Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Bryan (Technical Monitor)

2002-01-01

We present new, efficient central schemes for multi-dimensional Hamilton-Jacobi equations. These non-oscillatory, non-staggered schemes are first- and second-order accurate and are designed to scale well with an increasing dimension. Efficiency is obtained by carefully choosing the location of the evolution points and by using a one-dimensional projection step. First-and second-order accuracy is verified for a variety of multi-dimensional, convex and non-convex problems.

A Visual Analytics Approach for Station-Based Air Quality Data

PubMed Central

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-01-01

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support. PMID:28029117

A Visual Analytics Approach for Station-Based Air Quality Data.

PubMed

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Boundary layer energization by means of optimized vortex generators

NASA Technical Reports Server (NTRS)

Barber, T. J.; Mounts, J. S.; Mccormick, D. C.

1993-01-01

A three-dimensional, multi-block, multi-zone, Euler analysis has been developed and applied to analyze the flow processes induced by a lateral array of low profile vortex generators (VG). These vortex generators have been shown to alleviate boundary layer separation through the generation of streamwise vorticity. The analysis has been applied to help develop improved VG configurations in an efficient manner. Special attention has been paid to determining the accuracy requirements of the solver for calculations in which vortical mechanisms are dominant. The analysis has been used to assess the effectiveness or boundary layer energization capacity of different VG's, including the effect of scale and shape variation. Finally, the analysis has been validated through comparisons with experimental data obtained in a large-scale low-speed wind tunnel.

Large-scale Instability during Gravitational Collapse with Neutrino Transport and a Core-Collapse Supernova

NASA Astrophysics Data System (ADS)

Aksenov, A. G.; Chechetkin, V. M.

2018-04-01

Most of the energy released in the gravitational collapse of the cores of massive stars is carried away by neutrinos. Neutrinos play a pivotal role in explaining core-collape supernovae. Currently, mathematical models of the gravitational collapse are based on multi-dimensional gas dynamics and thermonuclear reactions, while neutrino transport is considered in a simplified way. Multidimensional gas dynamics is used with neutrino transport in the flux-limited diffusion approximation to study the role of multi-dimensional effects. The possibility of large-scale convection is discussed, which is interesting both for explaining SN II and for setting up observations to register possible high-energy (≳10MeV) neutrinos from the supernova. A new multi-dimensional, multi-temperature gas dynamics method with neutrino transport is presented.

A SOLAR CORONAL JET EVENT TRIGGERS A CORONAL MASS EJECTION

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

Liu, Jiajia; Wang, Yuming; Shen, Chenglong

2015-11-10

In this paper, we present multi-point, multi-wavelength observations and analysis of a solar coronal jet and coronal mass ejection (CME) event. Employing the GCS model, we obtained the real (three-dimensional) heliocentric distance and direction of the CME and found it to propagate at a high speed of over 1000 km s{sup −1}. The jet erupted before the CME and shared the same source region. The temporal and spacial relationship between these two events lead us to the possibility that the jet triggered the CME and became its core. This scenario hold the promise of enriching our understanding of the triggeringmore » mechanism of CMEs and their relations to coronal large-scale jets. On the other hand, the magnetic field configuration of the source region observed by the Solar Dynamics Observatory (SDO)/HMI instrument along with the off-limb inverse Y-shaped configuration observed by SDO/AIA in the 171 Å passband provide the first detailed observation of the three-dimensional reconnection process of a large-scale jet as simulated in Pariat et al. The eruption process of the jet highlights the importance of filament-like material during the eruption of not only small-scale X-ray jets, but likely also of large-scale EUV jets. Based on our observations and analysis, we propose the most probable mechanism for the whole event, with a blob structure overlaying the three-dimensional structure of the jet, to describe the interaction between the jet and the CME.« less

Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture

PubMed Central

Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis

2015-01-01

A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893

Modeling change from large-scale high-dimensional spatio-temporal array data

NASA Astrophysics Data System (ADS)

Lu, Meng; Pebesma, Edzer

2014-05-01

The massive data that come from Earth observation satellite and other sensors provide significant information for modeling global change. At the same time, the high dimensionality of the data has brought challenges in data acquisition, management, effective querying and processing. In addition, the output of earth system modeling tends to be data intensive and needs methodologies for storing, validation, analyzing and visualization, e.g. as maps. An important proportion of earth system observations and simulated data can be represented as multi-dimensional array data, which has received increasingly attention in big data management and spatial-temporal analysis. Study cases will be developed in natural science such as climate change, hydrological modeling, sediment dynamics, from which the addressing of big data problems is necessary. Multi-dimensional array-based database management and analytics system such as Rasdaman, SciDB, and R will be applied to these cases. From these studies will hope to learn the strengths and weaknesses of these systems, how they might work together or how semantics of array operations differ, through addressing the problems associated with big data. Research questions include: • How can we reduce dimensions spatially and temporally, or thematically? • How can we extend existing GIS functions to work on multidimensional arrays? • How can we combine data sets of different dimensionality or different resolutions? • Can map algebra be extended to an intelligible array algebra? • What are effective semantics for array programming of dynamic data driven applications? • In which sense are space and time special, as dimensions, compared to other properties? • How can we make the analysis of multi-spectral, multi-temporal and multi-sensor earth observation data easy?

Empirical Determination of Competence Areas to Computer Science Education

ERIC Educational Resources Information Center

Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia

2014-01-01

The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

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

Lee, Hyun Jung; McDonnell, Kevin T.; Zelenyuk, Alla

2014-03-01

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly inmore » high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.« less

Dimensional flow and fuzziness in quantum gravity: Emergence of stochastic spacetime

NASA Astrophysics Data System (ADS)

Calcagni, Gianluca; Ronco, Michele

2017-10-01

We show that the uncertainty in distance and time measurements found by the heuristic combination of quantum mechanics and general relativity is reproduced in a purely classical and flat multi-fractal spacetime whose geometry changes with the probed scale (dimensional flow) and has non-zero imaginary dimension, corresponding to a discrete scale invariance at short distances. Thus, dimensional flow can manifest itself as an intrinsic measurement uncertainty and, conversely, measurement-uncertainty estimates are generally valid because they rely on this universal property of quantum geometries. These general results affect multi-fractional theories, a recent proposal related to quantum gravity, in two ways: they can fix two parameters previously left free (in particular, the value of the spacetime dimension at short scales) and point towards a reinterpretation of the ultraviolet structure of geometry as a stochastic foam or fuzziness. This is also confirmed by a correspondence we establish between Nottale scale relativity and the stochastic geometry of multi-fractional models.

Satellite Imagery Analysis for Automated Global Food Security Forecasting

NASA Astrophysics Data System (ADS)

Moody, D.; Brumby, S. P.; Chartrand, R.; Keisler, R.; Mathis, M.; Beneke, C. M.; Nicholaeff, D.; Skillman, S.; Warren, M. S.; Poehnelt, J.

2017-12-01

The recent computing performance revolution has driven improvements in sensor, communication, and storage technology. Multi-decadal remote sensing datasets at the petabyte scale are now available in commercial clouds, with new satellite constellations generating petabytes/year of daily high-resolution global coverage imagery. Cloud computing and storage, combined with recent advances in machine learning, are enabling understanding of the world at a scale and at a level of detail never before feasible. We present results from an ongoing effort to develop satellite imagery analysis tools that aggregate temporal, spatial, and spectral information and that can scale with the high-rate and dimensionality of imagery being collected. We focus on the problem of monitoring food crop productivity across the Middle East and North Africa, and show how an analysis-ready, multi-sensor data platform enables quick prototyping of satellite imagery analysis algorithms, from land use/land cover classification and natural resource mapping, to yearly and monthly vegetative health change trends at the structural field level.

Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models

PubMed Central

Cowley, Benjamin R.; Doiron, Brent; Kohn, Adam

2016-01-01

Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure. PMID:27926936

ICM: a web server for integrated clustering of multi-dimensional biomedical data.

PubMed

He, Song; He, Haochen; Xu, Wenjian; Huang, Xin; Jiang, Shuai; Li, Fei; He, Fuchu; Bo, Xiaochen

2016-07-08

Large-scale efforts for parallel acquisition of multi-omics profiling continue to generate extensive amounts of multi-dimensional biomedical data. Thus, integrated clustering of multiple types of omics data is essential for developing individual-based treatments and precision medicine. However, while rapid progress has been made, methods for integrated clustering are lacking an intuitive web interface that facilitates the biomedical researchers without sufficient programming skills. Here, we present a web tool, named Integrated Clustering of Multi-dimensional biomedical data (ICM), that provides an interface from which to fuse, cluster and visualize multi-dimensional biomedical data and knowledge. With ICM, users can explore the heterogeneity of a disease or a biological process by identifying subgroups of patients. The results obtained can then be interactively modified by using an intuitive user interface. Researchers can also exchange the results from ICM with collaborators via a web link containing a Project ID number that will directly pull up the analysis results being shared. ICM also support incremental clustering that allows users to add new sample data into the data of a previous study to obtain a clustering result. Currently, the ICM web server is available with no login requirement and at no cost at http://biotech.bmi.ac.cn/icm/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Multi-scale calculation based on dual domain material point method combined with molecular dynamics

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

Dhakal, Tilak Raj

This dissertation combines the dual domain material point method (DDMP) with molecular dynamics (MD) in an attempt to create a multi-scale numerical method to simulate materials undergoing large deformations with high strain rates. In these types of problems, the material is often in a thermodynamically non-equilibrium state, and conventional constitutive relations are often not available. In this method, the closure quantities, such as stress, at each material point are calculated from a MD simulation of a group of atoms surrounding the material point. Rather than restricting the multi-scale simulation in a small spatial region, such as phase interfaces, or crackmore » tips, this multi-scale method can be used to consider non-equilibrium thermodynamic e ects in a macroscopic domain. This method takes advantage that the material points only communicate with mesh nodes, not among themselves; therefore MD simulations for material points can be performed independently in parallel. First, using a one-dimensional shock problem as an example, the numerical properties of the original material point method (MPM), the generalized interpolation material point (GIMP) method, the convected particle domain interpolation (CPDI) method, and the DDMP method are investigated. Among these methods, only the DDMP method converges as the number of particles increases, but the large number of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared of particles needed for convergence makes the method very expensive especially in our multi-scale method where we calculate stress in each material point using MD simulation. To improve DDMP, the sub-point method is introduced in this dissertation, which provides high quality numerical solutions with a very small number of particles. The multi-scale method based on DDMP with sub-points is successfully implemented for a one dimensional problem of shock wave propagation in a cerium crystal. The MD simulation to calculate stress in each material point is performed in GPU using CUDA to accelerate the computation. The numerical properties of the multiscale method are investigated as well as the results from this multi-scale calculation are compared with direct MD simulation results to demonstrate the feasibility of the method. Also, the multi-scale method is applied for a two dimensional problem of jet formation around copper notch under a strong impact.« less

The development of a multi-dimensional gambling accessibility scale.

PubMed

Hing, Nerilee; Haw, John

2009-12-01

The aim of the current study was to develop a scale of gambling accessibility that would have theoretical significance to exposure theory and also serve to highlight the accessibility risk factors for problem gambling. Scale items were generated from the Productivity Commission's (Australia's Gambling Industries: Report No. 10. AusInfo, Canberra, 1999) recommendations and tested on a group with high exposure to the gambling environment. In total, 533 gaming venue employees (aged 18-70 years; 67% women) completed a questionnaire that included six 13-item scales measuring accessibility across a range of gambling forms (gaming machines, keno, casino table games, lotteries, horse and dog racing, sports betting). Also included in the questionnaire was the Problem Gambling Severity Index (PGSI) along with measures of gambling frequency and expenditure. Principal components analysis indicated that a common three factor structure existed across all forms of gambling and these were labelled social accessibility, physical accessibility and cognitive accessibility. However, convergent validity was not demonstrated with inconsistent correlations between each subscale and measures of gambling behaviour. These results are discussed in light of exposure theory and the further development of a multi-dimensional measure of gambling accessibility.

Cardiac Light-Sheet Fluorescent Microscopy for Multi-Scale and Rapid Imaging of Architecture and Function

NASA Astrophysics Data System (ADS)

Fei, Peng; Lee, Juhyun; Packard, René R. Sevag; Sereti, Konstantina-Ioanna; Xu, Hao; Ma, Jianguo; Ding, Yichen; Kang, Hanul; Chen, Harrison; Sung, Kevin; Kulkarni, Rajan; Ardehali, Reza; Kuo, C.-C. Jay; Xu, Xiaolei; Ho, Chih-Ming; Hsiai, Tzung K.

2016-03-01

Light Sheet Fluorescence Microscopy (LSFM) enables multi-dimensional and multi-scale imaging via illuminating specimens with a separate thin sheet of laser. It allows rapid plane illumination for reduced photo-damage and superior axial resolution and contrast. We hereby demonstrate cardiac LSFM (c-LSFM) imaging to assess the functional architecture of zebrafish embryos with a retrospective cardiac synchronization algorithm for four-dimensional reconstruction (3-D space + time). By combining our approach with tissue clearing techniques, we reveal the entire cardiac structures and hypertrabeculation of adult zebrafish hearts in response to doxorubicin treatment. By integrating the resolution enhancement technique with c-LSFM to increase the resolving power under a large field-of-view, we demonstrate the use of low power objective to resolve the entire architecture of large-scale neonatal mouse hearts, revealing the helical orientation of individual myocardial fibers. Therefore, our c-LSFM imaging approach provides multi-scale visualization of architecture and function to drive cardiovascular research with translational implication in congenital heart diseases.

3D deblending of simultaneous source data based on 3D multi-scale shaping operator

NASA Astrophysics Data System (ADS)

Zu, Shaohuan; Zhou, Hui; Mao, Weijian; Gong, Fei; Huang, Weilin

2018-04-01

We propose an iterative three-dimensional (3D) deblending scheme using 3D multi-scale shaping operator to separate 3D simultaneous source data. The proposed scheme is based on the property that signal is coherent, whereas interference is incoherent in some domains, e.g., common receiver domain and common midpoint domain. In two-dimensional (2D) blended record, the coherency difference of signal and interference is in only one spatial direction. Compared with 2D deblending, the 3D deblending can take more sparse constraints into consideration to obtain better performance, e.g., in 3D common receiver gather, the coherency difference is in two spatial directions. Furthermore, with different levels of coherency, signal and interference distribute in different scale curvelet domains. In both 2D and 3D blended records, most coherent signal locates in coarse scale curvelet domain, while most incoherent interference distributes in fine scale curvelet domain. The scale difference is larger in 3D deblending, thus, we apply the multi-scale shaping scheme to further improve the 3D deblending performance. We evaluate the performance of 3D and 2D deblending with the multi-scale and global shaping operators, respectively. One synthetic and one field data examples demonstrate the advantage of the 3D deblending with 3D multi-scale shaping operator.

