2016-01-01

Abstract The Czech botanist František Nábělek (1884−1965) explored the Middle East in 1909-1910, visiting what are now Israel, Palestine, Jordan, Syria, Lebanon, Iraq, Bahrain, Iran and Turkey. He described four new genera, 78 species, 69 varieties and 38 forms of vascular plants, most of these in his work Iter Turcico-Persicum (1923−1929). The main herbarium collection of Iter Turcico-Persicum comprises 4163 collection numbers (some with duplicates), altogether 6465 specimens. It is currently deposited in the herbarium SAV. In addition, some fragments and duplicates are found in B, E, W and WU. The whole collection at SAV was recently digitized and both images and metadata are available via web portal www.nabelek.sav.sk, and through JSTOR Global Plants and the Biological Collection Access Service. Most localities were georeferenced and the web portal provides a mapping facility. Annotation of specimens is available via the AnnoSys facility. For each specimen a CETAF stable identifier is provided enabling the correct reference to the image and metadata. PMID:28127245

Analysis of Anderson Acceleration on a Simplified Neutronics/Thermal Hydraulics System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Toth, Alex; Kelley, C. T.; Slattery, Stuart R

ABSTRACT A standard method for solving coupled multiphysics problems in light water reactors is Picard iteration, which sequentially alternates between solving single physics applications. This solution approach is appealing due to simplicity of implementation and the ability to leverage existing software packages to accurately solve single physics applications. However, there are several drawbacks in the convergence behavior of this method; namely slow convergence and the necessity of heuristically chosen damping factors to achieve convergence in many cases. Anderson acceleration is a method that has been seen to be more robust and fast converging than Picard iteration for many problems, withoutmore » significantly higher cost per iteration or complexity of implementation, though its effectiveness in the context of multiphysics coupling is not well explored. In this work, we develop a one-dimensional model simulating the coupling between the neutron distribution and fuel and coolant properties in a single fuel pin. We show that this model generally captures the convergence issues noted in Picard iterations which couple high-fidelity physics codes. We then use this model to gauge potential improvements with regard to rate of convergence and robustness from utilizing Anderson acceleration as an alternative to Picard iteration.« less

A method of recovering the initial vectors of globally coupled map lattices based on symbolic dynamics

NASA Astrophysics Data System (ADS)

Sun, Li-Sha; Kang, Xiao-Yun; Zhang, Qiong; Lin, Lan-Xin

2011-12-01

Based on symbolic dynamics, a novel computationally efficient algorithm is proposed to estimate the unknown initial vectors of globally coupled map lattices (CMLs). It is proved that not all inverse chaotic mapping functions are satisfied for contraction mapping. It is found that the values in phase space do not always converge on their initial values with respect to sufficient backward iteration of the symbolic vectors in terms of global convergence or divergence (CD). Both CD property and the coupling strength are directly related to the mapping function of the existing CML. Furthermore, the CD properties of Logistic, Bernoulli, and Tent chaotic mapping functions are investigated and compared. Various simulation results and the performances of the initial vector estimation with different signal-to-noise ratios (SNRs) are also provided to confirm the proposed algorithm. Finally, based on the spatiotemporal chaotic characteristics of the CML, the conditions of estimating the initial vectors using symbolic dynamics are discussed. The presented method provides both theoretical and experimental results for better understanding and characterizing the behaviours of spatiotemporal chaotic systems.

Heterogeneous fractionation profiles of meta-analytic coactivation networks.

PubMed

Laird, Angela R; Riedel, Michael C; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L; Eickhoff, Simon B; Smith, Stephen M; Fox, Peter T; Sutherland, Matthew T

2017-04-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Heterogeneous fractionation profiles of meta-analytic coactivation networks

PubMed Central

Laird, Angela R.; Riedel, Michael C.; Okoe, Mershack; Jianu, Radu; Ray, Kimberly L.; Eickhoff, Simon B.; Smith, Stephen M.; Fox, Peter T.; Sutherland, Matthew T.

2017-01-01

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d = 20 to 300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how “parent” functional brain systems decompose into constituent “child” sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication. PMID:28222386

Thermo-mechanical Modelling of Pebble Beds in Fusion Blankets and its Implementation by a Return-Mapping Algorithm

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gan, Yixiang; Kamlah, Marc

In this investigation, a thermo-mechanical model of pebble beds is adopted and developed based on experiments by Dr. Reimann at Forschungszentrum Karlsruhe (FZK). The framework of the present material model is composed of a non-linear elastic law, the Drucker-Prager-Cap theory, and a modified creep law. Furthermore, the volumetric inelastic strain dependent thermal conductivity of beryllium pebble beds is taken into account and full thermo-mechanical coupling is considered. Investigation showed that the Drucker-Prager-Cap model implemented in ABAQUS can not fulfill the requirements of both the prediction of large creep strains and the hardening behaviour caused by creep, which are of importancemore » with respect to the application of pebble beds in fusion blankets. Therefore, UMAT (user defined material's mechanical behaviour) and UMATHT (user defined material's thermal behaviour) routines are used to re-implement the present thermo-mechanical model in ABAQUS. An elastic predictor radial return mapping algorithm is used to solve the non-associated plasticity iteratively, and a proper tangent stiffness matrix is obtained for cost-efficiency in the calculation. An explicit creep mechanism is adopted for the prediction of time-dependent behaviour in order to represent large creep strains in high temperature. Finally, the thermo-mechanical interactions are implemented in a UMATHT routine for the coupled analysis. The oedometric compression tests and creep tests of pebble beds at different temperatures are simulated with the help of the present UMAT and UMATHT routines, and the comparison between the simulation and the experiments is made. (authors)« less

Improved method for retinotopy constrained source estimation of visual evoked responses

PubMed Central

Hagler, Donald J.; Dale, Anders M.

2011-01-01

Retinotopy constrained source estimation (RCSE) is a method for non-invasively measuring the time courses of activation in early visual areas using magnetoencephalography (MEG) or electroencephalography (EEG). Unlike conventional equivalent current dipole or distributed source models, the use of multiple, retinotopically-mapped stimulus locations to simultaneously constrain the solutions allows for the estimation of independent waveforms for visual areas V1, V2, and V3, despite their close proximity to each other. We describe modifications that improve the reliability and efficiency of this method. First, we find that increasing the number and size of visual stimuli results in source estimates that are less susceptible to noise. Second, to create a more accurate forward solution, we have explicitly modeled the cortical point spread of individual visual stimuli. Dipoles are represented as extended patches on the cortical surface, which take into account the estimated receptive field size at each location in V1, V2, and V3 as well as the contributions from contralateral, ipsilateral, dorsal, and ventral portions of the visual areas. Third, we implemented a map fitting procedure to deform a template to match individual subject retinotopic maps derived from functional magnetic resonance imaging (fMRI). This improves the efficiency of the overall method by allowing automated dipole selection, and it makes the results less sensitive to physiological noise in fMRI retinotopy data. Finally, the iteratively reweighted least squares (IRLS) method was used to reduce the contribution from stimulus locations with high residual error for robust estimation of visual evoked responses. PMID:22102418

A fresh look at electron cyclotron current drive power requirements for stabilization of tearing modes in ITER

DOE Office of Scientific and Technical Information (OSTI.GOV)

La Haye, R. J., E-mail: lahaye@fusion.gat.com

2015-12-10

ITER is an international project to design and build an experimental fusion reactor based on the “tokamak” concept. ITER relies upon localized electron cyclotron current drive (ECCD) at the rational safety factor q=2 to suppress or stabilize the expected poloidal mode m=2, toroidal mode n=1 neoclassical tearing mode (NTM) islands. Such islands if unmitigated degrade energy confinement, lock to the resistive wall (stop rotating), cause loss of “H-mode” and induce disruption. The International Tokamak Physics Activity (ITPA) on MHD, Disruptions and Magnetic Control joint experiment group MDC-8 on Current Drive Prevention/Stabilization of Neoclassical Tearing Modes started in 2005, after whichmore » assessments were made for the requirements for ECCD needed in ITER, particularly that of rf power and alignment on q=2 [1]. Narrow well-aligned rf current parallel to and of order of one percent of the total plasma current is needed to replace the “missing” current in the island O-points and heal or preempt (avoid destabilization by applying ECCD on q=2 in absence of the mode) the island [2-4]. This paper updates the advances in ECCD stabilization on NTMs learned in DIII-D experiments and modeling during the last 5 to 10 years as applies to stabilization by localized ECCD of tearing modes in ITER. This includes the ECCD (inside the q=1 radius) stabilization of the NTM “seeding” instability known as sawteeth (m/n=1/1) [5]. Recent measurements in DIII-D show that the ITER-similar current profile is classically unstable, curvature stabilization must not be neglected, and the small island width stabilization effect from helical ion polarization currents is stronger than was previously thought [6]. The consequences of updated assumptions in ITER modeling of the minimum well-aligned ECCD power needed are all-in-all favorable (and well-within the ITER 24 gyrotron capability) when all effects are included. However, a “wild card” may be broadening of the localized ECCD by the presence of the island; various theories predict broadening could occur and there is experimental evidence for broadening in DIII-D. Wider than now expected ECCD in ITER would make alignment easier to do but weaken the stabilization and thus require more rf power. In addition to updated modeling for ITER, advances in the ITER-relevant DIII-D ECCD gyrotron launch mirror control system hardware and real-time plasma control system have been made [7] and there are plans for application in DIII-D ITER demonstration discharges.« less

A fresh look at electron cyclotron current drive power requirements for stabilization of tearing modes in ITER

NASA Astrophysics Data System (ADS)

La Haye, R. J.

2015-12-01

ITER is an international project to design and build an experimental fusion reactor based on the "tokamak" concept. ITER relies upon localized electron cyclotron current drive (ECCD) at the rational safety factor q=2 to suppress or stabilize the expected poloidal mode m=2, toroidal mode n=1 neoclassical tearing mode (NTM) islands. Such islands if unmitigated degrade energy confinement, lock to the resistive wall (stop rotating), cause loss of "H-mode" and induce disruption. The International Tokamak Physics Activity (ITPA) on MHD, Disruptions and Magnetic Control joint experiment group MDC-8 on Current Drive Prevention/Stabilization of Neoclassical Tearing Modes started in 2005, after which assessments were made for the requirements for ECCD needed in ITER, particularly that of rf power and alignment on q=2 [1]. Narrow well-aligned rf current parallel to and of order of one percent of the total plasma current is needed to replace the "missing" current in the island O-points and heal or preempt (avoid destabilization by applying ECCD on q=2 in absence of the mode) the island [2-4]. This paper updates the advances in ECCD stabilization on NTMs learned in DIII-D experiments and modeling during the last 5 to 10 years as applies to stabilization by localized ECCD of tearing modes in ITER. This includes the ECCD (inside the q=1 radius) stabilization of the NTM "seeding" instability known as sawteeth (m/n=1/1) [5]. Recent measurements in DIII-D show that the ITER-similar current profile is classically unstable, curvature stabilization must not be neglected, and the small island width stabilization effect from helical ion polarization currents is stronger than was previously thought [6]. The consequences of updated assumptions in ITER modeling of the minimum well-aligned ECCD power needed are all-in-all favorable (and well-within the ITER 24 gyrotron capability) when all effects are included. However, a "wild card" may be broadening of the localized ECCD by the presence of the island; various theories predict broadening could occur and there is experimental evidence for broadening in DIII-D. Wider than now expected ECCD in ITER would make alignment easier to do but weaken the stabilization and thus require more rf power. In addition to updated modeling for ITER, advances in the ITER-relevant DIII-D ECCD gyrotron launch mirror control system hardware and real-time plasma control system have been made [7] and there are plans for application in DIII-D ITER demonstration discharges.