The theory of n-scales

NASA Astrophysics Data System (ADS)

Dündar, Furkan Semih

2018-01-01

We provide a theory of n-scales previously called as n dimensional time scales. In previous approaches to the theory of time scales, multi-dimensional scales were taken as product space of two time scales [1, 2]. n-scales make the mathematical structure more flexible and appropriate to real world applications in physics and related fields. Here we define an n-scale as an arbitrary closed subset of ℝn. Modified forward and backward jump operators, Δ-derivatives and Δ-integrals on n-scales are defined.

Analysis of a municipal wastewater treatment plant using a neural network-based pattern analysis

USGS Publications Warehouse

Hong, Y.-S.T.; Rosen, Michael R.; Bhamidimarri, R.

2003-01-01

This paper addresses the problem of how to capture the complex relationships that exist between process variables and to diagnose the dynamic behaviour of a municipal wastewater treatment plant (WTP). Due to the complex biological reaction mechanisms, the highly time-varying, and multivariable aspects of the real WTP, the diagnosis of the WTP are still difficult in practice. The application of intelligent techniques, which can analyse the multi-dimensional process data using a sophisticated visualisation technique, can be useful for analysing and diagnosing the activated-sludge WTP. In this paper, the Kohonen Self-Organising Feature Maps (KSOFM) neural network is applied to analyse the multi-dimensional process data, and to diagnose the inter-relationship of the process variables in a real activated-sludge WTP. By using component planes, some detailed local relationships between the process variables, e.g., responses of the process variables under different operating conditions, as well as the global information is discovered. The operating condition and the inter-relationship among the process variables in the WTP have been diagnosed and extracted by the information obtained from the clustering analysis of the maps. It is concluded that the KSOFM technique provides an effective analysing and diagnosing tool to understand the system behaviour and to extract knowledge contained in multi-dimensional data of a large-scale WTP. ?? 2003 Elsevier Science Ltd. All rights reserved.

The effects of perfectionism on academic achievement in medical students.

PubMed

Kyeon, Yeong-Gi; Cho, Sung-Myeong; Hwang, Hwyeon-Guk; Lee, Kang-Uk

2010-09-01

The purpose of this study was to explore the differential effects of multi-dimensional perfectionism on academic achievement, depression, engagement, and burnout in medical students. Also, the mediating effects of engagement on perfectionism and academic achievement, as well as the effects of burnout on perfectionism and depression, were examined. Two hundred eight medical students participated, and 167 students completed questionnaires, including the Frost Multi-dimensional Perfectionism Scale (FMPS), Hewitt & Flett Multi-dimensional Perfectionism Scale (HFMPS), Beck Depression Inventory (BDI), Schaufeli Engagement Scale (SES), and Malslach Burnout Inventory-General Survey (MBI-GS). Academic achievement was measured as the grade point average (GPA) of the previous semester. Data were analyzed by correlation analyses, independent t-tests, and Structural Equation Model (SEM) for path analysis. Adaptive perfectionism (personal standard, self-oriented perfectionism) was associated with GPA (r=0.164, p<0.05; r=0.173, p<0.05) and engagement (r=0.394, p<0.01; r=0.449, p<0.01), and maladaptive perfectionism (parental criticism, concern over mistakes, socially prescribed perfectionism) was associated with depression (r=0.208, p<0.01; r=0.254, p<0.01; r=0.234, p<0.01) and burnout (r=0.218, p<0.01; r=0.236, p<0.01; r=0.280, p<0.01). Engagement had mediating effects on adaptive perfectionism and GPA, and burnout had mediating effects on maladaptive perfectionism and depression. Students who experienced academic failure had lower engagement than those who did not. This study demonstrates that academic achievement and emotional difficulties such as depression are determined by adaptive and maladaptive perfectionism, respectively, in medical students.

The Moral Injury Symptom Scale-Military Version.

PubMed

Koenig, Harold G; Ames, Donna; Youssef, Nagy A; Oliver, John P; Volk, Fred; Teng, Ellen J; Haynes, Kerry; Erickson, Zachary D; Arnold, Irina; O'Garo, Keisha; Pearce, Michelle

2018-02-01

The purpose of this study was to develop a multi-dimensional measure of moral injury symptoms that can be used as a primary outcome measure in intervention studies that target moral injury (MI) in Veterans and Active Duty Military with PTSD. This was a multi-center study of 427 Veterans and Active Duty Military with PTSD symptoms recruited from VA Medical Centers in Augusta, Los Angeles, Durham, Houston, and San Antonio, and from Liberty University in Lynchburg. Internal reliability of the Moral Injury Symptom Scale-Military Version (MISS-M) was examined along with factor analytic, discriminant, and convergent validity. Participants were randomly split into two equal samples, with exploratory factor analysis conducted in the first sample and confirmatory factor analysis in the second. Test-retest reliability was assessed in a subsample of 64 Veterans. The 45-item MISS-M consists of 10 theoretically grounded subscales assessing guilt, shame, moral concerns, religious struggles, loss of religious faith/hope, loss of meaning/purpose, difficulty forgiving, loss of trust, and self-condemnation. The Cronbach's alpha of the overall scale was .92 and of individual subscales ranged from .56 to .91. The test-retest reliability was .91 for the total scale and ranged from .78 to .90 for subscales. Discriminant validity was demonstrated by relatively weak correlations with other psychosocial, religious, and physical health constructs, and convergent validity was indicated by strong correlations with PTSD, depression, and anxiety symptoms. The MISS-M is a reliable and valid multi-dimensional symptom measure of moral injury that can be used in studies targeting MI in Veterans and Active Duty Military with PTSD symptoms and may also be used by clinicians to identify those at risk.

Assessing Children's Homework Performance: Development of Multi-Dimensional, Multi-Informant Rating Scales.

PubMed

Power, Thomas J; Dombrowski, Stefan C; Watkins, Marley W; Mautone, Jennifer A; Eagle, John W

2007-06-01

Efforts to develop interventions to improve homework performance have been impeded by limitations in the measurement of homework performance. This study was conducted to develop rating scales for assessing homework performance among students in elementary and middle school. Items on the scales were intended to assess student strengths as well as deficits in homework performance. The sample included 163 students attending two school districts in the Northeast. Parents completed the 36-item Homework Performance Questionnaire - Parent Scale (HPQ-PS). Teachers completed the 22-item teacher scale (HPQ-TS) for each student for whom the HPQ-PS had been completed. A common factor analysis with principal axis extraction and promax rotation was used to analyze the findings. The results of the factor analysis of the HPQ-PS revealed three salient and meaningful factors: student task orientation/efficiency, student competence, and teacher support. The factor analysis of the HPQ-TS uncovered two salient and substantive factors: student responsibility and student competence. The findings of this study suggest that the HPQ is a promising set of measures for assessing student homework functioning and contextual factors that may influence performance. Directions for future research are presented.

Assessing Children’s Homework Performance: Development of Multi-Dimensional, Multi-Informant Rating Scales

PubMed Central

Power, Thomas J.; Dombrowski, Stefan C.; Watkins, Marley W.; Mautone, Jennifer A.; Eagle, John W.

2007-01-01

Efforts to develop interventions to improve homework performance have been impeded by limitations in the measurement of homework performance. This study was conducted to develop rating scales for assessing homework performance among students in elementary and middle school. Items on the scales were intended to assess student strengths as well as deficits in homework performance. The sample included 163 students attending two school districts in the Northeast. Parents completed the 36-item Homework Performance Questionnaire – Parent Scale (HPQ-PS). Teachers completed the 22-item teacher scale (HPQ-TS) for each student for whom the HPQ-PS had been completed. A common factor analysis with principal axis extraction and promax rotation was used to analyze the findings. The results of the factor analysis of the HPQ-PS revealed three salient and meaningful factors: student task orientation/efficiency, student competence, and teacher support. The factor analysis of the HPQ-TS uncovered two salient and substantive factors: student responsibility and student competence. The findings of this study suggest that the HPQ is a promising set of measures for assessing student homework functioning and contextual factors that may influence performance. Directions for future research are presented. PMID:18516211

Some theorems and properties of multi-dimensional fractional Laplace transforms

NASA Astrophysics Data System (ADS)

Ahmood, Wasan Ajeel; Kiliçman, Adem

2016-06-01

The aim of this work is to study theorems and properties for the one-dimensional fractional Laplace transform, generalize some properties for the one-dimensional fractional Lapalce transform to be valid for the multi-dimensional fractional Lapalce transform and is to give the definition of the multi-dimensional fractional Lapalce transform. This study includes: dedicate the one-dimensional fractional Laplace transform for functions of only one independent variable with some of important theorems and properties and develop of some properties for the one-dimensional fractional Laplace transform to multi-dimensional fractional Laplace transform. Also, we obtain a fractional Laplace inversion theorem after a short survey on fractional analysis based on the modified Riemann-Liouville derivative.

Processor farming in two-level analysis of historical bridge

NASA Astrophysics Data System (ADS)

Krejčí, T.; Kruis, J.; Koudelka, T.; Šejnoha, M.

2017-11-01

This contribution presents a processor farming method in connection with a multi-scale analysis. In this method, each macro-scopic integration point or each finite element is connected with a certain meso-scopic problem represented by an appropriate representative volume element (RVE). The solution of a meso-scale problem provides then effective parameters needed on the macro-scale. Such an analysis is suitable for parallel computing because the meso-scale problems can be distributed among many processors. The application of the processor farming method to a real world masonry structure is illustrated by an analysis of Charles bridge in Prague. The three-dimensional numerical model simulates the coupled heat and moisture transfer of one half of arch No. 3. and it is a part of a complex hygro-thermo-mechanical analysis which has been developed to determine the influence of climatic loading on the current state of the bridge.

A multi scale multi-dimensional thermo electrochemical modelling of high capacity lithium-ion cells

NASA Astrophysics Data System (ADS)

Tourani, Abbas; White, Peter; Ivey, Paul

2014-06-01

Lithium iron phosphate (LFP) and lithium manganese oxide (LMO) are competitive and complementary to each other as cathode materials for lithium-ion batteries, especially for use in electric vehicles. A multi scale multi-dimensional physic-based model is proposed in this paper to study the thermal behaviour of the two lithium-ion chemistries. The model consists of two sub models, a one dimensional (1D) electrochemical sub model and a two dimensional (2D) thermo-electric sub model, which are coupled and solved concurrently. The 1D model predicts the heat generation rate (Qh) and voltage (V) of the battery cell through different load cycles. The 2D model of the battery cell accounts for temperature distribution and current distribution across the surface of the battery cell. The two cells are examined experimentally through 90 h load cycles including high/low charge/discharge rates. The experimental results are compared with the model results and they are in good agreement. The presented results in this paper verify the cells temperature behaviour at different operating conditions which will lead to the design of a cost effective thermal management system for the battery pack.

Assessing the weighted multi-objective adaptive surrogate model optimization to derive large-scale reservoir operating rules with sensitivity analysis

NASA Astrophysics Data System (ADS)

Zhang, Jingwen; Wang, Xu; Liu, Pan; Lei, Xiaohui; Li, Zejun; Gong, Wei; Duan, Qingyun; Wang, Hao

2017-01-01

The optimization of large-scale reservoir system is time-consuming due to its intrinsic characteristics of non-commensurable objectives and high dimensionality. One way to solve the problem is to employ an efficient multi-objective optimization algorithm in the derivation of large-scale reservoir operating rules. In this study, the Weighted Multi-Objective Adaptive Surrogate Model Optimization (WMO-ASMO) algorithm is used. It consists of three steps: (1) simplifying the large-scale reservoir operating rules by the aggregation-decomposition model, (2) identifying the most sensitive parameters through multivariate adaptive regression splines (MARS) for dimensional reduction, and (3) reducing computational cost and speeding the searching process by WMO-ASMO, embedded with weighted non-dominated sorting genetic algorithm II (WNSGAII). The intercomparison of non-dominated sorting genetic algorithm (NSGAII), WNSGAII and WMO-ASMO are conducted in the large-scale reservoir system of Xijiang river basin in China. Results indicate that: (1) WNSGAII surpasses NSGAII in the median of annual power generation, increased by 1.03% (from 523.29 to 528.67 billion kW h), and the median of ecological index, optimized by 3.87% (from 1.879 to 1.809) with 500 simulations, because of the weighted crowding distance and (2) WMO-ASMO outperforms NSGAII and WNSGAII in terms of better solutions (annual power generation (530.032 billion kW h) and ecological index (1.675)) with 1000 simulations and computational time reduced by 25% (from 10 h to 8 h) with 500 simulations. Therefore, the proposed method is proved to be more efficient and could provide better Pareto frontier.

Mechanical exfoliation of two-dimensional materials

NASA Astrophysics Data System (ADS)

Gao, Enlai; Lin, Shao-Zhen; Qin, Zhao; Buehler, Markus J.; Feng, Xi-Qiao; Xu, Zhiping

2018-06-01

Two-dimensional materials such as graphene and transition metal dichalcogenides have been identified and drawn much attention over the last few years for their unique structural and electronic properties. However, their rise begins only after these materials are successfully isolated from their layered assemblies or adhesive substrates into individual monolayers. Mechanical exfoliation and transfer are the most successful techniques to obtain high-quality single- or few-layer nanocrystals from their native multi-layer structures or their substrate for growth, which involves interfacial peeling and intralayer tearing processes that are controlled by material properties, geometry and the kinetics of exfoliation. This procedure is rationalized in this work through theoretical analysis and atomistic simulations. We propose a criterion to assess the feasibility for the exfoliation of two-dimensional sheets from an adhesive substrate without fracturing itself, and explore the effects of material and interface properties, as well as the geometrical, kinetic factors on the peeling behaviors and the torn morphology. This multi-scale approach elucidates the microscopic mechanism of the mechanical processes, offering predictive models and tools for the design of experimental procedures to obtain single- or few-layer two-dimensional materials and structures.

Multi Length Scale Imaging of Flocculated Estuarine Sediments; Insights into their Complex 3D Structure

NASA Astrophysics Data System (ADS)

Wheatland, Jonathan; Bushby, Andy; Droppo, Ian; Carr, Simon; Spencer, Kate

2015-04-01

Suspended estuarine sediments form flocs that are compositionally complex, fragile and irregularly shaped. The fate and transport of suspended particulate matter (SPM) is determined by the size, shape, density, porosity and stability of these flocs and prediction of SPM transport requires accurate measurements of these three-dimensional (3D) physical properties. However, the multi-scaled nature of flocs in addition to their fragility makes their characterisation in 3D problematic. Correlative microscopy is a strategy involving the spatial registration of information collected at different scales using several imaging modalities. Previously, conventional optical microscopy (COM) and transmission electron microscopy (TEM) have enabled 2-dimensional (2D) floc characterisation at the gross (> 1 µm) and sub-micron scales respectively. Whilst this has proven insightful there remains a critical spatial and dimensional gap preventing the accurate measurement of geometric properties and an understanding of how structures at different scales are related. Within life sciences volumetric imaging techniques such as 3D micro-computed tomography (3D µCT) and focused ion beam scanning electron microscopy [FIB-SEM (or FIB-tomography)] have been combined to characterise materials at the centimetre to micron scale. Combining these techniques with TEM enables an advanced correlative study, allowing material properties across multiple spatial and dimensional scales to be visualised. The aims of this study are; 1) to formulate an advanced correlative imaging strategy combining 3D µCT, FIB-tomography and TEM; 2) to acquire 3D datasets; 3) to produce a model allowing their co-visualisation; 4) to interpret 3D floc structure. To reduce the chance of structural alterations during analysis samples were first 'fixed' in 2.5% glutaraldehyde/2% formaldehyde before being embedding in Durcupan resin. Intermediate steps were implemented to improve contrast and remove pore water, achieved by the addition of heavy metal stains and washing samples in a series of ethanol solutions and acetone. Gross-scale characterisation involved scanning samples using a Nikon Metrology HM X 225 µCT. For micro-scale analysis a working surface was revealed by microtoming the sample. Ultrathin sections were then collected and analysed using a JEOL 1200 Ex II TEM, and FIB-tomography datasets obtained using an FEI Quanta 3D FIB-SEM. Finally, to locate the surface and relate TEM and FIB-tomography datasets to the original floc, samples were rescanned using the µCT. Image processing was initially conducted in ImageJ. Following this datasets were imported into Amira 5.5 where pixel intensity thresholding allowed particle-matrix boundaries to be defined. Using 'landmarks' datasets were then registered to enable their co-visualisation in 3D models. Analysis of registered datasets reveals the complex non-fractal nature of flocs, whose properties span several of orders of magnitude. Primary particles are organised into discrete 'bundles', the arrangement of which directly influences their gross morphology. This strategy, which allows the co-visualisation of spatially registered multi-scale 3D datasets, provides unique insights into the true nature floc which would other have been impossible.

Multi-scale modeling of irradiation effects in spallation neutron source materials

NASA Astrophysics Data System (ADS)

Yoshiie, T.; Ito, T.; Iwase, H.; Kaneko, Y.; Kawai, M.; Kishida, I.; Kunieda, S.; Sato, K.; Shimakawa, S.; Shimizu, F.; Hashimoto, S.; Hashimoto, N.; Fukahori, T.; Watanabe, Y.; Xu, Q.; Ishino, S.

2011-07-01

Changes in mechanical property of Ni under irradiation by 3 GeV protons were estimated by multi-scale modeling. The code consisted of four parts. The first part was based on the Particle and Heavy-Ion Transport code System (PHITS) code for nuclear reactions, and modeled the interactions between high energy protons and nuclei in the target. The second part covered atomic collisions by particles without nuclear reactions. Because the energy of the particles was high, subcascade analysis was employed. The direct formation of clusters and the number of mobile defects were estimated using molecular dynamics (MD) and kinetic Monte-Carlo (kMC) methods in each subcascade. The third part considered damage structural evolutions estimated by reaction kinetic analysis. The fourth part involved the estimation of mechanical property change using three-dimensional discrete dislocation dynamics (DDD). Using the above four part code, stress-strain curves for high energy proton irradiated Ni were obtained.

Status of the Combustion Devices Injector Technology Program at the NASA MSFC

NASA Technical Reports Server (NTRS)

Jones, Gregg; Protz, Christopher; Trinh, Huu; Tucker, Kevin; Nesman, Tomas; Hulka, James

2005-01-01

To support the NASA Space Exploration Mission, an in-house program called Combustion Devices Injector Technology (CDIT) is being conducted at the NASA Marshall Space Flight Center (MSFC) for the fiscal year 2005. CDIT is focused on developing combustor technology and analysis tools to improve reliability and durability of upper-stage and in-space liquid propellant rocket engines. The three areas of focus include injector/chamber thermal compatibility, ignition, and combustion stability. In the compatibility and ignition areas, small-scale single- and multi-element hardware experiments will be conducted to demonstrate advanced technological concepts as well as to provide experimental data for validation of computational analysis tools. In addition, advanced analysis tools will be developed to eventually include 3-dimensional and multi- element effects and improve capability and validity to analyze heat transfer and ignition in large, multi-element injectors.

A Multi-Dimensional Instrument for Evaluating Taiwanese High School Students' Science Learning Self-Efficacy in Relation to Their Approaches to Learning Science

ERIC Educational Resources Information Center

Lin, Tzung-Jin; Tsai, Chin-Chung

2013-01-01

In the past, students' science learning self-efficacy (SLSE) was usually measured by questionnaires that consisted of only a single scale, which might be insufficient to fully understand their SLSE. In this study, a multi-dimensional instrument, the SLSE instrument, was developed and validated to assess students' SLSE based on the previous…

A revised Thai Multi-Dimensional Scale of Perceived Social Support.

PubMed

Wongpakaran, Nahathai; Wongpakaran, Tinakon

2012-11-01

In order to ensure the construct validity of the three-factor model of the Multi-dimensional Scale of Perceived Social Support (MSPSS), and based on the assumption that it helps users differentiate between sources of social support, in this study a revised version was created and tested. The aim was to compare the level of model fit of the original version of the MSPSS against the revised version--which contains a minor change from the original. The study was conducted on 486 medical students who completed the original and revised versions of the MSPSS, as well as the Rosenberg Self-Esteem Scale (Rosenberg, 1965) and Beck Depression Inventory II (Beck, Steer, & Brown, 1996). Confirmatory factor analysis was performed to compare the results, showing that the revised version of MSPSS demonstrated a good internal consistency--with a Cronbach's alpha of .92 for the MSPSS questionnaire, and a significant correlation with the other scales, as predicted. The revised version provided better internal consistency, increasing the Cronbach's alpha for the Significant Others sub-scale from 0.86 to 0.92. Confirmatory factor analysis revealed an acceptable model fit: chi2 128.11, df 51, p < .001; TLI 0.94; CFI 0.95; GFI 0.90; PNFI 0.71; AGFI 0.85; RMSEA 0.093 (0.073-0.113) and SRMR 0.042, which is better than the original version. The tendency of the new version was to display a better level of fit with a larger sample size. The limitations of the study are discussed, as well as recommendations for further study.

Finite Volume Numerical Methods for Aeroheating Rate Calculations from Infrared Thermographic Data

NASA Technical Reports Server (NTRS)

Daryabeigi, Kamran; Berry, Scott A.; Horvath, Thomas J.; Nowak, Robert J.

2006-01-01

The use of multi-dimensional finite volume heat conduction techniques for calculating aeroheating rates from measured global surface temperatures on hypersonic wind tunnel models was investigated. Both direct and inverse finite volume techniques were investigated and compared with the standard one-dimensional semi-infinite technique. Global transient surface temperatures were measured using an infrared thermographic technique on a 0.333-scale model of the Hyper-X forebody in the NASA Langley Research Center 20-Inch Mach 6 Air tunnel. In these tests the effectiveness of vortices generated via gas injection for initiating hypersonic transition on the Hyper-X forebody was investigated. An array of streamwise-orientated heating striations was generated and visualized downstream of the gas injection sites. In regions without significant spatial temperature gradients, one-dimensional techniques provided accurate aeroheating rates. In regions with sharp temperature gradients caused by striation patterns multi-dimensional heat transfer techniques were necessary to obtain more accurate heating rates. The use of the one-dimensional technique resulted in differences of 20% in the calculated heating rates compared to 2-D analysis because it did not account for lateral heat conduction in the model.

SOMAR-LES: A framework for multi-scale modeling of turbulent stratified oceanic flows

NASA Astrophysics Data System (ADS)

Chalamalla, Vamsi K.; Santilli, Edward; Scotti, Alberto; Jalali, Masoud; Sarkar, Sutanu

2017-12-01

A new multi-scale modeling technique, SOMAR-LES, is presented in this paper. Localized grid refinement gives SOMAR (the Stratified Ocean Model with Adaptive Resolution) access to small scales of the flow which are normally inaccessible to general circulation models (GCMs). SOMAR-LES drives a LES (Large Eddy Simulation) on SOMAR's finest grids, forced with large scale forcing from the coarser grids. Three-dimensional simulations of internal tide generation, propagation and scattering are performed to demonstrate this multi-scale modeling technique. In the case of internal tide generation at a two-dimensional bathymetry, SOMAR-LES is able to balance the baroclinic energy budget and accurately model turbulence losses at only 10% of the computational cost required by a non-adaptive solver running at SOMAR-LES's fine grid resolution. This relative cost is significantly reduced in situations with intermittent turbulence or where the location of the turbulence is not known a priori because SOMAR-LES does not require persistent, global, high resolution. To illustrate this point, we consider a three-dimensional bathymetry with grids adaptively refined along the tidally generated internal waves to capture remote mixing in regions of wave focusing. The computational cost in this case is found to be nearly 25 times smaller than that of a non-adaptive solver at comparable resolution. In the final test case, we consider the scattering of a mode-1 internal wave at an isolated two-dimensional and three-dimensional topography, and we compare the results with Legg (2014) numerical experiments. We find good agreement with theoretical estimates. SOMAR-LES is less dissipative than the closure scheme employed by Legg (2014) near the bathymetry. Depending on the flow configuration and resolution employed, a reduction of more than an order of magnitude in computational costs is expected, relative to traditional existing solvers.

Coupled multi-disciplinary simulation of composite engine structures in propulsion environment

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Singhal, Surendra N.

1992-01-01

A computational simulation procedure is described for the coupled response of multi-layered multi-material composite engine structural components which are subjected to simultaneous multi-disciplinary thermal, structural, vibration, and acoustic loadings including the effect of hostile environments. The simulation is based on a three dimensional finite element analysis technique in conjunction with structural mechanics codes and with acoustic analysis methods. The composite material behavior is assessed at the various composite scales, i.e., the laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization model. Sample cases exhibiting nonlinear geometrical, material, loading, and environmental behavior of aircraft engine fan blades, are presented. Results for deformed shape, vibration frequency, mode shapes, and acoustic noise emitted from the fan blade, are discussed for their coupled effect in hot and humid environments. Results such as acoustic noise for coupled composite-mechanics/heat transfer/structural/vibration/acoustic analyses demonstrate the effectiveness of coupled multi-disciplinary computational simulation and the various advantages of composite materials compared to metals.

The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, Robert A.; Gaffney, Richard L., Jr.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

The Art of Extracting One-Dimensional Flow Properties from Multi-Dimensional Data Sets

NASA Technical Reports Server (NTRS)

Baurle, R. A.; Gaffney, R. L.

2007-01-01

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e:g: thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

Exaggeration and suppression of iridescence: the evolution of two-dimensional butterfly structural colours

PubMed Central

Wickham, Shelley; Large, Maryanne C.J; Poladian, Leon; Jermiin, Lars S

2005-01-01

Many butterfly species possess ‘structural’ colour, where colour is due to optical microstructures found in the wing scales. A number of such structures have been identified in butterfly scales, including three variations on a simple multi-layer structure. In this study, we optically characterize examples of all three types of multi-layer structure, as found in 10 species. The optical mechanism of the suppression and exaggeration of the angle-dependent optical properties (iridescence) of these structures is described. In addition, we consider the phylogeny of the butterflies, and are thus able to relate the optical properties of the structures to their evolutionary development. By applying two different types of analysis, the mechanism of adaptation is addressed. A simple parsimony analysis, in which all evolutionary changes are given an equal weighting, suggests convergent evolution of one structure. A Dollo parsimony analysis, in which the evolutionary ‘cost’ of losing a structure is less than that of gaining it, implies that ‘latent’ structures can be reused. PMID:16849221

Three-dimensional Crustal Structure beneath the Tibetan Plateau Revealed by Multi-scale Gravity Analysis

NASA Astrophysics Data System (ADS)

Xu, C.; Luo, Z.; Sun, R.; Li, Q.

2017-12-01

The Tibetan Plateau, the largest and highest plateau on Earth, was uplifted, shorten and thicken by the collision and continuous convergence of the Indian and Eurasian plates since 50 million years ago, the Eocene epoch. Fine three-dimensional crustal structure of the Tibetan Plateau is helpful in understanding the tectonic development. At present, the ordinary method used for revealing crustal structure is seismic method, which is inhibited by poor seismic station coverage, especially in the central and western plateau primarily due to the rugged terrain. Fortunately, with the implementation of satellite gravity missions, gravity field models have demonstrated unprecedented global-scale accuracy and spatial resolution, which can subsequently be employed to study the crustal structure of the entire Tibetan Plateau. This study inverts three-dimensional crustal density and Moho topography of the Tibetan Plateau from gravity data using multi-scale gravity analysis. The inverted results are in agreement with those provided by the previous works. Besides, they can reveal rich tectonic development of the Tibetan Plateau: (1) The low-density channel flow can be observed from the inverted crustal density; (2) The Moho depth in the west is deeper than that in the east, and the deepest Moho, which is approximately 77 km, is located beneath the western Qiangtang Block; (3) The Moho fold, the directions of which are in agreement with the results of surface movement velocities estimated from Global Positioning System, exists clearly on the Moho topography.This study is supported by the National Natural Science Foundation of China (Grant No. 41504015), the China Postdoctoral Science Foundation (Grant No. 2015M572146), and the Surveying and Mapping Basic Research Programme of the National Administration of Surveying, Mapping and Geoinformation (Grant No. 15-01-08).