Un algorithme efficace d'intégration plastique pour un matériau obéissant au critère anisotrope de Hill

NASA Astrophysics Data System (ADS)

Titeux, Isabelle; Li, Yuming M.; Debray, Karl; Guo, Ying-Qiao

2004-11-01

This Note deals with an efficient algorithm to carry out the plastic integration and compute the stresses due to large strains for materials satisfying the Hill's anisotropic yield criterion. The classical algorithm of plastic integration such as 'Return Mapping Method' is largely used for nonlinear analyses of structures and numerical simulations of forming processes, but it requires an iterative schema and may have convergence problems. A new direct algorithm based on a scalar method is developed which allows us to directly obtain the plastic multiplier without an iteration procedure; thus the computation time is largely reduced and the numerical problems are avoided. To cite this article: I. Titeux et al., C. R. Mecanique 332 (2004).

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

PubMed Central

Wang, Kun; Su, Richard; Oraevsky, Alexander A; Anastasio, Mark A

2012-01-01

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications. PMID:22864062

Slaying the Great Green Dragon: Learning and Modelling Iterable Ordered Optional Adjuncts

ERIC Educational Resources Information Center

Fowlie, Meaghan

2017-01-01

Adjuncts and arguments exhibit different syntactic behaviours, but modelling this difference in minimalist syntax is challenging: on the one hand, adjuncts differ from arguments in that they are optional, transparent, and iterable, but on the other hand they are often strictly ordered, reflecting the kind of strict selection seen in argument…

Reliable recovery of the optical properties of multi-layer turbid media by iteratively using a layered diffusion model at multiple source-detector separations

PubMed Central

Liao, Yu-Kai; Tseng, Sheng-Hao

2014-01-01

Accurately determining the optical properties of multi-layer turbid media using a layered diffusion model is often a difficult task and could be an ill-posed problem. In this study, an iterative algorithm was proposed for solving such problems. This algorithm employed a layered diffusion model to calculate the optical properties of a layered sample at several source-detector separations (SDSs). The optical properties determined at various SDSs were mutually referenced to complete one round of iteration and the optical properties were gradually revised in further iterations until a set of stable optical properties was obtained. We evaluated the performance of the proposed method using frequency domain Monte Carlo simulations and found that the method could robustly recover the layered sample properties with various layer thickness and optical property settings. It is expected that this algorithm can work with photon transport models in frequency and time domain for various applications, such as determination of subcutaneous fat or muscle optical properties and monitoring the hemodynamics of muscle. PMID:24688828

Estimating pole/zero errors in GSN-IRIS/USGS network calibration metadata

USGS Publications Warehouse

Ringler, A.T.; Hutt, C.R.; Aster, R.; Bolton, H.; Gee, L.S.; Storm, T.

2012-01-01

Mapping the digital record of a seismograph into true ground motion requires the correction of the data by some description of the instrument's response. For the Global Seismographic Network (Butler et al., 2004), as well as many other networks, this instrument response is represented as a Laplace domain pole–zero model and published in the Standard for the Exchange of Earthquake Data (SEED) format. This Laplace representation assumes that the seismometer behaves as a linear system, with any abrupt changes described adequately via multiple time-invariant epochs. The SEED format allows for published instrument response errors as well, but these typically have not been estimated or provided to users. We present an iterative three-step method to estimate the instrument response parameters (poles and zeros) and their associated errors using random calibration signals. First, we solve a coarse nonlinear inverse problem using a least-squares grid search to yield a first approximation to the solution. This approach reduces the likelihood of poorly estimated parameters (a local-minimum solution) caused by noise in the calibration records and enhances algorithm convergence. Second, we iteratively solve a nonlinear parameter estimation problem to obtain the least-squares best-fit Laplace pole–zero–gain model. Third, by applying the central limit theorem, we estimate the errors in this pole–zero model by solving the inverse problem at each frequency in a two-thirds octave band centered at each best-fit pole–zero frequency. This procedure yields error estimates of the 99% confidence interval. We demonstrate the method by applying it to a number of recent Incorporated Research Institutions in Seismology/United States Geological Survey (IRIS/USGS) network calibrations (network code IU).

Too Little Too Soon? Modeling the Risks of Spiral Development

DTIC Science & Technology

2007-04-30

270 315 360 405 450 495 540 585 630 675 720 765 810 855 900 Time (Week) Work started and active PhIt [Requirements,Iter1] : JavelinCalibration work...packages1 1 1 Work started and active PhIt [Technology,Iter1] : JavelinCalibration work packages2 2 2 Work started and active PhIt [Design,Iter1...JavelinCalibration work packages3 3 3 3 Work started and active PhIt [Manufacturing,Iter1] : JavelinCalibration work packages4 4 Work started and active PhIt

Quantum learning of classical stochastic processes: The completely positive realization problem

NASA Astrophysics Data System (ADS)

Monràs, Alex; Winter, Andreas

2016-01-01

Among several tasks in Machine Learning, a specially important one is the problem of inferring the latent variables of a system and their causal relations with the observed behavior. A paradigmatic instance of this is the task of inferring the hidden Markov model underlying a given stochastic process. This is known as the positive realization problem (PRP), [L. Benvenuti and L. Farina, IEEE Trans. Autom. Control 49(5), 651-664 (2004)] and constitutes a central problem in machine learning. The PRP and its solutions have far-reaching consequences in many areas of systems and control theory, and is nowadays an important piece in the broad field of positive systems theory. We consider the scenario where the latent variables are quantum (i.e., quantum states of a finite-dimensional system) and the system dynamics is constrained only by physical transformations on the quantum system. The observable dynamics is then described by a quantum instrument, and the task is to determine which quantum instrument — if any — yields the process at hand by iterative application. We take as a starting point the theory of quasi-realizations, whence a description of the dynamics of the process is given in terms of linear maps on state vectors and probabilities are given by linear functionals on the state vectors. This description, despite its remarkable resemblance with the hidden Markov model, or the iterated quantum instrument, is however devoid of any stochastic or quantum mechanical interpretation, as said maps fail to satisfy any positivity conditions. The completely positive realization problem then consists in determining whether an equivalent quantum mechanical description of the same process exists. We generalize some key results of stochastic realization theory, and show that the problem has deep connections with operator systems theory, giving possible insight to the lifting problem in quotient operator systems. Our results have potential applications in quantum machine learning, device-independent characterization and reverse-engineering of stochastic processes and quantum processors, and more generally, of dynamical processes with quantum memory [M. Guţă, Phys. Rev. A 83(6), 062324 (2011); M. Guţă and N. Yamamoto, e-print arXiv:1303.3771(2013)].

High resolution x-ray CMT: Reconstruction methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, J.K.

This paper qualitatively discusses the primary characteristics of methods for reconstructing tomographic images from a set of projections. These reconstruction methods can be categorized as either {open_quotes}analytic{close_quotes} or {open_quotes}iterative{close_quotes} techniques. Analytic algorithms are derived from the formal inversion of equations describing the imaging process, while iterative algorithms incorporate a model of the imaging process and provide a mechanism to iteratively improve image estimates. Analytic reconstruction algorithms are typically computationally more efficient than iterative methods; however, analytic algorithms are available for a relatively limited set of imaging geometries and situations. Thus, the framework of iterative reconstruction methods is better suited formore » high accuracy, tomographic reconstruction codes.« less

Will it Blend? Visualization and Accuracy Evaluation of High-Resolution Fuzzy Vegetation Maps

NASA Astrophysics Data System (ADS)

Zlinszky, A.; Kania, A.

2016-06-01

Instead of assigning every map pixel to a single class, fuzzy classification includes information on the class assigned to each pixel but also the certainty of this class and the alternative possible classes based on fuzzy set theory. The advantages of fuzzy classification for vegetation mapping are well recognized, but the accuracy and uncertainty of fuzzy maps cannot be directly quantified with indices developed for hard-boundary categorizations. The rich information in such a map is impossible to convey with a single map product or accuracy figure. Here we introduce a suite of evaluation indices and visualization products for fuzzy maps generated with ensemble classifiers. We also propose a way of evaluating classwise prediction certainty with "dominance profiles" visualizing the number of pixels in bins according to the probability of the dominant class, also showing the probability of all the other classes. Together, these data products allow a quantitative understanding of the rich information in a fuzzy raster map both for individual classes and in terms of variability in space, and also establish the connection between spatially explicit class certainty and traditional accuracy metrics. These map products are directly comparable to widely used hard boundary evaluation procedures, support active learning-based iterative classification and can be applied for operational use.

Attenuation-emission alignment in cardiac PET∕CT based on consistency conditions

PubMed Central

Alessio, Adam M.; Kinahan, Paul E.; Champley, Kyle M.; Caldwell, James H.

2010-01-01

Purpose: In cardiac PET and PET∕CT imaging, misaligned transmission and emission images are a common problem due to respiratory and cardiac motion. This misalignment leads to erroneous attenuation correction and can cause errors in perfusion mapping and quantification. This study develops and tests a method for automated alignment of attenuation and emission data. Methods: The CT-based attenuation map is iteratively transformed until the attenuation corrected emission data minimize an objective function based on the Radon consistency conditions. The alignment process is derived from previous work by Welch et al. [“Attenuation correction in PET using consistency information,” IEEE Trans. Nucl. Sci. 45, 3134–3141 (1998)] for stand-alone PET imaging. The process was evaluated with the simulated data and measured patient data from multiple cardiac ammonia PET∕CT exams. The alignment procedure was applied to simulations of five different noise levels with three different initial attenuation maps. For the measured patient data, the alignment procedure was applied to eight attenuation-emission combinations with initially acceptable alignment and eight combinations with unacceptable alignment. The initially acceptable alignment studies were forced out of alignment a known amount and quantitatively evaluated for alignment and perfusion accuracy. The initially unacceptable studies were compared to the proposed aligned images in a blinded side-by-side review. Results: The proposed automatic alignment procedure reduced errors in the simulated data and iteratively approaches global minimum solutions with the patient data. In simulations, the alignment procedure reduced the root mean square error to less than 5 mm and reduces the axial translation error to less than 1 mm. In patient studies, the procedure reduced the translation error by >50% and resolved perfusion artifacts after a known misalignment for the eight initially acceptable patient combinations. The side-by-side review of the proposed aligned attenuation-emission maps and initially misaligned attenuation-emission maps revealed that reviewers preferred the proposed aligned maps in all cases, except one inconclusive case. Conclusions: The proposed alignment procedure offers an automatic method to reduce attenuation correction artifacts in cardiac PET∕CT and provides a viable supplement to subjective manual realignment tools. PMID:20384256

M-estimator for the 3D symmetric Helmert coordinate transformation

NASA Astrophysics Data System (ADS)

Chang, Guobin; Xu, Tianhe; Wang, Qianxin

2018-01-01

The M-estimator for the 3D symmetric Helmert coordinate transformation problem is developed. Small-angle rotation assumption is abandoned. The direction cosine matrix or the quaternion is used to represent the rotation. The 3 × 1 multiplicative error vector is defined to represent the rotation estimation error. An analytical solution can be employed to provide the initial approximate for iteration, if the outliers are not large. The iteration is carried out using the iterative reweighted least-squares scheme. In each iteration after the first one, the measurement equation is linearized using the available parameter estimates, the reweighting matrix is constructed using the residuals obtained in the previous iteration, and then the parameter estimates with their variance-covariance matrix are calculated. The influence functions of a single pseudo-measurement on the least-squares estimator and on the M-estimator are derived to theoretically show the robustness. In the solution process, the parameter is rescaled in order to improve the numerical stability. Monte Carlo experiments are conducted to check the developed method. Different cases to investigate whether the assumed stochastic model is correct are considered. The results with the simulated data slightly deviating from the true model are used to show the developed method's statistical efficacy at the assumed stochastic model, its robustness against the deviations from the assumed stochastic model, and the validity of the estimated variance-covariance matrix no matter whether the assumed stochastic model is correct or not.