Accelerating three-dimensional FDTD calculations on GPU clusters for electromagnetic field simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2012-01-01

Electromagnetic simulation with anatomically realistic computational human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the computational human model, we adapt three-dimensional FDTD code to a multi-GPU cluster environment with Compute Unified Device Architecture and Message Passing Interface. Our multi-GPU cluster system consists of three nodes. The seven GPU boards (NVIDIA Tesla C2070) are mounted on each node. We examined the performance of the FDTD calculation on multi-GPU cluster environment. We confirmed that the FDTD calculation on the multi-GPU clusters is faster than that on a multi-GPU (a single workstation), and we also found that the GPU cluster system calculate faster than a vector supercomputer. In addition, our GPU cluster system allowed us to perform the large-scale FDTD calculation because were able to use GPU memory of over 100 GB.

FAST: A multi-processed environment for visualization of computational fluid dynamics

NASA Technical Reports Server (NTRS)

Bancroft, Gordon V.; Merritt, Fergus J.; Plessel, Todd C.; Kelaita, Paul G.; Mccabe, R. Kevin

1991-01-01

Three-dimensional, unsteady, multi-zoned fluid dynamics simulations over full scale aircraft are typical of the problems being investigated at NASA Ames' Numerical Aerodynamic Simulation (NAS) facility on CRAY2 and CRAY-YMP supercomputers. With multiple processor workstations available in the 10-30 Mflop range, we feel that these new developments in scientific computing warrant a new approach to the design and implementation of analysis tools. These larger, more complex problems create a need for new visualization techniques not possible with the existing software or systems available as of this writing. The visualization techniques will change as the supercomputing environment, and hence the scientific methods employed, evolves even further. The Flow Analysis Software Toolkit (FAST), an implementation of a software system for fluid mechanics analysis, is discussed.

Method of multi-dimensional moment analysis for the characterization of signal peaks

DOEpatents

Pfeifer, Kent B; Yelton, William G; Kerr, Dayle R; Bouchier, Francis A

2012-10-23

A method of multi-dimensional moment analysis for the characterization of signal peaks can be used to optimize the operation of an analytical system. With a two-dimensional Peclet analysis, the quality and signal fidelity of peaks in a two-dimensional experimental space can be analyzed and scored. This method is particularly useful in determining optimum operational parameters for an analytical system which requires the automated analysis of large numbers of analyte data peaks. For example, the method can be used to optimize analytical systems including an ion mobility spectrometer that uses a temperature stepped desorption technique for the detection of explosive mixtures.

Multi-dimensional modelling of gas turbine combustion using a flame sheet model in KIVA II

NASA Technical Reports Server (NTRS)

Cheng, W. K.; Lai, M.-C.; Chue, T.-H.

1991-01-01

A flame sheet model for heat release is incorporated into a multi-dimensional fluid mechanical simulation for gas turbine application. The model assumes that the chemical reaction takes place in thin sheets compared to the length scale of mixing, which is valid for the primary combustion zone in a gas turbine combustor. In this paper, the details of the model are described and computational results are discussed.

Enhanced multi-protocol analysis via intelligent supervised embedding (EMPrAvISE): detecting prostate cancer on multi-parametric MRI

NASA Astrophysics Data System (ADS)

Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant

2011-03-01

Currently, there is significant interest in developing methods for quantitative integration of multi-parametric (structural, functional) imaging data with the objective of building automated meta-classifiers to improve disease detection, diagnosis, and prognosis. Such techniques are required to address the differences in dimensionalities and scales of individual protocols, while deriving an integrated multi-parametric data representation which best captures all disease-pertinent information available. In this paper, we present a scheme called Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE); a powerful, generalizable framework applicable to a variety of domains for multi-parametric data representation and fusion. Our scheme utilizes an ensemble of embeddings (via dimensionality reduction, DR); thereby exploiting the variance amongst multiple uncorrelated embeddings in a manner similar to ensemble classifier schemes (e.g. Bagging, Boosting). We apply this framework to the problem of prostate cancer (CaP) detection on 12 3 Tesla pre-operative in vivo multi-parametric (T2-weighted, Dynamic Contrast Enhanced, and Diffusion-weighted) magnetic resonance imaging (MRI) studies, in turn comprising a total of 39 2D planar MR images. We first align the different imaging protocols via automated image registration, followed by quantification of image attributes from individual protocols. Multiple embeddings are generated from the resultant high-dimensional feature space which are then combined intelligently to yield a single stable solution. Our scheme is employed in conjunction with graph embedding (for DR) and probabilistic boosting trees (PBTs) to detect CaP on multi-parametric MRI. Finally, a probabilistic pairwise Markov Random Field algorithm is used to apply spatial constraints to the result of the PBT classifier, yielding a per-voxel classification of CaP presence. Per-voxel evaluation of detection results against ground truth for CaP extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).

Establishing a coherent and replicable measurement model of the Edinburgh Postnatal Depression Scale.

PubMed

Martin, Colin R; Redshaw, Maggie

2018-06-01

The 10-item Edinburgh Postnatal Depression Scale (EPDS) is an established screening tool for postnatal depression. Inconsistent findings in factor structure and replication difficulties have limited the scope of development of the measure as a multi-dimensional tool. The current investigation sought to robustly determine the underlying factor structure of the EPDS and the replicability and stability of the most plausible model identified. A between-subjects design was used. EPDS data were collected postpartum from two independent cohorts using identical data capture methods. Datasets were examined with confirmatory factor analysis, model invariance testing and systematic evaluation of relational and internal aspects of the measure. Participants were two samples of postpartum women in England assessed at three months (n = 245) and six months (n = 217). The findings showed a three-factor seven-item model of the EPDS offered an excellent fit to the data, and was observed to be replicable in both datasets and invariant as a function of time point of assessment. Some EPDS sub-scale scores were significantly higher at six months. The EPDS is multi-dimensional and a robust measurement model comprises three factors that are replicable. The potential utility of the sub-scale components identified requires further research to identify a role in contemporary screening practice. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Automatic deformable diffusion tensor registration for fiber population analysis.

PubMed

Irfanoglu, M O; Machiraju, R; Sammet, S; Pierpaoli, C; Knopp, M V

2008-01-01

In this work, we propose a novel method for deformable tensor-to-tensor registration of Diffusion Tensor Images. Our registration method models the distances in between the tensors with Geode-sic-Loxodromes and employs a version of Multi-Dimensional Scaling (MDS) algorithm to unfold the manifold described with this metric. Defining the same shape properties as tensors, the vector images obtained through MDS are fed into a multi-step vector-image registration scheme and the resulting deformation fields are used to reorient the tensor fields. Results on brain DTI indicate that the proposed method is very suitable for deformable fiber-to-fiber correspondence and DTI-atlas construction.

A tool for multi-scale modelling of the renal nephron

PubMed Central

Nickerson, David P.; Terkildsen, Jonna R.; Hamilton, Kirk L.; Hunter, Peter J.

2011-01-01

We present the development of a tool, which provides users with the ability to visualize and interact with a comprehensive description of a multi-scale model of the renal nephron. A one-dimensional anatomical model of the nephron has been created and is used for visualization and modelling of tubule transport in various nephron anatomical segments. Mathematical models of nephron segments are embedded in the one-dimensional model. At the cellular level, these segment models use models encoded in CellML to describe cellular and subcellular transport kinetics. A web-based presentation environment has been developed that allows the user to visualize and navigate through the multi-scale nephron model, including simulation results, at the different spatial scales encompassed by the model description. The Zinc extension to Firefox is used to provide an interactive three-dimensional view of the tubule model and the native Firefox rendering of scalable vector graphics is used to present schematic diagrams for cellular and subcellular scale models. The model viewer is embedded in a web page that dynamically presents content based on user input. For example, when viewing the whole nephron model, the user might be presented with information on the various embedded segment models as they select them in the three-dimensional model view. Alternatively, the user chooses to focus the model viewer on a cellular model located in a particular nephron segment in order to view the various membrane transport proteins. Selecting a specific protein may then present the user with a description of the mathematical model governing the behaviour of that protein—including the mathematical model itself and various simulation experiments used to validate the model against the literature. PMID:22670210

Preliminary results on the fracture analysis of multi-site cracking of lap joints in aircraft skins

NASA Astrophysics Data System (ADS)

Beuth, J. L., Jr.; Hutchinson, John W.

1992-07-01

Results of a fracture mechanics analysis relevant to fatigue crack growth at rivets in lap joints of aircraft skins are presented. Multi-site damage (MSD) is receiving increased attention within the context of problems of aging aircraft. Fracture analyses previously carried out include small-scale modeling of rivet/skin interactions, larger-scale two-dimensional models of lap joints similar to that developed here, and full scale three-dimensional models of large portions of the aircraft fuselage. Fatigue testing efforts have included flat coupon specimens, two-dimensional lap joint tests, and full scale tests on specimens designed to closely duplicate aircraft sections. Most of this work is documented in the proceedings of previous symposia on the aging aircraft problem. The effect MSD has on the ability of skin stiffeners to arrest the growth of long skin cracks is a particularly important topic that remains to be addressed. One of the most striking features of MSD observed in joints of some test sections and in the joints of some of the older aircraft fuselages is the relative uniformity of the fatigue cracks from rivet to rivet along an extended row of rivets. This regularity suggests that nucleation of the cracks must not be overly difficult. Moreover, it indicates that there is some mechanism which keeps longer cracks from running away from shorter ones, or, equivalently, a mechanism for shorter cracks to catch-up with longer cracks. This basic mechanism has not been identified, and one of the objectives of the work is to see to what extent the mechanism is revealed by a fracture analysis of the MSD cracks. Another related aim is to present accurate stress intensity factor variations with crack length which can be used to estimate fatigue crack growth lifetimes once cracks have been initiated. Results are presented which illustrate the influence of load shedding from rivets with long cracks to neighboring rivets with shorter cracks. Results are also included for the effect of residual stress due to the riveting process itself.

Preliminary results on the fracture analysis of multi-site cracking of lap joints in aircraft skins

NASA Technical Reports Server (NTRS)

Beuth, J. L., Jr.; Hutchinson, John W.

1992-01-01

Results of a fracture mechanics analysis relevant to fatigue crack growth at rivets in lap joints of aircraft skins are presented. Multi-site damage (MSD) is receiving increased attention within the context of problems of aging aircraft. Fracture analyses previously carried out include small-scale modeling of rivet/skin interactions, larger-scale two-dimensional models of lap joints similar to that developed here, and full scale three-dimensional models of large portions of the aircraft fuselage. Fatigue testing efforts have included flat coupon specimens, two-dimensional lap joint tests, and full scale tests on specimens designed to closely duplicate aircraft sections. Most of this work is documented in the proceedings of previous symposia on the aging aircraft problem. The effect MSD has on the ability of skin stiffeners to arrest the growth of long skin cracks is a particularly important topic that remains to be addressed. One of the most striking features of MSD observed in joints of some test sections and in the joints of some of the older aircraft fuselages is the relative uniformity of the fatigue cracks from rivet to rivet along an extended row of rivets. This regularity suggests that nucleation of the cracks must not be overly difficult. Moreover, it indicates that there is some mechanism which keeps longer cracks from running away from shorter ones, or, equivalently, a mechanism for shorter cracks to catch-up with longer cracks. This basic mechanism has not been identified, and one of the objectives of the work is to see to what extent the mechanism is revealed by a fracture analysis of the MSD cracks. Another related aim is to present accurate stress intensity factor variations with crack length which can be used to estimate fatigue crack growth lifetimes once cracks have been initiated. Results are presented which illustrate the influence of load shedding from rivets with long cracks to neighboring rivets with shorter cracks. Results are also included for the effect of residual stress due to the riveting process itself.

Application of the Geophysical Scale Multi-Block Transport Modeling System to Hydrodynamic Forcing of Dredged Material Placement Sediment Transport within the James River Estuary

NASA Astrophysics Data System (ADS)

Kim, S. C.; Hayter, E. J.; Pruhs, R.; Luong, P.; Lackey, T. C.

2016-12-01

The geophysical scale circulation of the Mid Atlantic Bight and hydrologic inputs from adjacent Chesapeake Bay watersheds and tributaries influences the hydrodynamics and transport of the James River estuary. Both barotropic and baroclinic transport govern the hydrodynamics of this partially stratified estuary. Modeling the placement of dredged sediment requires accommodating this wide spectrum of atmospheric and hydrodynamic scales. The Geophysical Scale Multi-Block (GSMB) Transport Modeling System is a collection of multiple well established and USACE approved process models. Taking advantage of the parallel computing capability of multi-block modeling, we performed one year three-dimensional modeling of hydrodynamics in supporting simulation of dredged sediment placements transport and morphology changes. Model forcing includes spatially and temporally varying meteorological conditions and hydrological inputs from the watershed. Surface heat flux estimates were derived from the National Solar Radiation Database (NSRDB). The open water boundary condition for water level was obtained from an ADCIRC model application of the U. S. East Coast. Temperature-salinity boundary conditions were obtained from the Environmental Protection Agency (EPA) Chesapeake Bay Program (CBP) long-term monitoring stations database. Simulated water levels were calibrated and verified by comparison with National Oceanic and Atmospheric Administration (NOAA) tide gage locations. A harmonic analysis of the modeled tides was performed and compared with NOAA tide prediction data. In addition, project specific circulation was verified using US Army Corps of Engineers (USACE) drogue data. Salinity and temperature transport was verified at seven CBP long term monitoring stations along the navigation channel. Simulation and analysis of model results suggest that GSMB is capable of resolving the long duration, multi-scale processes inherent to practical engineering problems such as dredged material placement stability.

Multi-Scale Behavioral Modeling and Analysis Promoting a Fundamental Understanding of Agent-Based System Design and Operation

DTIC Science & Technology

2007-03-01

Chains," Mathematics of Control, Signals, and Systems, vol. 3(1), pp. 1-29, 1990. [4] A . Arnold, J . A . Carrillo, and I. Gamba, "Low and High Field...Aronson, C. L. A ., and J . L. Vázquez, "Interfaces with a corner point in one- dimensional porous medium flow," Comm. Pure Appl. Math, vol. 38(4), pp. 375...K. Levin, "Damage analysis of fiber composites," Computer Methods in Applied Mechanics and Engineering. [10] K. S. Barber, A . Goel, T. J . Graser, T

Statistical analysis of dispersion relations in turbulent solar wind fluctuations using Cluster data

NASA Astrophysics Data System (ADS)

Perschke, C.; Narita, Y.

2012-12-01

Multi-spacecraft measurements enable us to resolve three-dimensional spatial structures without assuming Taylor's frozen-in-flow hypothesis. This is very useful to study frequency-wave vector diagram in solar wind turbulence through direct determination of three-dimensional wave vectors. The existence and evolution of dispersion relation and its role in fully-developed plasma turbulence have been drawing attention of physicists, in particular, if solar wind turbulence represents kinetic Alfvén or whistler mode as the carrier of spectral energy among different scales through wave-wave interactions. We investigate solar wind intervals of Cluster data for various flow velocities with a high-resolution wave vector analysis method, Multi-point Signal Resonator technique, at the tetrahedral separation about 100 km. Magnetic field data and ion data are used to determine the frequency- wave vector diagrams in the co-moving frame of the solar wind. We find primarily perpendicular wave vectors in solar wind turbulence which justify the earlier discussions about kinetic Alfvén or whistler wave. The frequency- wave vector diagrams confirm (a) wave vector anisotropy and (b) scattering in frequencies.

Adjoint Methods for Adjusting Three-Dimensional Atmosphere and Surface Properties to Fit Multi-Angle Multi-Pixel Polarimetric Measurements

NASA Technical Reports Server (NTRS)

Martin, William G.; Cairns, Brian; Bal, Guillaume

2014-01-01

This paper derives an efficient procedure for using the three-dimensional (3D) vector radiative transfer equation (VRTE) to adjust atmosphere and surface properties and improve their fit with multi-angle/multi-pixel radiometric and polarimetric measurements of scattered sunlight. The proposed adjoint method uses the 3D VRTE to compute the measurement misfit function and the adjoint 3D VRTE to compute its gradient with respect to all unknown parameters. In the remote sensing problems of interest, the scalar-valued misfit function quantifies agreement with data as a function of atmosphere and surface properties, and its gradient guides the search through this parameter space. Remote sensing of the atmosphere and surface in a three-dimensional region may require thousands of unknown parameters and millions of data points. Many approaches would require calls to the 3D VRTE solver in proportion to the number of unknown parameters or measurements. To avoid this issue of scale, we focus on computing the gradient of the misfit function as an alternative to the Jacobian of the measurement operator. The resulting adjoint method provides a way to adjust 3D atmosphere and surface properties with only two calls to the 3D VRTE solver for each spectral channel, regardless of the number of retrieval parameters, measurement view angles or pixels. This gives a procedure for adjusting atmosphere and surface parameters that will scale to the large problems of 3D remote sensing. For certain types of multi-angle/multi-pixel polarimetric measurements, this encourages the development of a new class of three-dimensional retrieval algorithms with more flexible parametrizations of spatial heterogeneity, less reliance on data screening procedures, and improved coverage in terms of the resolved physical processes in the Earth?s atmosphere.

A Integrated Service Platform for Remote Sensing Image 3D Interpretation and Draughting based on HTML5

NASA Astrophysics Data System (ADS)

LIU, Yiping; XU, Qing; ZhANG, Heng; LV, Liang; LU, Wanjie; WANG, Dandi

2016-11-01

The purpose of this paper is to solve the problems of the traditional single system for interpretation and draughting such as inconsistent standards, single function, dependence on plug-ins, closed system and low integration level. On the basis of the comprehensive analysis of the target elements composition, map representation and similar system features, a 3D interpretation and draughting integrated service platform for multi-source, multi-scale and multi-resolution geospatial objects is established based on HTML5 and WebGL, which not only integrates object recognition, access, retrieval, three-dimensional display and test evaluation but also achieves collection, transfer, storage, refreshing and maintenance of data about Geospatial Objects and shows value in certain prospects and potential for growth.

The Development and Validation of a Scale Measuring Teacher Autonomous Behaviour

ERIC Educational Resources Information Center

Evers, Arnoud T.; Verboon, Peter; Klaeijsen, Andrea

2017-01-01

In the current study a multi-dimensional scale that measures teacher autonomous behaviour is presented. The scale is applicable across the following educational sectors: primary education, secondary education and vocational education. Based on an elaborate literature study, four theoretically relevant dimensions of teacher autonomous behaviour…

Multi-atlas learner fusion: An efficient segmentation approach for large-scale data.

PubMed

Asman, Andrew J; Huo, Yuankai; Plassard, Andrew J; Landman, Bennett A

2015-12-01

We propose multi-atlas learner fusion (MLF), a framework for rapidly and accurately replicating the highly accurate, yet computationally expensive, multi-atlas segmentation framework based on fusing local learners. In the largest whole-brain multi-atlas study yet reported, multi-atlas segmentations are estimated for a training set of 3464 MR brain images. Using these multi-atlas estimates we (1) estimate a low-dimensional representation for selecting locally appropriate example images, and (2) build AdaBoost learners that map a weak initial segmentation to the multi-atlas segmentation result. Thus, to segment a new target image we project the image into the low-dimensional space, construct a weak initial segmentation, and fuse the trained, locally selected, learners. The MLF framework cuts the runtime on a modern computer from 36 h down to 3-8 min - a 270× speedup - by completely bypassing the need for deformable atlas-target registrations. Additionally, we (1) describe a technique for optimizing the weak initial segmentation and the AdaBoost learning parameters, (2) quantify the ability to replicate the multi-atlas result with mean accuracies approaching the multi-atlas intra-subject reproducibility on a testing set of 380 images, (3) demonstrate significant increases in the reproducibility of intra-subject segmentations when compared to a state-of-the-art multi-atlas framework on a separate reproducibility dataset, (4) show that under the MLF framework the large-scale data model significantly improve the segmentation over the small-scale model under the MLF framework, and (5) indicate that the MLF framework has comparable performance as state-of-the-art multi-atlas segmentation algorithms without using non-local information. Copyright © 2015 Elsevier B.V. All rights reserved.

Development and psychometric pilot-testing of a questionnaire for the evaluation of satisfaction with continuing education in infection control nurses.

PubMed

Meng, Michael; Peter, Daniel; Mattner, Frauke; Igel, Christoph; Kugler, Christiane

2018-05-16

Satisfaction with continuing education can be defined as positive attitudes towards educational programs, which has potential to strengthen learning outcomes. A multi-dimensional construct may enhance continuing education program evaluation processes. The objective is to describe the development and psychometric testing of the 'affective - behavioral - cognitive - satisfaction questionnaire' (ABC-SAT) for assessing participants' satisfaction with a continuing education program for nurses in infection control. The multi-staged development of a satisfaction questionnaire comprised of three subscales. The pilot tool was administered to a nationwide sample of 126 infection control nurses to assess satisfaction after participating in a continuing education program. Satisfaction scores were calculated and psychometric testing was performed to determine reliability, using Cronbach's alpha, face validity, objectivity, and economy. A principle component analysis using varimax rotation and Kaiser normalization was performed. The analysis led to a three-factor solution of the questionnaire with 11 items, explaining 61.4% of the variance. Internal consistency of three scales using Cronbach's alpha was 0.83, 0.60, and 0.66, respectively. Selectivity coefficients varied between 0.39 and 0.70. Participants needed approximately three minutes to complete the questionnaire. Initial findings refer to a satisfying scale structure and internal consistency of the 3-dimensional ABC-SAT questionnaire. Further research is required to confirm the questionnaires' psychometric properties. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Research on non-rigid registration of multi-modal medical image based on Demons algorithm].

PubMed

Hao, Peibo; Chen, Zhen; Jiang, Shaofeng; Wang, Yang

2014-02-01

Non-rigid medical image registration is a popular subject in the research areas of the medical image and has an important clinical value. In this paper we put forward an improved algorithm of Demons, together with the conservation of gray model and local structure tensor conservation model, to construct a new energy function processing multi-modal registration problem. We then applied the L-BFGS algorithm to optimize the energy function and solve complex three-dimensional data optimization problem. And finally we used the multi-scale hierarchical refinement ideas to solve large deformation registration. The experimental results showed that the proposed algorithm for large de formation and multi-modal three-dimensional medical image registration had good effects.

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Efficient High Order Central Schemes for Multi-Dimensional Hamilton-Jacobi Equations: Talk Slides

NASA Technical Reports Server (NTRS)

Bryson, Steve; Levy, Doron; Biegel, Brian R. (Technical Monitor)

2002-01-01

This viewgraph presentation presents information on the attempt to produce high-order, efficient, central methods that scale well to high dimension. The central philosophy is that the equations should evolve to the point where the data is smooth. This is accomplished by a cyclic pattern of reconstruction, evolution, and re-projection. One dimensional and two dimensional representational methods are detailed, as well.

Automated Geo/Co-Registration of Multi-Temporal Very-High-Resolution Imagery.

PubMed

Han, Youkyung; Oh, Jaehong

2018-05-17

For time-series analysis using very-high-resolution (VHR) multi-temporal satellite images, both accurate georegistration to the map coordinates and subpixel-level co-registration among the images should be conducted. However, applying well-known matching methods, such as scale-invariant feature transform and speeded up robust features for VHR multi-temporal images, has limitations. First, they cannot be used for matching an optical image to heterogeneous non-optical data for georegistration. Second, they produce a local misalignment induced by differences in acquisition conditions, such as acquisition platform stability, the sensor's off-nadir angle, and relief displacement of the considered scene. Therefore, this study addresses the problem by proposing an automated geo/co-registration framework for full-scene multi-temporal images acquired from a VHR optical satellite sensor. The proposed method comprises two primary steps: (1) a global georegistration process, followed by (2) a fine co-registration process. During the first step, two-dimensional multi-temporal satellite images are matched to three-dimensional topographic maps to assign the map coordinates. During the second step, a local analysis of registration noise pixels extracted between the multi-temporal images that have been mapped to the map coordinates is conducted to extract a large number of well-distributed corresponding points (CPs). The CPs are finally used to construct a non-rigid transformation function that enables minimization of the local misalignment existing among the images. Experiments conducted on five Kompsat-3 full scenes confirmed the effectiveness of the proposed framework, showing that the georegistration performance resulted in an approximately pixel-level accuracy for most of the scenes, and the co-registration performance further improved the results among all combinations of the georegistered Kompsat-3 image pairs by increasing the calculated cross-correlation values.

EXPERIMENTAL INVESTIGATION OF RELATIVE PERMEABILITY UPSCALING FROM THE MICRO-SCALE TO THE MACRO-SCALE

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

JiangTao Cheng; Ping Yu; William Headley

2001-12-01

The principal challenge of upscaling techniques for multi-phase fluid dynamics in porous media is to determine which properties on the micro-scale can be used to predict macroscopic flow and spatial distribution of phases at core- and field-scales. The most notable outcome of recent theories is the identification of interfacial areas per volume for multiple phases as a fundamental parameter that determines much of the multi-phase properties of the porous medium. A formal program of experimental research was begun to directly test upscaling theories in fluid flow through porous media by comparing measurements of relative permeability and capillary-saturation with measurements ofmore » interfacial area per volume. During this reporting period, we have shown experimentally and theoretically that the optical coherence imaging system is optimized for sandstone. The measurement of interfacial area per volume (IAV), capillary pressure and saturation in two dimensional micro-models structures that are statistically similar to real porous media has shown the existence of a unique relationship among these hydraulic parameters. The measurement of interfacial area per volume on a three-dimensional natural sample, i.e., sandstone, has the same length-scale as the values of IAV determined for the two-dimensional micro-models.« less

A morphologically preserved multi-resolution TIN surface modeling and visualization method for virtual globes

NASA Astrophysics Data System (ADS)

Zheng, Xianwei; Xiong, Hanjiang; Gong, Jianya; Yue, Linwei

2017-07-01

Virtual globes play an important role in representing three-dimensional models of the Earth. To extend the functioning of a virtual globe beyond that of a "geobrowser", the accuracy of the geospatial data in the processing and representation should be of special concern for the scientific analysis and evaluation. In this study, we propose a method for the processing of large-scale terrain data for virtual globe visualization and analysis. The proposed method aims to construct a morphologically preserved multi-resolution triangulated irregular network (TIN) pyramid for virtual globes to accurately represent the landscape surface and simultaneously satisfy the demands of applications at different scales. By introducing cartographic principles, the TIN model in each layer is controlled with a data quality standard to formulize its level of detail generation. A point-additive algorithm is used to iteratively construct the multi-resolution TIN pyramid. The extracted landscape features are also incorporated to constrain the TIN structure, thus preserving the basic morphological shapes of the terrain surface at different levels. During the iterative construction process, the TIN in each layer is seamlessly partitioned based on a virtual node structure, and tiled with a global quadtree structure. Finally, an adaptive tessellation approach is adopted to eliminate terrain cracks in the real-time out-of-core spherical terrain rendering. The experiments undertaken in this study confirmed that the proposed method performs well in multi-resolution terrain representation, and produces high-quality underlying data that satisfy the demands of scientific analysis and evaluation.

Multi-GPU accelerated three-dimensional FDTD method for electromagnetic simulation.

PubMed

Nagaoka, Tomoaki; Watanabe, Soichi

2011-01-01

Numerical simulation with a numerical human model using the finite-difference time domain (FDTD) method has recently been performed in a number of fields in biomedical engineering. To improve the method's calculation speed and realize large-scale computing with the numerical human model, we adapt three-dimensional FDTD code to a multi-GPU environment using Compute Unified Device Architecture (CUDA). In this study, we used NVIDIA Tesla C2070 as GPGPU boards. The performance of multi-GPU is evaluated in comparison with that of a single GPU and vector supercomputer. The calculation speed with four GPUs was approximately 3.5 times faster than with a single GPU, and was slightly (approx. 1.3 times) slower than with the supercomputer. Calculation speed of the three-dimensional FDTD method using GPUs can significantly improve with an expanding number of GPUs.

Two-Dimensional Signal Processing, Optical Information Storage and Processing, and Electromagnetic Measurements

DTIC Science & Technology

1994-05-16

analysis of anisotropic grating diffraction, perfor- mance analysis of Givens rotation integrated optical interdigitated-electrode cross- channel Bragg...11. T. R. Gardos and R. M. Mersereau, "FIR filtering on a lattice with periodically deleted samples," Proc. 1991 IEEE Int. Conf. on Acoustics...pp. vol. 1, pp. 301-311, July 1992. 23. T. R. Gardos , K. Nayebi, and R. M. Mersereau, "Time domain analysis of multi- dimensional multi-rate filter

Field scale test of multi-dimensional flow and morphodynamic simulations used for restoration design analysis

USGS Publications Warehouse

McDonald, Richard R.; Nelson, Jonathan M.; Fosness, Ryan L.; Nelson, Peter O.; Constantinescu, George; Garcia, Marcelo H.; Hanes, Dan

2016-01-01

Two- and three-dimensional morphodynamic simulations are becoming common in studies of channel form and process. The performance of these simulations are often validated against measurements from laboratory studies. Collecting channel change information in natural settings for model validation is difficult because it can be expensive and under most channel forming flows the resulting channel change is generally small. Several channel restoration projects designed in part to armor large meanders with several large spurs constructed of wooden piles on the Kootenai River, ID, have resulted in rapid bed elevation change following construction. Monitoring of these restoration projects includes post- restoration (as-built) Digital Elevation Models (DEMs) as well as additional channel surveys following high channel forming flows post-construction. The resulting sequence of measured bathymetry provides excellent validation data for morphodynamic simulations at the reach scale of a real river. In this paper we test the performance a quasi-three-dimensional morphodynamic simulation against the measured elevation change. The resulting simulations predict the pattern of channel change reasonably well but many of the details such as the maximum scour are under predicted.