Iterative method of construction of a bifurcation diagram of autorotation motions for a system with one degree of freedom

NASA Astrophysics Data System (ADS)

Klimina, L. A.

2018-05-01

The modification of the Picard approach is suggested that is targeted to the construction of a bifurcation diagram of 2π -periodic motions of mechanical system with a cylindrical phase space. Each iterative step is based on principles of averaging and energy balance similar to the Poincare-Pontryagin approach. If the iterative procedure converges, it provides the periodic trajectory of the system depending on the bifurcation parameter of the model. The method is applied to describe self-sustained rotations in the model of an aerodynamic pendulum.

Noise models for low counting rate coherent diffraction imaging.

PubMed

Godard, Pierre; Allain, Marc; Chamard, Virginie; Rodenburg, John

2012-11-05

Coherent diffraction imaging (CDI) is a lens-less microscopy method that extracts the complex-valued exit field from intensity measurements alone. It is of particular importance for microscopy imaging with diffraction set-ups where high quality lenses are not available. The inversion scheme allowing the phase retrieval is based on the use of an iterative algorithm. In this work, we address the question of the choice of the iterative process in the case of data corrupted by photon or electron shot noise. Several noise models are presented and further used within two inversion strategies, the ordered subset and the scaled gradient. Based on analytical and numerical analysis together with Monte-Carlo studies, we show that any physical interpretations drawn from a CDI iterative technique require a detailed understanding of the relationship between the noise model and the used inversion method. We observe that iterative algorithms often assume implicitly a noise model. For low counting rates, each noise model behaves differently. Moreover, the used optimization strategy introduces its own artefacts. Based on this analysis, we develop a hybrid strategy which works efficiently in the absence of an informed initial guess. Our work emphasises issues which should be considered carefully when inverting experimental data.

Non-iterative distance constraints enforcement for cloth drapes simulation

NASA Astrophysics Data System (ADS)

Hidajat, R. L. L. G.; Wibowo, Arifin, Z.; Suyitno

2016-03-01

A cloth simulation represents the behavior of cloth objects such as flag, tablecloth, or even garments has application in clothing animation for games and virtual shops. Elastically deformable models have widely used to provide realistic and efficient simulation, however problem of overstretching is encountered. We introduce a new cloth simulation algorithm that replaces iterative distance constraint enforcement steps with non-iterative ones for preventing over stretching in a spring-mass system for cloth modeling. Our method is based on a simple position correction procedure applied at one end of a spring. In our experiments, we developed a rectangle cloth model which is initially at a horizontal position with one point is fixed, and it is allowed to drape by its own weight. Our simulation is able to achieve a plausible cloth drapes as in reality. This paper aims to demonstrate the reliability of our approach to overcome overstretches while decreasing the computational cost of the constraint enforcement process due to an iterative procedure that is eliminated.

Iterative Importance Sampling Algorithms for Parameter Estimation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grout, Ray W; Morzfeld, Matthias; Day, Marcus S.

In parameter estimation problems one computes a posterior distribution over uncertain parameters defined jointly by a prior distribution, a model, and noisy data. Markov chain Monte Carlo (MCMC) is often used for the numerical solution of such problems. An alternative to MCMC is importance sampling, which can exhibit near perfect scaling with the number of cores on high performance computing systems because samples are drawn independently. However, finding a suitable proposal distribution is a challenging task. Several sampling algorithms have been proposed over the past years that take an iterative approach to constructing a proposal distribution. We investigate the applicabilitymore » of such algorithms by applying them to two realistic and challenging test problems, one in subsurface flow, and one in combustion modeling. More specifically, we implement importance sampling algorithms that iterate over the mean and covariance matrix of Gaussian or multivariate t-proposal distributions. Our implementation leverages massively parallel computers, and we present strategies to initialize the iterations using 'coarse' MCMC runs or Gaussian mixture models.« less

A fluid modeling perspective on the tokamak power scrape-off width using SOLPS-ITER

NASA Astrophysics Data System (ADS)

Meier, Eric

2016-10-01

SOLPS-ITER, a 2D fluid code, is used to conduct the first fluid modeling study of the physics behind the power scrape-off width (λq). When drift physics are activated in the code, λq is insensitive to changes in toroidal magnetic field (Bt), as predicted by the 0D heuristic drift (HD) model developed by Goldston. Using the HD model, which quantitatively agrees with regression analysis of a multi-tokamak database, λq in ITER is projected to be 1 mm instead of the previously assumed 4 mm, magnifying the challenge of maintaining the peak divertor target heat flux below the technological limit. These simulations, which use DIII-D H-mode experimental conditions as input, and reproduce the observed high-recycling, attached outer target plasma, allow insights into the scrape-off layer (SOL) physics that set λq. Independence of λq with respect to Bt suggests that SOLPS-ITER captures basic HD physics: the effect of Bt on the particle dwell time ( Bt) cancels with the effect on drift speed ( 1 /Bt), fixing the SOL plasma density width, and dictating λq. Scaling with plasma current (Ip), however, is much weaker than the roughly 1 /Ip dependence predicted by the HD model. Simulated net cross-separatrix particle flux due to magnetic drifts exceeds the anomalous particle transport, and a Pfirsch-Schluter-like SOL flow pattern is established. Up-down ion pressure asymmetry enables the net magnetic drift flux. Drifts establish in-out temperature asymmetry, and an associated thermoelectric current carries significant heat flux to the outer target. The density fall-off length in the SOL is similar to the electron temperature fall-off length, as observed experimentally. Finally, opportunities and challenges foreseen in ongoing work to extrapolate SOLPS-ITER and the HD model to ITER and future machines will be discussed. Supported by U.S. Department of Energy Contract DESC0010434.

Development of an iterative reconstruction method to overcome 2D detector low resolution limitations in MLC leaf position error detection for 3D dose verification in IMRT.

PubMed

Visser, R; Godart, J; Wauben, D J L; Langendijk, J A; Van't Veld, A A; Korevaar, E W

2016-05-21

The objective of this study was to introduce a new iterative method to reconstruct multi leaf collimator (MLC) positions based on low resolution ionization detector array measurements and to evaluate its error detection performance. The iterative reconstruction method consists of a fluence model, a detector model and an optimizer. Expected detector response was calculated using a radiotherapy treatment plan in combination with the fluence model and detector model. MLC leaf positions were reconstructed by minimizing differences between expected and measured detector response. The iterative reconstruction method was evaluated for an Elekta SLi with 10.0 mm MLC leafs in combination with the COMPASS system and the MatriXX Evolution (IBA Dosimetry) detector with a spacing of 7.62 mm. The detector was positioned in such a way that each leaf pair of the MLC was aligned with one row of ionization chambers. Known leaf displacements were introduced in various field geometries ranging from  -10.0 mm to 10.0 mm. Error detection performance was tested for MLC leaf position dependency relative to the detector position, gantry angle dependency, monitor unit dependency, and for ten clinical intensity modulated radiotherapy (IMRT) treatment beams. For one clinical head and neck IMRT treatment beam, influence of the iterative reconstruction method on existing 3D dose reconstruction artifacts was evaluated. The described iterative reconstruction method was capable of individual MLC leaf position reconstruction with millimeter accuracy, independent of the relative detector position within the range of clinically applied MU's for IMRT. Dose reconstruction artifacts in a clinical IMRT treatment beam were considerably reduced as compared to the current dose verification procedure. The iterative reconstruction method allows high accuracy 3D dose verification by including actual MLC leaf positions reconstructed from low resolution 2D measurements.

Macromolecular Calculations for the XTAL-System of Crystallographic Programs

DTIC Science & Technology

1989-06-01

INSTRUMENT DE NTiFiCAT C 1.1BE R ORG!A%,ZAT:ON1 (if applicable) Office of Naval Research ONR N00014-88-K-0323 8c A:):)R -S ( Citr . Sta te, and ZIP Code) 10...of prio, difference, and updated maps, in addition to the usual BDF handling, is simple but a fruitful source of confusion. For the usual iterative

DECONVOLUTION OF IMAGES FROM BLAST 2005: INSIGHT INTO THE K3-50 AND IC 5146 STAR-FORMING REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roy, Arabindo; Netterfield, Calvin B.; Ade, Peter A. R.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed itsmore » performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and {sup 12}CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below {approx} 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.« less

Deconvolution of Images from BLAST 2005: Insight into the K3-50 and IC 5146 Star-forming Regions

NASA Astrophysics Data System (ADS)

Roy, Arabindo; Ade, Peter A. R.; Bock, James J.; Brunt, Christopher M.; Chapin, Edward L.; Devlin, Mark J.; Dicker, Simon R.; France, Kevin; Gibb, Andrew G.; Griffin, Matthew; Gundersen, Joshua O.; Halpern, Mark; Hargrave, Peter C.; Hughes, David H.; Klein, Jeff; Marsden, Gaelen; Martin, Peter G.; Mauskopf, Philip; Netterfield, Calvin B.; Olmi, Luca; Patanchon, Guillaume; Rex, Marie; Scott, Douglas; Semisch, Christopher; Truch, Matthew D. P.; Tucker, Carole; Tucker, Gregory S.; Viero, Marco P.; Wiebe, Donald V.

2011-04-01

We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4farcm5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and 12CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting SEDs to multi-wavelength data. All of these compact sources are still quite cold (typical temperature below ~ 16 K) and are above the critical Bonner-Ebert mass. They have associated low-power young stellar objects. Further evidence for starless clumps has also been found in the IC 5146 region.

Calibration and Data Analysis of the MC-130 Air Balance

NASA Technical Reports Server (NTRS)

Booth, Dennis; Ulbrich, N.

2012-01-01

Design, calibration, calibration analysis, and intended use of the MC-130 air balance are discussed. The MC-130 balance is an 8.0 inch diameter force balance that has two separate internal air flow systems and one external bellows system. The manual calibration of the balance consisted of a total of 1854 data points with both unpressurized and pressurized air flowing through the balance. A subset of 1160 data points was chosen for the calibration data analysis. The regression analysis of the subset was performed using two fundamentally different analysis approaches. First, the data analysis was performed using a recently developed extension of the Iterative Method. This approach fits gage outputs as a function of both applied balance loads and bellows pressures while still allowing the application of the iteration scheme that is used with the Iterative Method. Then, for comparison, the axial force was also analyzed using the Non-Iterative Method. This alternate approach directly fits loads as a function of measured gage outputs and bellows pressures and does not require a load iteration. The regression models used by both the extended Iterative and Non-Iterative Method were constructed such that they met a set of widely accepted statistical quality requirements. These requirements lead to reliable regression models and prevent overfitting of data because they ensure that no hidden near-linear dependencies between regression model terms exist and that only statistically significant terms are included. Finally, a comparison of the axial force residuals was performed. Overall, axial force estimates obtained from both methods show excellent agreement as the differences of the standard deviation of the axial force residuals are on the order of 0.001 % of the axial force capacity.

Solving large test-day models by iteration on data and preconditioned conjugate gradient.

PubMed

Lidauer, M; Strandén, I; Mäntysaari, E A; Pösö, J; Kettunen, A

1999-12-01

A preconditioned conjugate gradient method was implemented into an iteration on a program for data estimation of breeding values, and its convergence characteristics were studied. An algorithm was used as a reference in which one fixed effect was solved by Gauss-Seidel method, and other effects were solved by a second-order Jacobi method. Implementation of the preconditioned conjugate gradient required storing four vectors (size equal to number of unknowns in the mixed model equations) in random access memory and reading the data at each round of iteration. The preconditioner comprised diagonal blocks of the coefficient matrix. Comparison of algorithms was based on solutions of mixed model equations obtained by a single-trait animal model and a single-trait, random regression test-day model. Data sets for both models used milk yield records of primiparous Finnish dairy cows. Animal model data comprised 665,629 lactation milk yields and random regression test-day model data of 6,732,765 test-day milk yields. Both models included pedigree information of 1,099,622 animals. The animal model ¿random regression test-day model¿ required 122 ¿305¿ rounds of iteration to converge with the reference algorithm, but only 88 ¿149¿ were required with the preconditioned conjugate gradient. To solve the random regression test-day model with the preconditioned conjugate gradient required 237 megabytes of random access memory and took 14% of the computation time needed by the reference algorithm.

An implicit-iterative solution of the heat conduction equation with a radiation boundary condition

NASA Technical Reports Server (NTRS)

Williams, S. D.; Curry, D. M.

1977-01-01

For the problem of predicting one-dimensional heat transfer between conducting and radiating mediums by an implicit finite difference method, four different formulations were used to approximate the surface radiation boundary condition while retaining an implicit formulation for the interior temperature nodes. These formulations are an explicit boundary condition, a linearized boundary condition, an iterative boundary condition, and a semi-iterative boundary method. The results of these methods in predicting surface temperature on the space shuttle orbiter thermal protection system model under a variety of heating rates were compared. The iterative technique caused the surface temperature to be bounded at each step. While the linearized and explicit methods were generally more efficient, the iterative and semi-iterative techniques provided a realistic surface temperature response without requiring step size control techniques.

On the solution of evolution equations based on multigrid and explicit iterative methods

NASA Astrophysics Data System (ADS)

Zhukov, V. T.; Novikova, N. D.; Feodoritova, O. B.

2015-08-01

Two schemes for solving initial-boundary value problems for three-dimensional parabolic equations are studied. One is implicit and is solved using the multigrid method, while the other is explicit iterative and is based on optimal properties of the Chebyshev polynomials. In the explicit iterative scheme, the number of iteration steps and the iteration parameters are chosen as based on the approximation and stability conditions, rather than on the optimization of iteration convergence to the solution of the implicit scheme. The features of the multigrid scheme include the implementation of the intergrid transfer operators for the case of discontinuous coefficients in the equation and the adaptation of the smoothing procedure to the spectrum of the difference operators. The results produced by these schemes as applied to model problems with anisotropic discontinuous coefficients are compared.

Modeling defect trends for iterative development

NASA Technical Reports Server (NTRS)

Powell, J. D.; Spanguolo, J. N.

2003-01-01

The Employment of Defects (EoD) approach to measuring and analyzing defects seeks to identify and capture trends and phenomena that are critical to managing software quality in the iterative software development lifecycle at JPL.

Flood inundation mapping in the Logone floodplain from multi temporal Landsat ETM+ imagery

NASA Astrophysics Data System (ADS)

Jung, H.; Alsdorf, D. E.; Moritz, M.; Lee, H.; Vassolo, S.

2011-12-01

Yearly flooding in the Logone floodplain makes an impact on agricultural, pastoral, and fishery systems in the Lake Chad Basin. Since the flooding extent and depth are highly variable, flood inundation mapping helps us make better use of water resources and prevent flood hazards in the Logone floodplain. The flood maps are generated from 33 multi temporal Landsat Enhanced Thematic Mapper Plus (ETM+) during three years 2006 to 2008. Flooded area is classified using a short-wave infrared band whereas open water is classified by Iterative Self-organizing Data Analysis (ISODATA) clustering. The maximum flooding extent in the study area increases up to ~5.8K km2 in late October 2008. The study also provides strong correlation of the flooding extents with water height variations in both the floodplain and the river based on a second polynomial regression model. The water heights are from ENIVSAT altimetry in the floodplain and gauge measurements in the river. Coefficients of determination between flooding extents and water height variations are greater than 0.91 with 4 to 36 days in phase lag. Floodwater drains back to the river and to the northeast during the recession period in December and January. The study supports understanding of the Logone floodplain dynamics in detail of spatial pattern and size of the flooding extent and assists the flood monitoring and prediction systems in the catchment.

Flood Inundation Mapping in the Logone Floodplain from Multi Temporal Landsat ETM+Imagery

NASA Technical Reports Server (NTRS)

Jung, Hahn Chul; Alsdorf, Douglas E.; Moritz, Mark; Lee, Hyongki; Vassolo, Sara

2011-01-01

Yearly flooding in the Logone floodplain makes an impact on agricultural, pastoral, and fishery systems in the Lake Chad Basin. Since the flooding extent and depth are highly variable, flood inundation mapping helps us make better use of water resources and prevent flood hazards in the Logone floodplain. The flood maps are generated from 33 multi temporal Landsat Enhanced Thematic Mapper Plus (ETM+) during three years 2006 to 2008. Flooded area is classified using a short-wave infrared band whereas open water is classified by Iterative Self-organizing Data Analysis (ISODATA) clustering. The maximum flooding extent in the study area increases up to approximately 5.8K km2 in late October 2008. The study also provides strong correlation of the flooding extents with water height variations in both the floodplain and the river based on a second polynomial regression model. The water heights are from ENIVSAT altimetry in the floodplain and gauge measurements in the river. Coefficients of determination between flooding extents and water height variations are greater than 0.91 with 4 to 36 days in phase lag. Floodwater drains back to the river and to the northeast during the recession period in December and January. The study supports understanding of the Logone floodplain dynamics in detail of spatial pattern and size of the flooding extent and assists the flood monitoring and prediction systems in the catchment.

Artificial neural systems for interpretation and inversion of seismic data

NASA Astrophysics Data System (ADS)

Calderon-Macias, Carlos

The goal of this work is to investigate the feasibility of using neural network (NN) models for solving geophysical exploration problems. First, a feedforward neural network (FNN) is used to solve inverse problems. The operational characteristics of a FNN are primarily controlled by a set of weights and a nonlinear function that performs a mapping between two sets of data. In a process known as training, the FNN weights are iteratively adjusted to perform the mapping. After training, the computed weights encode important features of the data that enable one pattern to be distinguished from another. Synthetic data computed from an ensemble of earth models and the corresponding models provide the training data. Two training methods are studied: the backpropagation method which is a gradient scheme, and a global optimization method called very fast simulated annealing (VFSA). A trained network is then used to predict models from new data (e.g., data from a new location) in a one-step procedure. The application of this method to the problems of obtaining formation resistivities and layer thicknesses from resistivity sounding data and 1D velocity models from seismic data shows that trained FNNs produce reasonably accurate earth models when observed data are input to the FNNs. In a second application, a FNN is used for automating the NMO correction process of seismic reflection data. The task of the FNN is to map CMP data at control locations along a seismic line into subsurface velocities. The network is trained while the velocity analyses are performed at the control locations. Once trained, the computed weights are used as an operator that acts on the remaining CMP data as a velocity interpolator, resulting in a fast method for NMO correction. The second part of this dissertation describes the application of a Hopfield neural network (HNN) to the problems of deconvolution and multiple attenuation. In these applications, the unknown parameters (reflection coefficients and source wavelet in the first problem and an operator in the second) are mapped as neurons of the HNN. The proposed deconvolution method attempts to reproduce the data with a limited number of events. The multiple attenuation method resembles the predictive deconvolution method. Results of this method are compared with a multiple elimination method based on estimating the source wavelet from the seismic data.

Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

PubMed

Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P < 0.05). Adaptive statistical iterative reconstruction-V 90% showed superior LCD and had the highest CNR in the liver, aorta, and, pancreas, measuring 7.32 ± 3.22, 11.60 ± 4.25, and 4.60 ± 2.31, respectively, compared with the next best series of ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P <0.0001). Veo 3.0 and ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

SU-E-T-446: Group-Sparsity Based Angle Generation Method for Beam Angle Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, H

2015-06-15

Purpose: This work is to develop the effective algorithm for beam angle optimization (BAO), with the emphasis on enabling further improvement from existing treatment-dependent templates based on clinical knowledge and experience. Methods: The proposed BAO algorithm utilizes a priori beam angle templates as the initial guess, and iteratively generates angular updates for this initial set, namely angle generation method, with improved dose conformality that is quantitatively measured by the objective function. That is, during each iteration, we select “the test angle” in the initial set, and use group-sparsity based fluence map optimization to identify “the candidate angle” for updating “themore » test angle”, for which all the angles in the initial set except “the test angle”, namely “the fixed set”, are set free, i.e., with no group-sparsity penalty, and the rest of angles including “the test angle” during this iteration are in “the working set”. And then “the candidate angle” is selected with the smallest objective function value from the angles in “the working set” with locally maximal group sparsity, and replaces “the test angle” if “the fixed set” with “the candidate angle” has a smaller objective function value by solving the standard fluence map optimization (with no group-sparsity regularization). Similarly other angles in the initial set are in turn selected as “the test angle” for angular updates and this chain of updates is iterated until no further new angular update is identified for a full loop. Results: The tests using the MGH public prostate dataset demonstrated the effectiveness of the proposed BAO algorithm. For example, the optimized angular set from the proposed BAO algorithm was better the MGH template. Conclusion: A new BAO algorithm is proposed based on the angle generation method via group sparsity, with improved dose conformality from the given template. Hao Gao was partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

An Automatic and Robust Algorithm of Reestablishment of Digital Dental Occlusion

PubMed Central

Chang, Yu-Bing; Xia, James J.; Gateno, Jaime; Xiong, Zixiang; Zhou, Xiaobo; Wong, Stephen T. C.

2017-01-01

In the field of craniomaxillofacial (CMF) surgery, surgical planning can be performed on composite 3-D models that are generated by merging a computerized tomography scan with digital dental models. Digital dental models can be generated by scanning the surfaces of plaster dental models or dental impressions with a high-resolution laser scanner. During the planning process, one of the essential steps is to reestablish the dental occlusion. Unfortunately, this task is time-consuming and often inaccurate. This paper presents a new approach to automatically and efficiently reestablish dental occlusion. It includes two steps. The first step is to initially position the models based on dental curves and a point matching technique. The second step is to reposition the models to the final desired occlusion based on iterative surface-based minimum distance mapping with collision constraints. With linearization of rotation matrix, the alignment is modeled by solving quadratic programming. The simulation was completed on 12 sets of digital dental models. Two sets of dental models were partially edentulous, and another two sets have first premolar extractions for orthodontic treatment. Two validation methods were applied to the articulated models. The results show that using our method, the dental models can be successfully articulated with a small degree of deviations from the occlusion achieved with the gold-standard method. PMID:20529735

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

Assessment of DInSAR Potential in Simulating Geological Subsurface Structure

NASA Astrophysics Data System (ADS)

Fouladi Moghaddam, N.; Rudiger, C.; Samsonov, S. V.; Hall, M.; Walker, J. P.; Camporese, M.