Decoupling Principle Analysis and Development of a Parallel Three-Dimensional Force Sensor

PubMed Central

Zhao, Yanzhi; Jiao, Leihao; Weng, Dacheng; Zhang, Dan; Zheng, Rencheng

2016-01-01

In the development of the multi-dimensional force sensor, dimension coupling is the ubiquitous factor restricting the improvement of the measurement accuracy. To effectively reduce the influence of dimension coupling on the parallel multi-dimensional force sensor, a novel parallel three-dimensional force sensor is proposed using a mechanical decoupling principle, and the influence of the friction on dimension coupling is effectively reduced by making the friction rolling instead of sliding friction. In this paper, the mathematical model is established by combining with the structure model of the parallel three-dimensional force sensor, and the modeling and analysis of mechanical decoupling are carried out. The coupling degree (ε) of the designed sensor is defined and calculated, and the calculation results show that the mechanical decoupling parallel structure of the sensor possesses good decoupling performance. A prototype of the parallel three-dimensional force sensor was developed, and FEM analysis was carried out. The load calibration and data acquisition experiment system are built, and then calibration experiments were done. According to the calibration experiments, the measurement accuracy is less than 2.86% and the coupling accuracy is less than 3.02%. The experimental results show that the sensor system possesses high measuring accuracy, which provides a basis for the applied research of the parallel multi-dimensional force sensor. PMID:27649194

Spider-web inspired multi-resolution graphene tactile sensor.

PubMed

Liu, Lu; Huang, Yu; Li, Fengyu; Ma, Ying; Li, Wenbo; Su, Meng; Qian, Xin; Ren, Wanjie; Tang, Kanglai; Song, Yanlin

2018-05-08

Multi-dimensional accurate response and smooth signal transmission are critical challenges in the advancement of multi-resolution recognition and complex environment analysis. Inspired by the structure-activity relationship between discrepant microstructures of the spiral and radial threads in a spider web, we designed and printed graphene with porous and densely-packed microstructures to integrate into a multi-resolution graphene tactile sensor. The three-dimensional (3D) porous graphene structure performs multi-dimensional deformation responses. The laminar densely-packed graphene structure contributes excellent conductivity with flexible stability. The spider-web inspired printed pattern inherits orientational and locational kinesis tracking. The multi-structure construction with homo-graphene material can integrate discrepant electronic properties with remarkable flexibility, which will attract enormous attention for electronic skin, wearable devices and human-machine interactions.

The Impact of Learner Characteristics on the Multi-Dimensional Construct of Social Presence

ERIC Educational Resources Information Center

Mykota, David

2017-01-01

This study explored the impact of learner characteristics on the multi-dimensional construct of social presence as measured by the computer-mediated communication questionnaire. Using Multiple Analysis of Variance findings reveal that the number of online courses taken and computer-mediated communication experience significantly affect the…

Detecting the transition to failure: wavelet analysis of multi-scale crack patterns at different confining pressures

NASA Astrophysics Data System (ADS)

Rizzo, R. E.; Healy, D.; Farrell, N. J.

2017-12-01

Numerous laboratory brittle deformation experiments have shown that a rapid transition exists in the behaviour of porous materials under stress: at a certain point, early formed tensile cracks interact and coalesce into a `single' narrow zone, the shear plane, rather than remaining distributed throughout the material. In this work, we present and apply a novel image processing tool which is able to quantify this transition between distributed (`stable') damage accumulation and localised (`unstable') deformation, in terms of size, density, and orientation of cracks at the point of failure. Our technique, based on a two-dimensional (2D) continuous Morlet wavelet analysis, can recognise, extract and visually separate the multi-scale changes occurring in the fracture network during the deformation process. We have analysed high-resolution SEM-BSE images of thin sections of Hopeman Sandstone (Scotland, UK) taken from core plugs deformed under triaxial conditions, with increasing confining pressure. Through this analysis, we can determine the relationship between the initial orientation of tensile microcracks and the final geometry of the through-going shear fault, exploiting the total areal coverage of the analysed image. In addition, by comparing patterns of fractures in thin sections derived from triaxial (σ1>σ2=σ3=Pc) laboratory experiments conducted at different confining pressures (Pc), we can quantitatively explore the relationship between the observed geometry and the inferred mechanical processes. The methodology presented here can have important implications for larger-scale mechanical problems related to major fault propagation. Just as a core plug scale fault localises through extension and coalescence of microcracks, larger faults also grow by extension and coalescence of segments in a multi-scale process by which microscopic cracks can ultimately lead to macroscopic faulting. Consequently, wavelet analysis represents a useful tool for fracture pattern recognition, applicable to the detection of the transitions occurring at the time of catastrophic rupture.

Xray: N-dimensional, labeled arrays for analyzing physical datasets in Python

NASA Astrophysics Data System (ADS)

Hoyer, S.

2015-12-01

Efficient analysis of geophysical datasets requires tools that both preserve and utilize metadata, and that transparently scale to process large datas. Xray is such a tool, in the form of an open source Python library for analyzing the labeled, multi-dimensional array (tensor) datasets that are ubiquitous in the Earth sciences. Xray's approach pairs Python data structures based on the data model of the netCDF file format with the proven design and user interface of pandas, the popular Python data analysis library for labeled tabular data. On top of the NumPy array, xray adds labeled dimensions (e.g., "time") and coordinate values (e.g., "2015-04-10"), which it uses to enable a host of operations powered by these labels: selection, aggregation, alignment, broadcasting, split-apply-combine, interoperability with pandas and serialization to netCDF/HDF5. Many of these operations are enabled by xray's tight integration with pandas. Finally, to allow for easy parallelism and to enable its labeled data operations to scale to datasets that does not fit into memory, xray integrates with the parallel processing library dask.

On Involvement.

ERIC Educational Resources Information Center

Greene, Michael B.

Involvement Ratings In Settings (IRIS), a multi-dimensional non-verbal scale of involvement adaptable to a time-sampling method of data collection, was constructed with the aid of the videotapes of second-grade Follow Through classrooms made by CCEP. Scales were defined through observations of involved and alienated behavior, and the IRIS was…

Teacher Efficacy, Work Engagement, and Social Support Among Chinese Special Education School Teachers

PubMed Central

Minghui, Lu; Lei, Hao; Xiaomeng, Chen; Potměšilc, Miloň

2018-01-01

This paper investigates the relationship between teacher efficacy and socio-demographic factors, work engagement, and social support among Chinese special education school teachers. The sample comprised 1,027 special education school teachers in mainland China. The Teachers’ Sense of Efficacy Scale, the Multi-Dimensional Scale of Perceived Social Support, and the Utrecht Work Engagement Scale were used for data collection. Correlation analysis revealed that social support, work engagement, and teacher efficacy were significantly correlated with each other. Additionally, gender, years of experience, and monthly salary were significant predictors of teacher efficacy. Furthermore, structural equation modeling analysis showed that social support exerted its indirect effect on teacher efficacy through the mediation of work engagement. The findings of this study provide a new perspective on the complex association between social support and teacher efficacy. The explanations and limitations of these findings are discussed. PMID:29867634

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

PubMed Central

Chang, Chi-Ying; Chang, Chia-Chi; Hsiao, Tzu-Chien

2013-01-01

Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD) was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes. PMID:24240806

Design and Analysis of a Formation Flying System for the Cross-Scale Mission Concept

NASA Technical Reports Server (NTRS)

Cornara, Stefania; Bastante, Juan C.; Jubineau, Franck

2007-01-01

The ESA-funded "Cross-Scale Technology Reference Study has been carried out with the primary aim to identify and analyse a mission concept for the investigation of fundamental space plasma processes that involve dynamical non-linear coupling across multiple length scales. To fulfill this scientific mission goal, a constellation of spacecraft is required, flying in loose formations around the Earth and sampling three characteristic plasma scale distances simultaneously, with at least two satellites per scale: electron kinetic (10 km), ion kinetic (100-2000 km), magnetospheric fluid (3000-15000 km). The key Cross-Scale mission drivers identified are the number of S/C, the space segment configuration, the reference orbit design, the transfer and deployment strategy, the inter-satellite localization and synchronization process and the mission operations. This paper presents a comprehensive overview of the mission design and analysis for the Cross-Scale concept and outlines a technically feasible mission architecture for a multi-dimensional investigation of space plasma phenomena. The main effort has been devoted to apply a thorough mission-level trade-off approach and to accomplish an exhaustive analysis, so as to allow the characterization of a wide range of mission requirements and design solutions.

Belief in a Just What? Demystifying Just World Beliefs by Distinguishing Sources of Justice

PubMed Central

Stroebe, Katherine; Postmes, Tom; Täuber, Susanne; Stegeman, Alwin; John, Melissa-Sue

2015-01-01

People’s Belief in a Just World (BJW) plays an important role in coping with misfortune and unfairness. This paper demonstrates that understanding of the BJW concept, and its consequences for behavior, is enhanced if we specify what (or who) the source of justice might be. We introduce a new scale, the 5-Dimensional Belief in a Just Treatment Scale (BJT5), which distinguishes five causal dimensions of BJW (God, Nature, Other People, Self, Chance). We confirm the 5-factor structure of the BJT5. We then address whether the BJW should be considered a uni- and/or multi-dimensional construct and find support for our multi-dimensional approach. Finally, we demonstrate convergent and discriminant validity with respect to important correlates of BJW as well as action in response to important negative life events and societal attitudes. This work illustrates the importance of distinguishing causal dimensions with regard to who distributes justice. PMID:25803025

Three-dimensional distribution of polymorphs and magnesium in a calcified underwater attachment system by diffraction tomography

PubMed Central

Leemreize, Hanna; Almer, Jonathan D.; Stock, Stuart R.; Birkedal, Henrik

2013-01-01

Biological materials display complicated three-dimensional hierarchical structures. Determining these structures is essential in understanding the link between material design and properties. Herein, we show how diffraction tomography can be used to determine the relative placement of the calcium carbonate polymorphs calcite and aragonite in the highly mineralized holdfast system of the bivalve Anomia simplex. In addition to high fidelity and non-destructive mapping of polymorphs, we use detailed analysis of X-ray diffraction peak positions in reconstructed powder diffraction data to determine the local degree of Mg substitution in the calcite phase. These data show how diffraction tomography can provide detailed multi-length scale information on complex materials in general and of biomineralized tissues in particular. PMID:23804437

A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

PubMed

Xue, Xiaoming; Zhou, Jianzhong

2017-01-01

To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Nanofabrication

DOEpatents

Tuominen, Mark; Bal, Mustafa; Russell, Thomas P.; Ursache, Andrei

2007-03-13

Pathways to rapid and reliable fabrication of three-dimensional nanostructures are provided. Simple methods are described for the production of well-ordered, multilevel nanostructures. This is accomplished by patterning block copolymer templates with selective exposure to a radiation source. The resulting multi-scale lithographic template can be treated with post-fabrication steps to produce multilevel, three-dimensional, integrated nanoscale media, devices, and systems.

Dimensionality of Organizational Commitment in Volunteer Workers: Chamber of Commerce Board Members and Role Fulfillment

ERIC Educational Resources Information Center

Dawley, David D.; Stephens, Robert D.; Stephens, David B.

2005-01-01

This study explores the multi-dimensionality of organizational commitment of volunteer chamber of commerce board members using the Meyer and Allen (1997) scale. The effect of organizational commitment on desirable board member roles is also tested. Theory is developed by uniting past research in both organizational commitment and employee…

A Flight Dynamics Model for a Multi-Actuated Flexible Rocket Vehicle

NASA Technical Reports Server (NTRS)

Orr, Jeb S.

2011-01-01

A comprehensive set of motion equations for a multi-actuated flight vehicle is presented. The dynamics are derived from a vector approach that generalizes the classical linear perturbation equations for flexible launch vehicles into a coupled three-dimensional model. The effects of nozzle and aerosurface inertial coupling, sloshing propellant, and elasticity are incorporated without restrictions on the position, orientation, or number of model elements. The present formulation is well suited to matrix implementation for large-scale linear stability and sensitivity analysis and is also shown to be extensible to nonlinear time-domain simulation through the application of a special form of Lagrange s equations in quasi-coordinates. The model is validated through frequency-domain response comparison with a high-fidelity planar implementation.

Quantifying multi-dimensional attributes of human activities at various geographic scales based on smartphone tracking.

PubMed

Zhou, Xiaolu; Li, Dongying

2018-05-09

Advancement in location-aware technologies, and information and communication technology in the past decades has furthered our knowledge of the interaction between human activities and the built environment. An increasing number of studies have collected data regarding individual activities to better understand how the environment shapes human behavior. Despite this growing interest, some challenges exist in collecting and processing individual's activity data, e.g., capturing people's precise environmental contexts and analyzing data at multiple spatial scales. In this study, we propose and implement an innovative system that integrates smartphone-based step tracking with an app and the sequential tile scan techniques to collect and process activity data. We apply the OpenStreetMap tile system to aggregate positioning points at various scales. We also propose duration, step and probability surfaces to quantify the multi-dimensional attributes of activities. Results show that, by running the app in the background, smartphones can measure multi-dimensional attributes of human activities, including space, duration, step, and location uncertainty at various spatial scales. By coordinating Global Positioning System (GPS) sensor with accelerometer sensor, this app can save battery which otherwise would be drained by GPS sensor quickly. Based on a test dataset, we were able to detect the recreational center and sports center as the space where the user was most active, among other places visited. The methods provide techniques to address key issues in analyzing human activity data. The system can support future studies on behavioral and health consequences related to individual's environmental exposure.

The patient satisfaction questionnaire of EUprimecare project: measurement properties.