2013-12-01

High resolution geophysical surveys, including seismic, gravity, magnetic, etc., provide valuable information about subsurface structuring but they are very costly and time consuming with non-unique and sometimes conflicting interpretations. Several recent studies have examined the application of DInSAR to estimate surface deformation, monitor possible fault reactivation and constrain reservoir dynamic behaviour in geothermal and groundwater fields. The main focus of these studies was to generate an elevation map, which represents the reservoir extraction induced deformation. This research study, however, will focus on developing methods to simulate subsurface structuring and identify hidden faults/hydraulic barriers using DInSAR surface observations, as an innovative and cost-effective reconnaissance exploration tool for planning of seismic acquisition surveys in geothermal and Carbon Capture and Sequestration regions. By direct integration of various DInSAR datasets with overlapping temporal and spatial coverage we produce multi-temporal ground deformation maps with high resolution and precision to evaluate the potential of a new multidimensional MSBAS technique (Samsonov & d'Oreye, 2012). The technique is based on the Small Baseline Subset Algorithm (SBAS) that is modified to account for variation in sensor parameters. It allows integration of data from sensors with different wave-band, azimuth and incidence angles, different spatial and temporal sampling and resolutions. These deformation maps then will be used as an input for inverse modelling to simulate strain history and shallow depth structure. To achieve the main objective of our research, i.e. developing a method for coupled InSAR and geophysical observations and better understanding of subsurface structuring, comparing DInSAR inverse modelling results with previously provided static structural model will result in iteratively modified DInSAR structural model for adequate match with in situ observations. The newly developed and modified algorithm will then be applied in another part of the region where subsurface information is limited.

Simulation of Fusion Plasmas

ScienceCinema

Holland, Chris [UC San Diego, San Diego, California, United States

2017-12-09

The upcoming ITER experiment (www.iter.org) represents the next major milestone in realizing the promise of using nuclear fusion as a commercial energy source, by moving into the “burning plasma” regime where the dominant heat source is the internal fusion reactions. As part of its support for the ITER mission, the US fusion community is actively developing validated predictive models of the behavior of magnetically confined plasmas. In this talk, I will describe how the plasma community is using the latest high performance computing facilities to develop and refine our models of the nonlinear, multiscale plasma dynamics, and how recent advances in experimental diagnostics are allowing us to directly test and validate these models at an unprecedented level.

Use of wavelet-packet transforms to develop an engineering model for multifractal characterization of mutation dynamics in pathological and nonpathological gene sequences

NASA Astrophysics Data System (ADS)

Walker, David Lee

1999-12-01

This study uses dynamical analysis to examine in a quantitative fashion the information coding mechanism in DNA sequences. This exceeds the simple dichotomy of either modeling the mechanism by comparing DNA sequence walks as Fractal Brownian Motion (fbm) processes. The 2-D mappings of the DNA sequences for this research are from Iterated Function System (IFS) (Also known as the ``Chaos Game Representation'' (CGR)) mappings of the DNA sequences. This technique converts a 1-D sequence into a 2-D representation that preserves subsequence structure and provides a visual representation. The second step of this analysis involves the application of Wavelet Packet Transforms, a recently developed technique from the field of signal processing. A multi-fractal model is built by using wavelet transforms to estimate the Hurst exponent, H. The Hurst exponent is a non-parametric measurement of the dynamism of a system. This procedure is used to evaluate gene- coding events in the DNA sequence of cystic fibrosis mutations. The H exponent is calculated for various mutation sites in this gene. The results of this study indicate the presence of anti-persistent, random walks and persistent ``sub-periods'' in the sequence. This indicates the hypothesis of a multi-fractal model of DNA information encoding warrants further consideration. This work examines the model's behavior in both pathological (mutations) and non-pathological (healthy) base pair sequences of the cystic fibrosis gene. These mutations both natural and synthetic were introduced by computer manipulation of the original base pair text files. The results show that disease severity and system ``information dynamics'' correlate. These results have implications for genetic engineering as well as in mathematical biology. They suggest that there is scope for more multi-fractal models to be developed.

Modeling the dynamics of evaluation: a multilevel neural network implementation of the iterative reprocessing model.

PubMed

Ehret, Phillip J; Monroe, Brian M; Read, Stephen J

2015-05-01

We present a neural network implementation of central components of the iterative reprocessing (IR) model. The IR model argues that the evaluation of social stimuli (attitudes, stereotypes) is the result of the IR of stimuli in a hierarchy of neural systems: The evaluation of social stimuli develops and changes over processing. The network has a multilevel, bidirectional feedback evaluation system that integrates initial perceptual processing and later developing semantic processing. The network processes stimuli (e.g., an individual's appearance) over repeated iterations, with increasingly higher levels of semantic processing over time. As a result, the network's evaluations of stimuli evolve. We discuss the implications of the network for a number of different issues involved in attitudes and social evaluation. The success of the network supports the IR model framework and provides new insights into attitude theory. © 2014 by the Society for Personality and Social Psychology, Inc.

Decentralized control of sound radiation using iterative loop recovery.

PubMed

Schiller, Noah H; Cabell, Randolph H; Fuller, Chris R

2010-10-01

A decentralized model-based control strategy is designed to reduce low-frequency sound radiation from periodically stiffened panels. While decentralized control systems tend to be scalable, performance can be limited due to modeling error introduced by the unmodeled interaction between neighboring control units. Since bounds on modeling error are not known in advance, it is difficult to ensure the decentralized control system will be robust without making the controller overly conservative. Therefore an iterative approach is suggested, which utilizes frequency-shaped loop recovery. The approach accounts for modeling error introduced by neighboring control loops, requires no communication between subsystems, and is relatively simple. The control strategy is evaluated numerically using a model of a stiffened aluminum panel that is representative of the sidewall of an aircraft. Simulations demonstrate that the iterative approach can achieve significant reductions in radiated sound power from the stiffened panel without destabilizing neighboring control units.

Decentralized Control of Sound Radiation Using Iterative Loop Recovery

NASA Technical Reports Server (NTRS)

Schiller, Noah H.; Cabell, Randolph H.; Fuller, Chris R.

2009-01-01

A decentralized model-based control strategy is designed to reduce low-frequency sound radiation from periodically stiffened panels. While decentralized control systems tend to be scalable, performance can be limited due to modeling error introduced by the unmodeled interaction between neighboring control units. Since bounds on modeling error are not known in advance, it is difficult to ensure the decentralized control system will be robust without making the controller overly conservative. Therefore an iterative approach is suggested, which utilizes frequency-shaped loop recovery. The approach accounts for modeling error introduced by neighboring control loops, requires no communication between subsystems, and is relatively simple. The control strategy is evaluated numerically using a model of a stiffened aluminum panel that is representative of the sidewall of an aircraft. Simulations demonstrate that the iterative approach can achieve significant reductions in radiated sound power from the stiffened panel without destabilizing neighboring control units.

Robust and fast-converging level set method for side-scan sonar image segmentation

NASA Astrophysics Data System (ADS)

Liu, Yan; Li, Qingwu; Huo, Guanying

2017-11-01

A robust and fast-converging level set method is proposed for side-scan sonar (SSS) image segmentation. First, the noise in each sonar image is removed using the adaptive nonlinear complex diffusion filter. Second, k-means clustering is used to obtain the initial presegmentation image from the denoised image, and then the distance maps of the initial contours are reinitialized to guarantee the accuracy of the numerical calculation used in the level set evolution. Finally, the satisfactory segmentation is achieved using a robust variational level set model, where the evolution control parameters are generated by the presegmentation. The proposed method is successfully applied to both synthetic image with speckle noise and real SSS images. Experimental results show that the proposed method needs much less iteration and therefore is much faster than the fuzzy local information c-means clustering method, the level set method using a gamma observation model, and the enhanced region-scalable fitting method. Moreover, the proposed method can usually obtain more accurate segmentation results compared with other methods.

Estimation of cylinder orientation in three-dimensional point cloud using angular distance-based optimization

NASA Astrophysics Data System (ADS)

Su, Yun-Ting; Hu, Shuowen; Bethel, James S.

2017-05-01

Light detection and ranging (LIDAR) has become a widely used tool in remote sensing for mapping, surveying, modeling, and a host of other applications. The motivation behind this work is the modeling of piping systems in industrial sites, where cylinders are the most common primitive or shape. We focus on cylinder parameter estimation in three-dimensional point clouds, proposing a mathematical formulation based on angular distance to determine the cylinder orientation. We demonstrate the accuracy and robustness of the technique on synthetically generated cylinder point clouds (where the true axis orientation is known) as well as on real LIDAR data of piping systems. The proposed algorithm is compared with a discrete space Hough transform-based approach as well as a continuous space inlier approach, which iteratively discards outlier points to refine the cylinder parameter estimates. Results show that the proposed method is more computationally efficient than the Hough transform approach and is more accurate than both the Hough transform approach and the inlier method.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

Change Detection of Remote Sensing Images by Dt-Cwt and Mrf

NASA Astrophysics Data System (ADS)

Ouyang, S.; Fan, K.; Wang, H.; Wang, Z.

2017-05-01

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Simulation and Analysis of Launch Teams (SALT)

NASA Technical Reports Server (NTRS)

2008-01-01

A SALT effort was initiated in late 2005 with seed funding from the Office of Safety and Mission Assurance Human Factors organization. Its objectives included demonstrating human behavior and performance modeling and simulation technologies for launch team analysis, training, and evaluation. The goal of the research is to improve future NASA operations and training. The project employed an iterative approach, with the first iteration focusing on the last 70 minutes of a nominal-case Space Shuttle countdown, the second iteration focusing on aborts and launch commit criteria violations, the third iteration focusing on Ares I-X communications, and the fourth iteration focusing on Ares I-X Firing Room configurations. SALT applied new commercial off-the-shelf technologies from industry and the Department of Defense in the spaceport domain.

Full two-dimensional transient solutions of electrothermal aircraft blade deicing

NASA Technical Reports Server (NTRS)

Masiulaniec, K. C.; Keith, T. G., Jr.; Dewitt, K. J.; Leffel, K. L.

1985-01-01

Two finite difference methods are presented for the analysis of transient, two-dimensional responses of an electrothermal de-icer pad of an aircraft wing or blade with attached variable ice layer thickness. Both models employ a Crank-Nicholson iterative scheme, and use an enthalpy formulation to handle the phase change in the ice layer. The first technique makes use of a 'staircase' approach, fitting the irregular ice boundary with square computational cells. The second technique uses a body fitted coordinate transform, and maps the exact shape of the irregular boundary into a rectangular body, with uniformally square computational cells. The numerical solution takes place in the transformed plane. Initial results accounting for variable ice layer thickness are presented. Details of planned de-icing tests at NASA-Lewis, which will provide empirical verification for the above two methods, are also presented.

Modeling Data Containing Outliers using ARIMA Additive Outlier (ARIMA-AO)

NASA Astrophysics Data System (ADS)

Saleh Ahmar, Ansari; Guritno, Suryo; Abdurakhman; Rahman, Abdul; Awi; Alimuddin; Minggi, Ilham; Arif Tiro, M.; Kasim Aidid, M.; Annas, Suwardi; Utami Sutiksno, Dian; Ahmar, Dewi S.; Ahmar, Kurniawan H.; Abqary Ahmar, A.; Zaki, Ahmad; Abdullah, Dahlan; Rahim, Robbi; Nurdiyanto, Heri; Hidayat, Rahmat; Napitupulu, Darmawan; Simarmata, Janner; Kurniasih, Nuning; Andretti Abdillah, Leon; Pranolo, Andri; Haviluddin; Albra, Wahyudin; Arifin, A. Nurani M.

2018-01-01

The aim this study is discussed on the detection and correction of data containing the additive outlier (AO) on the model ARIMA (p, d, q). The process of detection and correction of data using an iterative procedure popularized by Box, Jenkins, and Reinsel (1994). By using this method we obtained an ARIMA models were fit to the data containing AO, this model is added to the original model of ARIMA coefficients obtained from the iteration process using regression methods. In the simulation data is obtained that the data contained AO initial models are ARIMA (2,0,0) with MSE = 36,780, after the detection and correction of data obtained by the iteration of the model ARIMA (2,0,0) with the coefficients obtained from the regression Zt = 0,106+0,204Z t-1+0,401Z t-2-329X 1(t)+115X 2(t)+35,9X 3(t) and MSE = 19,365. This shows that there is an improvement of forecasting error rate data.

Low-temperature tensile strength of the ITER-TF model coil insulation system after reactor irradiation

NASA Astrophysics Data System (ADS)

Bittner-Rohrhofer, K.; Humer, K.; Weber, H. W.

The windings of the superconducting magnet coils for the ITER-FEAT fusion device are affected by high mechanical stresses at cryogenic temperatures and by a radiation environment, which impose certain constraints especially on the insulating materials. A glass fiber reinforced plastic (GFRP) laminate, which consists of Kapton/R-glass-fiber reinforcement tapes, vacuum-impregnated in a DGEBA epoxy system, was used for the European toroidal field model coil turn insulation of ITER. In order to assess its mechanical properties under the actual operating conditions of ITER-FEAT, cryogenic (77 K) static tensile tests and tension-tension fatigue measurements were done before and after irradiation to a fast neutron fluence of 1×10 22 m -2 ( E>0.1 MeV), i.e. the ITER-FEAT design fluence level. We find that the mechanical strength and the fracture behavior of this GFRP are strongly influenced by the winding direction of the tape and by the radiation induced delamination process. In addition, the composite swells by 3%, forming bubbles inside the laminate, and loses weight (1.4%) at the design fluence.

Estimation of urban surface water at subpixel level from neighborhood pixels using multispectral remote sensing image (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xie, Huan; Luo, Xin; Xu, Xiong; Wang, Chen; Pan, Haiyan; Tong, Xiaohua; Liu, Shijie

2016-10-01

Water body is a fundamental element in urban ecosystems and water mapping is critical for urban and landscape planning and management. As remote sensing has increasingly been used for water mapping in rural areas, this spatially explicit approach applied in urban area is also a challenging work due to the water bodies mainly distributed in a small size and the spectral confusion widely exists between water and complex features in the urban environment. Water index is the most common method for water extraction at pixel level, and spectral mixture analysis (SMA) has been widely employed in analyzing urban environment at subpixel level recently. In this paper, we introduce an automatic subpixel water mapping method in urban areas using multispectral remote sensing data. The objectives of this research consist of: (1) developing an automatic land-water mixed pixels extraction technique by water index; (2) deriving the most representative endmembers of water and land by utilizing neighboring water pixels and adaptive iterative optimal neighboring land pixel for respectively; (3) applying a linear unmixing model for subpixel water fraction estimation. Specifically, to automatically extract land-water pixels, the locally weighted scatter plot smoothing is firstly used to the original histogram curve of WI image . And then the Ostu threshold is derived as the start point to select land-water pixels based on histogram of the WI image with the land threshold and water threshold determination through the slopes of histogram curve . Based on the previous process at pixel level, the image is divided into three parts: water pixels, land pixels, and mixed land-water pixels. Then the spectral mixture analysis (SMA) is applied to land-water mixed pixels for water fraction estimation at subpixel level. With the assumption that the endmember signature of a target pixel should be more similar to adjacent pixels due to spatial dependence, the endmember of water and land are determined by neighboring pure land or pure water pixels within a distance. To obtaining the most representative endmembers in SMA, we designed an adaptive iterative endmember selection method based on the spatial similarity of adjacent pixels. According to the spectral similarity in a spatial adjacent region, the spectrum of land endmember is determined by selecting the most representative land pixel in a local window, and the spectrum of water endmember is determined by calculating an average of the water pixels in the local window. The proposed hierarchical processing method based on WI and SMA (WISMA) is applied to urban areas for reliability evaluation using the Landsat-8 Operational Land Imager (OLI) images. For comparison, four methods at pixel level and subpixel level were chosen respectively. Results indicate that the water maps generated by the proposed method correspond as closely with the truth water maps with subpixel precision. And the results showed that the WISMA achieved the best performance in water mapping with comprehensive analysis of different accuracy evaluation indexes (RMSE and SE).

Connecting Projects to Complete the In Situ Resource Utilization Paradigm

NASA Technical Reports Server (NTRS)

Linne, Diane L.; Sanders, Gerald B.

2017-01-01

Terrain Identify specifics such as slope, rockiness, traction parameters Identify what part of ISRU needs each Physical Geotechnical Hardness, density, cohesion, etc. Identify what part of ISRU needs each (e.g., excavation needs to know hardness, density; soil processing needs to know density, cohesion; etc.)Mineral Identify specifics Identify what part of ISRU needs each Volatile Identify specifics Identify what part of ISRU needs each Atmosphere Identify specifics Identify what part of ISRU needs each Environment Identify specifics Identify what part of ISRU needs each Resource Characterization What: Develop an instrument suite to locate and evaluate the physical, mineral, and volatile resources at the lunar poles Neutron Spectrometer Near Infrared (IR) to locate subsurface hydrogen surface water Near IR for mineral identification Auger drill for sample removal down to 1 m Oven with Gas Chromatograph Mass Spectrometer to quantify volatiles present ISRU relevance: Water volatile resource characterization and subsurface material access removal Site Evaluation Resource Mapping What: Develop and utilize new data products and tools for evaluating potential exploration sites for selection and overlay mission data to map terrain, environment, and resource information e.g., New techniques applied to generate Digital Elevation Map (DEMs) at native scale of images (1mpxl)ISRU relevance: Resource mapping and estimation with terrain and environment information is needed for extraction planning Mission Planning and Operations What: Develop and utilize tools and procedures for planning mission operations and real time changes Planning tools include detailed engineering models (e.g., power and data) of surface segment systems allows evaluation of designs ISRU relevance: Allows for iterative engineering as a function of environment and hardware performance.

Exact static solutions for discrete phi4 models free of the Peierls-Nabarro barrier: discretized first-integral approach.

PubMed

Dmitriev, S V; Kevrekidis, P G; Yoshikawa, N; Frantzeskakis, D J

2006-10-01

We propose a generalization of the discrete Klein-Gordon models free of the Peierls-Nabarro barrier derived in Spreight [Nonlinearity 12, 1373 (1999)] and Barashenkov [Phys. Rev. E 72, 035602(R) (2005)], such that they support not only kinks but a one-parameter set of exact static solutions. These solutions can be obtained iteratively from a two-point nonlinear map whose role is played by the discretized first integral of the static Klein-Gordon field, as suggested by Dmitriev [J. Phys. A 38, 7617 (2005)]. We then discuss some discrete phi4 models free of the Peierls-Nabarro barrier and identify for them the full space of available static solutions, including those derived recently by Cooper [Phys. Rev. E 72, 036605 (2005)] but not limited to them. These findings are also relevant to standing wave solutions of discrete nonlinear Schrödinger models. We also study stability of the obtained solutions. As an interesting aside, we derive the list of solutions to the continuum phi4 equation that fill the entire two-dimensional space of parameters obtained as the continuum limit of the corresponding space of the discrete models.

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

Array seismological investigation of the South Atlantic 'Superplume'

NASA Astrophysics Data System (ADS)

Hempel, Stefanie; Gassmöller, Rene; Thomas, Christine

2015-04-01

We apply the axisymmetric, spherical Earth spectral elements code AxiSEM to model seismic compressional waves which sample complex `superplume' structures in the lower mantle. High-resolution array seismological stacking techniques are evaluated regarding their capability to resolve large-scale high-density low-velocity bodies including interior structure such as inner upwellings, high density lenses, ultra-low velocity zones (ULVZs), neighboring remnant slabs and adjacent small-scale uprisings. Synthetic seismograms are also computed and processed for models of the Earth resulting from geodynamic modelling of the South Atlantic mantle including plate reconstruction. We discuss the interference and suppression of the resulting seismic signals and implications for a seismic data study in terms of visibility of the South Atlantic `superplume' structure. This knowledge is used to process, invert and interpret our data set of seismic sources from the Andes and the South Sandwich Islands detected at seismic arrays spanning from Ethiopia over Cameroon to South Africa mapping the South Atlantic `superplume' structure including its interior structure. In order too present the model of the South Atlantic `superplume' structure that best fits the seismic data set, we iteratively compute synthetic seismograms while adjusting the model according to the dependencies found in the parameter study.

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder.

PubMed

Wittenborn, A K; Rahmandad, H; Rick, J; Hosseinichimeh, N

2016-02-01

Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics. We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder. The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression. Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention.

Creation of an ensemble of simulated cardiac cases and a human observer study: tools for the development of numerical observers for SPECT myocardial perfusion imaging

NASA Astrophysics Data System (ADS)

O'Connor, J. Michael; Pretorius, P. Hendrik; Gifford, Howard C.; Licho, Robert; Joffe, Samuel; McGuiness, Matthew; Mehurg, Shannon; Zacharias, Michael; Brankov, Jovan G.

2012-02-01

Our previous Single Photon Emission Computed Tomography (SPECT) myocardial perfusion imaging (MPI) research explored the utility of numerical observers. We recently created two hundred and eighty simulated SPECT cardiac cases using Dynamic MCAT (DMCAT) and SIMIND Monte Carlo tools. All simulated cases were then processed with two reconstruction methods: iterative ordered subset expectation maximization (OSEM) and filtered back-projection (FBP). Observer study sets were assembled for both OSEM and FBP methods. Five physicians performed an observer study on one hundred and seventy-nine images from the simulated cases. The observer task was to indicate detection of any myocardial perfusion defect using the American Society of Nuclear Cardiology (ASNC) 17-segment cardiac model and the ASNC five-scale rating guidelines. Human observer Receiver Operating Characteristic (ROC) studies established the guidelines for the subsequent evaluation of numerical model observer (NO) performance. Several NOs were formulated and their performance was compared with the human observer performance. One type of NO was based on evaluation of a cardiac polar map that had been pre-processed using a gradient-magnitude watershed segmentation algorithm. The second type of NO was also based on analysis of a cardiac polar map but with use of a priori calculated average image derived from an ensemble of normal cases.

Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder

PubMed Central

Wittenborn, A. K.; Rahmandad, H.; Rick, J.; Hosseinichimeh, N.

2016-01-01

Background Depression is a complex public health problem with considerable variation in treatment response. The systemic complexity of depression, or the feedback processes among diverse drivers of the disorder, contribute to the persistence of depression. This paper extends prior attempts to understand the complex causal feedback mechanisms that underlie depression by presenting the first broad boundary causal loop diagram of depression dynamics. Method We applied qualitative system dynamics methods to map the broad feedback mechanisms of depression. We used a structured approach to identify candidate causal mechanisms of depression in the literature. We assessed the strength of empirical support for each mechanism and prioritized those with support from validation studies. Through an iterative process, we synthesized the empirical literature and created a conceptual model of major depressive disorder. Results The literature review and synthesis resulted in the development of the first causal loop diagram of reinforcing feedback processes of depression. It proposes candidate drivers of illness, or inertial factors, and their temporal functioning, as well as the interactions among drivers of depression. The final causal loop diagram defines 13 key reinforcing feedback loops that involve nine candidate drivers of depression. Conclusions Future research is needed to expand upon this initial model of depression dynamics. Quantitative extensions may result in a better understanding of the systemic syndrome of depression and contribute to personalized methods of evaluation, prevention and intervention. PMID:26621339

Iterative atmospheric correction scheme and the polarization color of alpine snow

NASA Astrophysics Data System (ADS)

Ottaviani, Matteo; Cairns, Brian; Ferrare, Rich; Rogers, Raymond

2012-07-01

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories.In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss-Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction.In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft.The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Iterative Atmospheric Correction Scheme and the Polarization Color of Alpine Snow

NASA Technical Reports Server (NTRS)

Ottaviani, Matteo; Cairns, Brian; Ferrare, Rich; Rogers, Raymond

2012-01-01

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories. In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss-Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction. In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft. The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

NASA Astrophysics Data System (ADS)

Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng

2017-05-01

Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.

Thermal Structure and Dynamics of Saturn's Northern Springtime Disturbance

NASA Technical Reports Server (NTRS)

Fletcher, Leigh N.; Hesman, Brigette E.; Irwin, Patrick G.; Baines, Kevin H.; Momary, Thomas W.; SanchezLavega, Agustin; Flasar, F. Michael; Read, Peter L.; Orton, Glenn S.; SimonMiller, Amy;

REMOVING BIASES IN RESOLVED STELLAR MASS MAPS OF GALAXY DISKS THROUGH SUCCESSIVE BAYESIAN MARGINALIZATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martínez-García, Eric E.; González-Lópezlira, Rosa A.; Bruzual A, Gustavo

2017-01-20

Stellar masses of galaxies are frequently obtained by fitting stellar population synthesis models to galaxy photometry or spectra. The state of the art method resolves spatial structures within a galaxy to assess the total stellar mass content. In comparison to unresolved studies, resolved methods yield, on average, higher fractions of stellar mass for galaxies. In this work we improve the current method in order to mitigate a bias related to the resolved spatial distribution derived for the mass. The bias consists in an apparent filamentary mass distribution and a spatial coincidence between mass structures and dust lanes near spiral arms.more » The improved method is based on iterative Bayesian marginalization, through a new algorithm we have named Bayesian Successive Priors (BSP). We have applied BSP to M51 and to a pilot sample of 90 spiral galaxies from the Ohio State University Bright Spiral Galaxy Survey. By quantitatively comparing both methods, we find that the average fraction of stellar mass missed by unresolved studies is only half what previously thought. In contrast with the previous method, the output BSP mass maps bear a better resemblance to near-infrared images.« less

Physics Model-Based Scatter Correction in Multi-Source Interior Computed Tomography.

PubMed

Gong, Hao; Li, Bin; Jia, Xun; Cao, Guohua

2018-02-01

Multi-source interior computed tomography (CT) has a great potential to provide ultra-fast and organ-oriented imaging at low radiation dose. However, X-ray cross scattering from multiple simultaneously activated X-ray imaging chains compromises imaging quality. Previously, we published two hardware-based scatter correction methods for multi-source interior CT. Here, we propose a software-based scatter correction method, with the benefit of no need for hardware modifications. The new method is based on a physics model and an iterative framework. The physics model was derived analytically, and was used to calculate X-ray scattering signals in both forward direction and cross directions in multi-source interior CT. The physics model was integrated to an iterative scatter correction framework to reduce scatter artifacts. The method was applied to phantom data from both Monte Carlo simulations and physical experimentation that were designed to emulate the image acquisition in a multi-source interior CT architecture recently proposed by our team. The proposed scatter correction method reduced scatter artifacts significantly, even with only one iteration. Within a few iterations, the reconstructed images fast converged toward the "scatter-free" reference images. After applying the scatter correction method, the maximum CT number error at the region-of-interests (ROIs) was reduced to 46 HU in numerical phantom dataset and 48 HU in physical phantom dataset respectively, and the contrast-noise-ratio at those ROIs increased by up to 44.3% and up to 19.7%, respectively. The proposed physics model-based iterative scatter correction method could be useful for scatter correction in dual-source or multi-source CT.

Destruction of the Last Good Magnetic Surface in Diii-D Usn with Elms and C-Coils Shot 115467 due to Generalized Asymmetries Using Maps

NASA Astrophysics Data System (ADS)

Herrera, A.; Ali, H.; Punjabi, A.

2004-11-01

The unperturbed magnetic topology of DIII-D USN shot 115467 in the absence of ELMs and C-coils is described by the symmetric simple map (SSM) with the map parameter k=0.2623. For this k, the last good surface passes through x=0 and y=0.9995, q_edge=6.48 if six iterations of the SSM are taken to be equivalent to a single toroidal circuit of DIII-D, and the q_edge equals the q_edge in the DIII-D for shot 115467 [1]. The map parameter k represents the effects of the toroidal asymmetries. We study the changes in the last good surface and its destruction as the map parameter k is increased. This work is supported by NASA SHARP program and DE-FG02-02ER54673. [1] H. Ali, A. Punjabi, A. Boozer, and T. Evans, presented at the 31st European Physical Society Plasma Physics Meeting, London, UK, June 29, 2004, paper P2-172.

Iterative Covariance-based Removal of Time-Synchronous Artifacts: Application to Gastrointestinal Electrical Recordings

PubMed Central

Putney, Joy; Hilbert, Douglas; Paskaranandavadivel, Niranchan; Cheng, Leo K.; O'Grady, Greg; Angeli, Timothy R.

2016-01-01

Objective The aim of this study was to develop, validate, and apply a fully automated method for reducing large temporally synchronous artifacts present in electrical recordings made from the gastrointestinal (GI) serosa, which are problematic for properly assessing slow wave dynamics. Such artifacts routinely arise in experimental and clinical settings from motion, switching behavior of medical instruments, or electrode array manipulation. Methods A novel iterative COvaraiance-Based Reduction of Artifacts (COBRA) algorithm sequentially reduced artifact waveforms using an updating across-channel median as a noise template, scaled and subtracted from each channel based on their covariance. Results Application of COBRA substantially increased the signal-to-artifact ratio (12.8±2.5 dB), while minimally attenuating the energy of the underlying source signal by 7.9% on average (-11.1±3.9 dB). Conclusion COBRA was shown to be highly effective for aiding recovery and accurate marking of slow wave events (sensitivity = 0.90±0.04; positive-predictive value = 0.74±0.08) from large segments of in vivo porcine GI electrical mapping data that would otherwise be lost due to a broad range of contaminating artifact waveforms. Significance Strongly reducing artifacts with COBRA ultimately allowed for rapid production of accurate isochronal activation maps detailing the dynamics of slow wave propagation in the porcine intestine. Such mapping studies can help characterize differences between normal and dysrhythmic events, which have been associated with GI abnormalities, such as intestinal ischemia and gastroparesis. The COBRA method may be generally applicable for removing temporally synchronous artifacts in other biosignal processing domains. PMID:26829772

Designing Hyperchaotic Cat Maps With Any Desired Number of Positive Lyapunov Exponents.

PubMed

Hua, Zhongyun; Yi, Shuang; Zhou, Yicong; Li, Chengqing; Wu, Yue

2018-02-01

Generating chaotic maps with expected dynamics of users is a challenging topic. Utilizing the inherent relation between the Lyapunov exponents (LEs) of the Cat map and its associated Cat matrix, this paper proposes a simple but efficient method to construct an -dimensional ( -D) hyperchaotic Cat map (HCM) with any desired number of positive LEs. The method first generates two basic -D Cat matrices iteratively and then constructs the final -D Cat matrix by performing similarity transformation on one basic -D Cat matrix by the other. Given any number of positive LEs, it can generate an -D HCM with desired hyperchaotic complexity. Two illustrative examples of -D HCMs were constructed to show the effectiveness of the proposed method, and to verify the inherent relation between the LEs and Cat matrix. Theoretical analysis proves that the parameter space of the generated HCM is very large. Performance evaluations show that, compared with existing methods, the proposed method can construct -D HCMs with lower computation complexity and their outputs demonstrate strong randomness and complex ergodicity.

EcoEvo-MAPS: An Ecology and Evolution Assessment for Introductory through Advanced Undergraduates.

PubMed

Summers, Mindi M; Couch, Brian A; Knight, Jennifer K; Brownell, Sara E; Crowe, Alison J; Semsar, Katharine; Wright, Christian D; Smith, Michelle K

2018-06-01

A new assessment tool, Ecology and Evolution-Measuring Achievement and Progression in Science or EcoEvo-MAPS, measures student thinking in ecology and evolution during an undergraduate course of study. EcoEvo-MAPS targets foundational concepts in ecology and evolution and uses a novel approach that asks students to evaluate a series of predictions, conclusions, or interpretations as likely or unlikely to be true given a specific scenario. We collected evidence of validity and reliability for EcoEvo-MAPS through an iterative process of faculty review, student interviews, and analyses of assessment data from more than 3000 students at 34 associate's-, bachelor's-, master's-, and doctoral-granting institutions. The 63 likely/unlikely statements range in difficulty and target student understanding of key concepts aligned with the Vision and Change report. This assessment provides departments with a tool to measure student thinking at different time points in the curriculum and provides data that can be used to inform curricular and instructional modifications.

VIMOS Instrument Control Software Design: an Object Oriented Approach

NASA Astrophysics Data System (ADS)

Brau-Nogué, Sylvie; Lucuix, Christian

2002-12-01

The Franco-Italian VIMOS instrument is a VIsible imaging Multi-Object Spectrograph with outstanding multiplex capabilities, allowing to take spectra of more than 800 objects simultaneously, or integral field spectroscopy mode in a 54x54 arcsec area. VIMOS is being installed at the Nasmyth focus of the third Unit Telescope of the European Southern Observatory Very Large Telescope (VLT) at Mount Paranal in Chile. This paper will describe the analysis, the design and the implementation of the VIMOS Instrument Control System, using UML notation. Our Control group followed an Object Oriented software process while keeping in mind the ESO VLT standard control concepts. At ESO VLT a complete software library is available. Rather than applying waterfall lifecycle, ICS project used iterative development, a lifecycle consisting of several iterations. Each iteration consisted in : capture and evaluate the requirements, visual modeling for analysis and design, implementation, test, and deployment. Depending of the project phases, iterations focused more or less on specific activity. The result is an object model (the design model), including use-case realizations. An implementation view and a deployment view complement this product. An extract of VIMOS ICS UML model will be presented and some implementation, integration and test issues will be discussed.