PubMed

Cimas, Marta; Ayala, Alba; García-Pérez, Sonia; Sarria-Santamera, Antonio; Forjaz, Maria João

2016-06-01

The measurement of patient satisfaction is considered an essential outcome indicator to evaluate health care quality. Patient satisfaction is considered a multi-dimensional construct, which would include a variety of domains. Although a large number of studies have proposed scales to measure patient satisfaction, there is a lack of psychometric information on them. This study aims to describe the psychometric properties of the Primary Care Satisfaction Scale (PCSS) of the EUprimecare project. A cross-sectional survey of patient satisfaction with primary care was carried out by telephone interview. Primary care services of Estonia, Finland, Germany, Hungary, Lithuania, Italy and Spain. A total of 3020 adult patients aged 18-65 years old attending primary care services. Classic psychometric properties were analysed and Rasch analysis was used to assess the following measurement properties: fit to the Rasch model; uni-dimensionality; reliability; differential item functioning (DIF) by gender, age, civil status, area of residency and country; local independency; adequacy of response scale; and scale targeting. To achieve good fit to the Rasch model, the original response scales of three items (1, 2 and 6) were rescored and Item 3 (waiting time in the room) was removed. The scale was uni-dimensional and Person Separation Index was 0.79, indicating a good reliability. All items were free from bias. PCSS linear measure displayed satisfactory convergent validity with overall satisfaction with primary care. PCSS, as a reliable and valid scale, could be used to measure patient satisfaction in primary care in Europe. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

Quantitative Large-Scale Three-Dimensional Imaging of Human Kidney Biopsies: A Bridge to Precision Medicine in Kidney Disease.

PubMed

Winfree, Seth; Dagher, Pierre C; Dunn, Kenneth W; Eadon, Michael T; Ferkowicz, Michael; Barwinska, Daria; Kelly, Katherine J; Sutton, Timothy A; El-Achkar, Tarek M

2018-06-05

Kidney biopsy remains the gold standard for uncovering the pathogenesis of acute and chronic kidney diseases. However, the ability to perform high resolution, quantitative, molecular and cellular interrogation of this precious tissue is still at a developing stage compared to other fields such as oncology. Here, we discuss recent advances in performing large-scale, three-dimensional (3D), multi-fluorescence imaging of kidney biopsies and quantitative analysis referred to as 3D tissue cytometry. This approach allows the accurate measurement of specific cell types and their spatial distribution in a thick section spanning the entire length of the biopsy. By uncovering specific disease signatures, including rare occurrences, and linking them to the biology in situ, this approach will enhance our understanding of disease pathogenesis. Furthermore, by providing accurate quantitation of cellular events, 3D cytometry may improve the accuracy of prognosticating the clinical course and response to therapy. Therefore, large-scale 3D imaging and cytometry of kidney biopsy is poised to become a bridge towards personalized medicine for patients with kidney disease. © 2018 S. Karger AG, Basel.

Multi-dimensional scores to predict mortality in patients with idiopathic pulmonary fibrosis undergoing lung transplantation assessment.

PubMed

Fisher, Jolene H; Al-Hejaili, Faris; Kandel, Sonja; Hirji, Alim; Shapera, Shane; Mura, Marco

2017-04-01

The heterogeneous progression of idiopathic pulmonary fibrosis (IPF) makes prognostication difficult and contributes to high mortality on the waitlist for lung transplantation (LTx). Multi-dimensional scores (Composite Physiologic index [CPI], [Gender-Age-Physiology [GAP]; RIsk Stratification scorE [RISE]) demonstrated enhanced predictive power towards outcome in IPF. The lung allocation score (LAS) is a multi-dimensional tool commonly used to stratify patients assessed for LTx. We sought to investigate whether IPF-specific multi-dimensional scores predict mortality in patients with IPF assessed for LTx. The study included 302 patients with IPF who underwent a LTx assessment (2003-2014). Multi-dimensional scores were calculated. The primary outcome was 12-month mortality after assessment. LTx was considered as competing event in all analyses. At the end of the observation period, there were 134 transplants, 63 deaths, and 105 patients were alive without LTx. Multi-dimensional scores predicted mortality with accuracy similar to LAS, and superior to that of individual variables: area under the curve (AUC) for LAS was 0.78 (sensitivity 71%, specificity 86%); CPI 0.75 (sensitivity 67%, specificity 82%); GAP 0.67 (sensitivity 59%, specificity 74%); RISE 0.78 (sensitivity 71%, specificity 84%). A separate analysis conducted only in patients actively listed for LTx (n = 247; 50 deaths) yielded similar results. In patients with IPF assessed for LTx as well as in those actually listed, multi-dimensional scores predict mortality better than individual variables, and with accuracy similar to the LAS. If validated, multi-dimensional scores may serve as inexpensive tools to guide decisions on the timing of referral and listing for LTx. Copyright © 2017 Elsevier Ltd. All rights reserved.

DEVELOPMENT OF MOTIVATION SCALE - CLINICAL VALIDATION WITH ALCOHOL DEPENDENTS

PubMed Central

Neeliyara, Teresa; Nagalakshmi, S.V.

1994-01-01

This study focusses on the development of a comprehensive multi-dimensional scale for assessing motivation for change in the alcohol dependent population. After establishing face validity, the items evolved were administered to a normal sample of 600 male subjects in whom psychiatric illness was ruled out. The data thus obtained was subjected to factor analysis. Six factors were obtained which accounted for 55.2% of variance. These together formed a 80 item five point scale and norms were established on a sample of 600 normal subjects. Further clinical validation was established on 30 alcohol dependent subjects and 30 normals. The status of motivation was found to be inadequate in alcohol dependent individuals as compared to the normals. Split-half reliability was carried out and the tool was found to be highly reliable. PMID:21743674

Multi-dimensional Fokker-Planck equation analysis using the modified finite element method

NASA Astrophysics Data System (ADS)

Náprstek, J.; Král, R.

2016-09-01

The Fokker-Planck equation (FPE) is a frequently used tool for the solution of cross probability density function (PDF) of a dynamic system response excited by a vector of random processes. FEM represents a very effective solution possibility, particularly when transition processes are investigated or a more detailed solution is needed. Actual papers deal with single degree of freedom (SDOF) systems only. So the respective FPE includes two independent space variables only. Stepping over this limit into MDOF systems a number of specific problems related to a true multi-dimensionality must be overcome. Unlike earlier studies, multi-dimensional simplex elements in any arbitrary dimension should be deployed and rectangular (multi-brick) elements abandoned. Simple closed formulae of integration in multi-dimension domain have been derived. Another specific problem represents the generation of multi-dimensional finite element mesh. Assembling of system global matrices should be subjected to newly composed algorithms due to multi-dimensionality. The system matrices are quite full and no advantages following from their sparse character can be profited from, as is commonly used in conventional FEM applications in 2D/3D problems. After verification of partial algorithms, an illustrative example dealing with a 2DOF non-linear aeroelastic system in combination with random and deterministic excitations is discussed.

Multi-Scale Modeling, Surrogate-Based Analysis, and Optimization of Lithium-Ion Batteries for Vehicle Applications

NASA Astrophysics Data System (ADS)

Du, Wenbo

A common attribute of electric-powered aerospace vehicles and systems such as unmanned aerial vehicles, hybrid- and fully-electric aircraft, and satellites is that their performance is usually limited by the energy density of their batteries. Although lithium-ion batteries offer distinct advantages such as high voltage and low weight over other battery technologies, they are a relatively new development, and thus significant gaps in the understanding of the physical phenomena that govern battery performance remain. As a result of this limited understanding, batteries must often undergo a cumbersome design process involving many manual iterations based on rules of thumb and ad-hoc design principles. A systematic study of the relationship between operational, geometric, morphological, and material-dependent properties and performance metrics such as energy and power density is non-trivial due to the multiphysics, multiphase, and multiscale nature of the battery system. To address these challenges, two numerical frameworks are established in this dissertation: a process for analyzing and optimizing several key design variables using surrogate modeling tools and gradient-based optimizers, and a multi-scale model that incorporates more detailed microstructural information into the computationally efficient but limited macro-homogeneous model. In the surrogate modeling process, multi-dimensional maps for the cell energy density with respect to design variables such as the particle size, ion diffusivity, and electron conductivity of the porous cathode material are created. A combined surrogate- and gradient-based approach is employed to identify optimal values for cathode thickness and porosity under various operating conditions, and quantify the uncertainty in the surrogate model. The performance of multiple cathode materials is also compared by defining dimensionless transport parameters. The multi-scale model makes use of detailed 3-D FEM simulations conducted at the particle-level. A monodisperse system of ellipsoidal particles is used to simulate the effective transport coefficients and interfacial reaction current density within the porous microstructure. Microscopic simulation results are shown to match well with experimental measurements, while differing significantly from homogenization approximations used in the macroscopic model. Global sensitivity analysis and surrogate modeling tools are applied to couple the two length scales and complete the multi-scale model.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

Assessment of Computer and Information Literacy in ICILS 2013: Do Different Item Types Measure the Same Construct?

ERIC Educational Resources Information Center

Ihme, Jan Marten; Senkbeil, Martin; Goldhammer, Frank; Gerick, Julia

2017-01-01

The combination of different item formats is found quite often in large scale assessments, and analyses on the dimensionality often indicate multi-dimensionality of tests regarding the task format. In ICILS 2013, three different item types (information-based response tasks, simulation tasks, and authoring tasks) were used to measure computer and…

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages

DOE PAGES

Carlton, Holly D.; Elmer, John W.; Li, Yan; ...

2016-04-13

For this study synchrotron radiation micro-­tomography, a non-destructive three-dimensional imaging technique, is employed to investigate an entire microelectronic package with a cross-sectional area of 16 x 16 mm. Due to the synchrotron’s high flux and brightness the sample was imaged in just 3 minutes with an 8.7 μm spatial resolution.

The structure of the Hospital Anxiety and Depression Scale in four cohorts of community-based, healthy older people: the HALCyon program.

PubMed

Gale, Catharine R; Allerhand, Michael; Sayer, Avan Aihie; Cooper, Cyrus; Dennison, Elaine M; Starr, John M; Ben-Shlomo, Yoav; Gallacher, John E; Kuh, Diana; Deary, Ian J

2010-06-01

The Hospital Anxiety and Depression Scale (HADS) is widely used but evaluation of its psychometric properties has produced equivocal results. Little is known about its structure in non-clinical samples of older people. We used data from four cohorts in the HALCyon collaborative research program into healthy aging: the Caerphilly Prospective Study, the Hertfordshire Ageing Study, the Hertfordshire Cohort Study, and the Lothian Birth Cohort 1921. We used exploratory factor analysis and confirmatory factor analysis with multi-group comparisons to establish the structure of the HADS and test for factorial invariance between samples. Exploratory factor analysis showed a bi-dimensional structure (anxiety and depression) of the scale in men and women in each cohort. We tested a hypothesized three-factor model but high correlations between two of the factors made a two-factor model more psychologically plausible. Multi-group confirmatory factor analysis revealed that the sizes of the respective item loadings on the two factors were effectively identical in men and women from the same cohort. There was more variation between cohorts, particularly those from different parts of the U.K. and in whom the HADS was administered differently. Differences in social-class distribution accounted for part of this variation. Scoring the HADS as two subscales of anxiety and depression is appropriate in non-clinical populations of older men and women. However, there were differences between cohorts in the way that individual items were linked with the constructs of anxiety and depression, perhaps due to differences in sociocultural factors and/or in the administration of the scale.

Relationships between Organizations and Publics: Development of a Multi-Dimensional Organization-Public Relationship Scale.

ERIC Educational Resources Information Center

Bruning, Stephen D.; Ledingham, John A.

1999-01-01

Attempts to design a multiple-item, multiple-dimension organization/public relationship scale. Finds that organizations and key publics have three types of relationships: professional, personal, and community. Provides an instrument that can be used to measure the influence that perceptions of the organization/public relationship have on consumer…

Statistical Projections for Multi-resolution, Multi-dimensional Visual Data Exploration and Analysis

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

Hoa T. Nguyen; Stone, Daithi; E. Wes Bethel

2016-01-01

An ongoing challenge in visual exploration and analysis of large, multi-dimensional datasets is how to present useful, concise information to a user for some specific visualization tasks. Typical approaches to this problem have proposed either reduced-resolution versions of data, or projections of data, or both. These approaches still have some limitations such as consuming high computation or suffering from errors. In this work, we explore the use of a statistical metric as the basis for both projections and reduced-resolution versions of data, with a particular focus on preserving one key trait in data, namely variation. We use two different casemore » studies to explore this idea, one that uses a synthetic dataset, and another that uses a large ensemble collection produced by an atmospheric modeling code to study long-term changes in global precipitation. The primary findings of our work are that in terms of preserving the variation signal inherent in data, that using a statistical measure more faithfully preserves this key characteristic across both multi-dimensional projections and multi-resolution representations than a methodology based upon averaging.« less

Behavior analysis of video object in complicated background

NASA Astrophysics Data System (ADS)

Zhao, Wenting; Wang, Shigang; Liang, Chao; Wu, Wei; Lu, Yang

2016-10-01

This paper aims to achieve robust behavior recognition of video object in complicated background. Features of the video object are described and modeled according to the depth information of three-dimensional video. Multi-dimensional eigen vector are constructed and used to process high-dimensional data. Stable object tracing in complex scenes can be achieved with multi-feature based behavior analysis, so as to obtain the motion trail. Subsequently, effective behavior recognition of video object is obtained according to the decision criteria. What's more, the real-time of algorithms and accuracy of analysis are both improved greatly. The theory and method on the behavior analysis of video object in reality scenes put forward by this project have broad application prospect and important practical significance in the security, terrorism, military and many other fields.

Multi-Dimensional Shallow Landslide Stability Analysis Suitable for Application at the Watershed Scale

NASA Astrophysics Data System (ADS)

Milledge, David; Bellugi, Dino; McKean, Jim; Dietrich, William E.

2013-04-01

Current practice in regional-scale shallow landslide hazard assessment is to adopt a one-dimensional slope stability representation. Such a representation cannot produce discrete landslides and thus cannot make predictions on landslide size. Furthermore, one-dimensional approaches cannot include lateral effects, which are known to be important in defining instability. Here we derive an alternative model that accounts for lateral resistance by representing the forces acting on each margin of an unstable block of soil. We model boundary frictional resistances using 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure, using the log-spiral method, on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion declines exponentially with soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are relatively well constrained and find that our model predicts failure at the observed location and predicts that larger or smaller failures conformal to the observed shape are indeed more stable. We use a sensitivity analysis of the model to show that lateral reinforcement sets a minimum landslide size, and that the additional strength at the downslope boundary results in optimal shapes that are longer in the downslope direction. However, reinforcement effects alone cannot fully explain the size or shape distributions of observed landslides, highlighting the importance of the spatial pattern of key parameters (e.g. pore water pressure and soil depth) at the watershed scale. The application of the model at this scale requires an efficient method to find unstable shapes among an exponential number of candidates. In this context, the model allows a more extensive examination of the controls on landslide size, shape and location.