Iterative Methods to Solve Linear RF Fields in Hot Plasma

NASA Astrophysics Data System (ADS)

Spencer, Joseph; Svidzinski, Vladimir; Evstatiev, Evstati; Galkin, Sergei; Kim, Jin-Soo

2014-10-01

Most magnetic plasma confinement devices use radio frequency (RF) waves for current drive and/or heating. Numerical modeling of RF fields is an important part of performance analysis of such devices and a predictive tool aiding design and development of future devices. Prior attempts at this modeling have mostly used direct solvers to solve the formulated linear equations. Full wave modeling of RF fields in hot plasma with 3D nonuniformities is mostly prohibited, with memory demands of a direct solver placing a significant limitation on spatial resolution. Iterative methods can significantly increase spatial resolution. We explore the feasibility of using iterative methods in 3D full wave modeling. The linear wave equation is formulated using two approaches: for cold plasmas the local cold plasma dielectric tensor is used (resolving resonances by particle collisions), while for hot plasmas the conductivity kernel (which includes a nonlocal dielectric response) is calculated by integrating along test particle orbits. The wave equation is discretized using a finite difference approach. The initial guess is important in iterative methods, and we examine different initial guesses including the solution to the cold plasma wave equation. Work is supported by the U.S. DOE SBIR program.

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert

2013-01-01

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

An adaptive Gaussian process-based iterative ensemble smoother for data assimilation

NASA Astrophysics Data System (ADS)

Ju, Lei; Zhang, Jiangjiang; Meng, Long; Wu, Laosheng; Zeng, Lingzao

2018-05-01

Accurate characterization of subsurface hydraulic conductivity is vital for modeling of subsurface flow and transport. The iterative ensemble smoother (IES) has been proposed to estimate the heterogeneous parameter field. As a Monte Carlo-based method, IES requires a relatively large ensemble size to guarantee its performance. To improve the computational efficiency, we propose an adaptive Gaussian process (GP)-based iterative ensemble smoother (GPIES) in this study. At each iteration, the GP surrogate is adaptively refined by adding a few new base points chosen from the updated parameter realizations. Then the sensitivity information between model parameters and measurements is calculated from a large number of realizations generated by the GP surrogate with virtually no computational cost. Since the original model evaluations are only required for base points, whose number is much smaller than the ensemble size, the computational cost is significantly reduced. The applicability of GPIES in estimating heterogeneous conductivity is evaluated by the saturated and unsaturated flow problems, respectively. Without sacrificing estimation accuracy, GPIES achieves about an order of magnitude of speed-up compared with the standard IES. Although subsurface flow problems are considered in this study, the proposed method can be equally applied to other hydrological models.

16QAM transmission with 5.2 bits/s/Hz spectral efficiency over transoceanic distance.

PubMed

Zhang, H; Cai, J-X; Batshon, H G; Davidson, C R; Sun, Y; Mazurczyk, M; Foursa, D G; Pilipetskii, A; Mohs, G; Bergano, Neal S

2012-05-21

We transmit 160 x 100 G PDM RZ 16 QAM channels with 5.2 bits/s/Hz spectral efficiency over 6,860 km. There are more than 3 billion 16 QAM symbols, i.e., 12 billion bits, processed in total. Using coded modulation and iterative decoding between a MAP decoder and an LDPC based FEC all channels are decoded with no remaining errors.

AutoMap User’s Guide

DTIC Science & Technology

2006-10-01

Hierarchy of Pre-Processing Techniques 3. NLP (Natural Language Processing) Utilities 3.1 Named-Entity Recognition 3.1.1 Example for Named-Entity... Recognition 3.2 Symbol RemovalN-Gram Identification: Bi-Grams 4. Stemming 4.1 Stemming Example 5. Delete List 5.1 Open a Delete List 5.1.1 Small...iterative and involves several key processes: • Named-Entity Recognition Named-Entity Recognition is an Automap feature that allows you to

Exploring the Ability of a Coarse-grained Potential to Describe the Stress-strain Response of Glassy Polystyrene

DTIC Science & Technology

2012-10-01

using the open-source code Large-scale Atomic/Molecular Massively Parallel Simulator ( LAMMPS ) (http://lammps.sandia.gov) (23). The commercial...parameters are proprietary and cannot be ported to the LAMMPS 4 simulation code. In our molecular dynamics simulations at the atomistic resolution, we...IBI iterative Boltzmann inversion LAMMPS Large-scale Atomic/Molecular Massively Parallel Simulator MAPS Materials Processes and Simulations MS

A local chaotic quasi-attractor in a kicked rotator

NASA Astrophysics Data System (ADS)

Jiang, Yu-Mei; Lu, Yun-Qing; Zhao, Jin-Gang; Wang, Xu-Ming; Chen, He-Sheng; He, Da-Ren

2002-03-01

Recently, Hu et al. reported a diffusion in a special kind of stochastic web observed in a kicked rotator described by a discontinuous but invertible two-dimensional area-preserving map^1. We modified the function form of the system so that the period of the kicking force becomes different in two parts of the space, and the conservative map becomes both discontinuous and noninvertible. It is found that when the ratio between both periods becomes smaller or larger than (but near to) 1, the chaotic diffusion in the web transfers to chaotic transients, which are attracted to the elliptic islands those existed inside the holes of the web earlier when the ratio equals 1. As soon as reaching the islands, the iteration follows the conservative laws exactly. Therefore we address these elliptic islands as "regular quasi-attractor"^2. When the ratio increases further and becomes far from 1, all the elliptic islands disappear and a local chaotic quasi-attractor appears instead. It attracts the iterations starting from most initial points in the phase space. This behavior may be considered as a kind of "confinement" of chaotic motion of a particle. ^1B. Hu et al., Phys.Rev.Lett.,82(1999)4224. ^2J. Wang et al., Phys.Rev.E, 64(2001)026202.

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

PubMed

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

Rater variables associated with ITER ratings.

PubMed

Paget, Michael; Wu, Caren; McIlwrick, Joann; Woloschuk, Wayne; Wright, Bruce; McLaughlin, Kevin

2013-10-01

Advocates of holistic assessment consider the ITER a more authentic way to assess performance. But this assessment format is subjective and, therefore, susceptible to rater bias. Here our objective was to study the association between rater variables and ITER ratings. In this observational study our participants were clerks at the University of Calgary and preceptors who completed online ITERs between February 2008 and July 2009. Our outcome variable was global rating on the ITER (rated 1-5), and we used a generalized estimating equation model to identify variables associated with this rating. Students were rated "above expected level" or "outstanding" on 66.4 % of 1050 online ITERs completed during the study period. Two rater variables attenuated ITER ratings: the log transformed time taken to complete the ITER [β = -0.06, 95 % confidence interval (-0.10, -0.02), p = 0.002], and the number of ITERs that a preceptor completed over the time period of the study [β = -0.008 (-0.02, -0.001), p = 0.02]. In this study we found evidence of leniency bias that resulted in two thirds of students being rated above expected level of performance. This leniency bias appeared to be attenuated by delay in ITER completion, and was also blunted in preceptors who rated more students. As all biases threaten the internal validity of the assessment process, further research is needed to confirm these and other sources of rater bias in ITER ratings, and to explore ways of limiting their impact.

Evidential analysis of difference images for change detection of multitemporal remote sensing images

NASA Astrophysics Data System (ADS)

Chen, Yin; Peng, Lijuan; Cremers, Armin B.

2018-03-01

In this article, we develop two methods for unsupervised change detection in multitemporal remote sensing images based on Dempster-Shafer's theory of evidence (DST). In most unsupervised change detection methods, the probability of difference image is assumed to be characterized by mixture models, whose parameters are estimated by the expectation maximization (EM) method. However, the main drawback of the EM method is that it does not consider spatial contextual information, which may entail rather noisy detection results with numerous spurious alarms. To remedy this, we firstly develop an evidence theory based EM method (EEM) which incorporates spatial contextual information in EM by iteratively fusing the belief assignments of neighboring pixels to the central pixel. Secondly, an evidential labeling method in the sense of maximizing a posteriori probability (MAP) is proposed in order to further enhance the detection result. It first uses the parameters estimated by EEM to initialize the class labels of a difference image. Then it iteratively fuses class conditional information and spatial contextual information, and updates labels and class parameters. Finally it converges to a fixed state which gives the detection result. A simulated image set and two real remote sensing data sets are used to evaluate the two evidential change detection methods. Experimental results show that the new evidential methods are comparable to other prevalent methods in terms of total error rate.

Adaptive cornea modeling from keratometric data.

PubMed

Martínez-Finkelshtein, Andrei; López, Darío Ramos; Castro, Gracia M; Alió, Jorge L

2011-07-01

To introduce an iterative, multiscale procedure that allows for better reconstruction of the shape of the anterior surface of the cornea from altimetric data collected by a corneal topographer. The report describes, first, an adaptive, multiscale mathematical algorithm for the parsimonious fit of the corneal surface data that adapts the number of functions used in the reconstruction to the conditions of each cornea. The method also implements a dynamic selection of the parameters and the management of noise. Then, several numerical experiments are performed, comparing it with the results obtained by the standard Zernike-based procedure. The numerical experiments showed that the algorithm exhibits steady exponential error decay, independent of the level of aberration of the cornea. The complexity of each anisotropic Gaussian-basis function in the functional representation is the same, but the parameters vary to fit the current scale. This scale is determined only by the residual errors and not by the number of the iteration. Finally, the position and clustering of the centers, as well as the size of the shape parameters, provides additional spatial information about the regions of higher irregularity. The methodology can be used for the real-time reconstruction of both altimetric data and corneal power maps from the data collected by keratoscopes, such as the Placido ring-based topographers, that will be decisive in early detection of corneal diseases such as keratoconus.

Study of steam condensation at sub-atmospheric pressure: setting a basic research using MELCOR code

NASA Astrophysics Data System (ADS)

Manfredini, A.; Mazzini, M.

2017-11-01

One of the most serious accidents that can occur in the experimental nuclear fusion reactor ITER is the break of one of the headers of the refrigeration system of the first wall of the Tokamak. This results in water-steam mixture discharge in vacuum vessel (VV), with consequent pressurization of this container. To prevent the pressure in the VV exceeds 150 KPa absolute, a system discharges the steam inside a suppression pool, at an absolute pressure of 4.2 kPa. The computer codes used to analyze such incident (eg. RELAP 5 or MELCOR) are not validated experimentally for such conditions. Therefore, we planned a basic research, in order to have experimental data useful to validate the heat transfer correlations used in these codes. After a thorough literature search on this topic, ACTA, in collaboration with the staff of ITER, defined the experimental matrix and performed the design of the experimental apparatus. For the thermal-hydraulic design of the experiments, we executed a series of calculations by MELCOR. This code, however, was used in an unconventional mode, with the development of models suited respectively to low and high steam flow-rate tests. The article concludes with a discussion of the placement of experimental data within the map featuring the phenomenon characteristics, showing the importance of the new knowledge acquired, particularly in the case of chugging.