Determination of secondary flow morphologies by wavelet analysis in a curved artery model with physiological inflow

NASA Astrophysics Data System (ADS)

Bulusu, Kartik V.; Hussain, Shadman; Plesniak, Michael W.

2014-11-01

Secondary flow vortical patterns in arterial curvatures have the potential to affect several cardiovascular phenomena, e.g., progression of atherosclerosis by altering wall shear stresses, carotid atheromatous disease, thoracic aortic aneurysms and Marfan's syndrome. Temporal characteristics of secondary flow structures vis-à-vis physiological (pulsatile) inflow waveform were explored by continuous wavelet transform (CWT) analysis of phase-locked, two-component, two-dimensional particle image velocimeter data. Measurements were made in a 180° curved artery test section upstream of the curvature and at the 90° cross-sectional plane. Streamwise, upstream flow rate measurements were analyzed using a one-dimensional antisymmetric wavelet. Cross-stream measurements at the 90° location of the curved artery revealed interesting multi-scale, multi-strength coherent secondary flow structures. An automated process for coherent structure detection and vortical feature quantification was applied to large ensembles of PIV data. Metrics such as the number of secondary flow structures, their sizes and strengths were generated at every discrete time instance of the physiological inflow waveform. An autonomous data post-processing method incorporating two-dimensional CWT for coherent structure detection was implemented. Loss of coherence in secondary flow structures during the systolic deceleration phase is observed in accordance with previous research. The algorithmic approach presented herein further elucidated the sensitivity and dependence of morphological changes in secondary flow structures on quasiperiodicity and magnitude of temporal gradients in physiological inflow conditions.

electromagnetics, eddy current, computer codes

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

Gartling, David

TORO Version 4 is designed for finite element analysis of steady, transient and time-harmonic, multi-dimensional, quasi-static problems in electromagnetics. The code allows simulation of electrostatic fields, steady current flows, magnetostatics and eddy current problems in plane or axisymmetric, two-dimensional geometries. TORO is easily coupled to heat conduction and solid mechanics codes to allow multi-physics simulations to be performed.

Poincaré-Treshchev Mechanism in Multi-scale, Nearly Integrable Hamiltonian Systems

NASA Astrophysics Data System (ADS)

Xu, Lu; Li, Yong; Yi, Yingfei

2018-02-01

This paper is a continuation to our work (Xu et al. in Ann Henri Poincaré 18(1):53-83, 2017) concerning the persistence of lower-dimensional tori on resonant surfaces of a multi-scale, nearly integrable Hamiltonian system. This type of systems, being properly degenerate, arise naturally in planar and spatial lunar problems of celestial mechanics for which the persistence problem ties closely to the stability of the systems. For such a system, under certain non-degenerate conditions of Rüssmann type, the majority persistence of non-resonant tori and the existence of a nearly full measure set of Poincaré non-degenerate, lower-dimensional, quasi-periodic invariant tori on a resonant surface corresponding to the highest order of scale is proved in Han et al. (Ann Henri Poincaré 10(8):1419-1436, 2010) and Xu et al. (2017), respectively. In this work, we consider a resonant surface corresponding to any intermediate order of scale and show the existence of a nearly full measure set of Poincaré non-degenerate, lower-dimensional, quasi-periodic invariant tori on the resonant surface. The proof is based on a normal form reduction which consists of a finite step of KAM iterations in pushing the non-integrable perturbation to a sufficiently high order and the splitting of resonant tori on the resonant surface according to the Poincaré-Treshchev mechanism.

Non-classical photon correlation in a two-dimensional photonic lattice.

PubMed

Gao, Jun; Qiao, Lu-Feng; Lin, Xiao-Feng; Jiao, Zhi-Qiang; Feng, Zhen; Zhou, Zheng; Gao, Zhen-Wei; Xu, Xiao-Yun; Chen, Yuan; Tang, Hao; Jin, Xian-Min

2016-06-13

Quantum interference and quantum correlation, as two main features of quantum optics, play an essential role in quantum information applications, such as multi-particle quantum walk and boson sampling. While many experimental demonstrations have been done in one-dimensional waveguide arrays, it remains unexplored in higher dimensions due to tight requirement of manipulating and detecting photons in large-scale. Here, we experimentally observe non-classical correlation of two identical photons in a fully coupled two-dimensional structure, i.e. photonic lattice manufactured by three-dimensional femtosecond laser writing. Photon interference consists of 36 Hong-Ou-Mandel interference and 9 bunching. The overlap between measured and simulated distribution is up to 0.890 ± 0.001. Clear photon correlation is observed in the two-dimensional photonic lattice. Combining with controllably engineered disorder, our results open new perspectives towards large-scale implementation of quantum simulation on integrated photonic chips.

Implementation of Finite Volume based Navier Stokes Algorithm Within General Purpose Flow Network Code

NASA Technical Reports Server (NTRS)

Schallhorn, Paul; Majumdar, Alok

2012-01-01

This paper describes a finite volume based numerical algorithm that allows multi-dimensional computation of fluid flow within a system level network flow analysis. There are several thermo-fluid engineering problems where higher fidelity solutions are needed that are not within the capacity of system level codes. The proposed algorithm will allow NASA's Generalized Fluid System Simulation Program (GFSSP) to perform multi-dimensional flow calculation within the framework of GFSSP s typical system level flow network consisting of fluid nodes and branches. The paper presents several classical two-dimensional fluid dynamics problems that have been solved by GFSSP's multi-dimensional flow solver. The numerical solutions are compared with the analytical and benchmark solution of Poiseulle, Couette and flow in a driven cavity.

Aspects of effective supersymmetric theories

NASA Astrophysics Data System (ADS)

Tziveloglou, Panteleimon

This work consists of two parts. In the first part we construct the complete extension of the Minimal Supersymmetric Standard Model by higher dimensional effective operators and then study its phenomenology. These operators encapsulate the effects on LHC physics of any kind of new degrees of freedom at the multiTeV scale. The effective analysis includes the case where the multiTeV physics is the supersymmetry breaking sector itself. In that case the appropriate framework is nonlinear supersymmetry. We choose to realize the nonlinear symmetry by the method of constrained superfields. Beyond the new effective couplings, the analysis suggests an interpretation of the 'little hierarchy problem' as an indication of new physics at multiTeV scale. In the second part we explore the power of constrained superfields in extended supersymmetry. It is known that in N = 2 supersymmetry the gauge kinetic function cannot depend on hypermultiplet scalars. However, it is also known that the low energy effective action of a D-brane in an N = 2 supersymmetric bulk includes the DBI action, where the gauge kinetic function does depend on the dilaton. We show how the nonlinearization of the second SUSY (imposed by the presence of the D-brane) opens this possibility, by constructing the global N = 1 linear + 1 nonlinear invariant coupling of a hypermultiplet with a gauge multiplet. The constructed theory enjoys interesting features, including a novel super-Higgs mechanism without gravity.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

Upscaling river biomass using dimensional analysis and hydrogeomorphic scaling

NASA Astrophysics Data System (ADS)

Barnes, Elizabeth A.; Power, Mary E.; Foufoula-Georgiou, Efi; Hondzo, Miki; Dietrich, William E.

2007-12-01

We propose a methodology for upscaling biomass in a river using a combination of dimensional analysis and hydro-geomorphologic scaling laws. We first demonstrate the use of dimensional analysis for determining local scaling relationships between Nostoc biomass and hydrologic and geomorphic variables. We then combine these relationships with hydraulic geometry and streamflow scaling in order to upscale biomass from point to reach-averaged quantities. The methodology is demonstrated through an illustrative example using an 18 year dataset of seasonal monitoring of biomass of a stream cyanobacterium (Nostoc parmeloides) in a northern California river.

Scaling of graphene integrated circuits.

PubMed

Bianchi, Massimiliano; Guerriero, Erica; Fiocco, Marco; Alberti, Ruggero; Polloni, Laura; Behnam, Ashkan; Carrion, Enrique A; Pop, Eric; Sordan, Roman

2015-05-07

The influence of transistor size reduction (scaling) on the speed of realistic multi-stage integrated circuits (ICs) represents the main performance metric of a given transistor technology. Despite extensive interest in graphene electronics, scaling efforts have so far focused on individual transistors rather than multi-stage ICs. Here we study the scaling of graphene ICs based on transistors from 3.3 to 0.5 μm gate lengths and with different channel widths, access lengths, and lead thicknesses. The shortest gate delay of 31 ps per stage was obtained in sub-micron graphene ROs oscillating at 4.3 GHz, which is the highest oscillation frequency obtained in any strictly low-dimensional material to date. We also derived the fundamental Johnson limit, showing that scaled graphene ICs could be used at high frequencies in applications with small voltage swing.

Increasing CAD system efficacy for lung texture analysis using a convolutional network

NASA Astrophysics Data System (ADS)

Tarando, Sebastian Roberto; Fetita, Catalin; Faccinetto, Alex; Brillet, Pierre-Yves

2016-03-01

The infiltrative lung diseases are a class of irreversible, non-neoplastic lung pathologies requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. For the large majority of CAD systems, such classification relies on a two-dimensional analysis of axial CT images. In a previously developed CAD system, we proposed a fully-3D approach exploiting a multi-scale morphological analysis which showed good performance in detecting diseased areas, but with a major drawback consisting of sometimes overestimating the pathological areas and mixing different type of lung patterns. This paper proposes a combination of the existing CAD system with the classification outcome provided by a convolutional network, specifically tuned-up, in order to increase the specificity of the classification and the confidence to diagnosis. The advantage of using a deep learning approach is a better regularization of the classification output (because of a deeper insight into a given pathological class over a large series of samples) where the previous system is extra-sensitive due to the multi-scale response on patient-specific, localized patterns. In a preliminary evaluation, the combined approach was tested on a 10 patient database of various lung pathologies, showing a sharp increase of true detections.

Future time perspective: opportunities and limitations are differentially associated with subjective well-being and hair cortisol concentration.

PubMed

Kozik, Pavel; Hoppmann, Christiane A; Gerstorf, Denis

2015-01-01

Future time perspective has been associated with subjective well-being, though depending on the line of research considered either an open-ended future time perspective or a limited future time perspective has been associated with high well-being. Most of this research however has conceptualized future time perspective as a one-dimensional construct, whereas recent evidence has demonstrated that there are likely at least two different underlying dimensions, a focus on opportunities and a focus on limitations. This project first seeks to replicate the two-dimensional structure of the Future Time Perspective Scale, and then examines the associations these dimensions may have with different measures of subjective well-being and a biological index of chronic stress. To test if the two dimensions of the Future Time Perspective Scale, a focus on opportunities and a focus on limitations, differentially associate with two measures of subjective well-being and a biological indicator of chronic stress, namely hair cortisol. Sixty-six community-dwelling participants with a mean age of 72 years (SD = 5.83) completed the Future Time Perspective Scale, Center for Epidemiologic Studies Depression Scale, and Philadelphia Geriatric Center Morale Scale. Participants also provided a 3-cm-long hair strand to index cortisol accumulation over the past 3 months. Following the results of a factor analysis, a mediation model was created for each dimension of the Future Time Perspective Scale, and significance testing was done through a bootstrapping approach to harness maximal statistical power. Factor analysis results replicated the two-dimensional structure of the Future Time Perspective Scale. Both dimensions were then found to have unique associations with well-being. Specifically, a high focus on opportunities was associated with fewer depressive symptoms and higher morale, whereas a low focus on limitations was associated with reduced hair cortisol, though this association was mediated by subjective well-being. RESULTS replicate and extend previous research by pointing to the multi-dimensional nature of the Future Time Perspective Scale. While an open future time perspective was overall beneficial for well-being, the exact association each dimension had with well-being differed depending on whether subjective measures of well-being or biological indices of chronic stress were considered. © 2014 S. Karger AG, Basel.

Scientific Visualization and Simulation for Multi-dimensional Marine Environment Data

NASA Astrophysics Data System (ADS)

Su, T.; Liu, H.; Wang, W.; Song, Z.; Jia, Z.

2017-12-01

As higher attention on the ocean and rapid development of marine detection, there are increasingly demands for realistic simulation and interactive visualization of marine environment in real time. Based on advanced technology such as GPU rendering, CUDA parallel computing and rapid grid oriented strategy, a series of efficient and high-quality visualization methods, which can deal with large-scale and multi-dimensional marine data in different environmental circumstances, has been proposed in this paper. Firstly, a high-quality seawater simulation is realized by FFT algorithm, bump mapping and texture animation technology. Secondly, large-scale multi-dimensional marine hydrological environmental data is virtualized by 3d interactive technologies and volume rendering techniques. Thirdly, seabed terrain data is simulated with improved Delaunay algorithm, surface reconstruction algorithm, dynamic LOD algorithm and GPU programming techniques. Fourthly, seamless modelling in real time for both ocean and land based on digital globe is achieved by the WebGL technique to meet the requirement of web-based application. The experiments suggest that these methods can not only have a satisfying marine environment simulation effect, but also meet the rendering requirements of global multi-dimension marine data. Additionally, a simulation system for underwater oil spill is established by OSG 3D-rendering engine. It is integrated with the marine visualization method mentioned above, which shows movement processes, physical parameters, current velocity and direction for different types of deep water oil spill particle (oil spill particles, hydrates particles, gas particles, etc.) dynamically and simultaneously in multi-dimension. With such application, valuable reference and decision-making information can be provided for understanding the progress of oil spill in deep water, which is helpful for ocean disaster forecasting, warning and emergency response.

Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images.

PubMed

Barbosa, Daniel C; Roupar, Dalila B; Ramos, Jaime C; Tavares, Adriano C; Lima, Carlos S

2012-01-11

Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Two-dimensional multi-heart cutting centrifugal partition chromatography-liquid chromatography for the preparative isolation of antioxidants from Edelweiss plant.

PubMed

Marlot, Léa; Batteau, Magali; Escofet, Marie-Claire; Nuccio, Sylvie; Coquoin, Véronique; De Vaumas, René; Faure, Karine

2017-06-30

The Edelweiss plant has been recognized as a very valuable source of anti-aging principles due to its composition of antioxidants compounds: leontopodic acid A and 3,5-dicaffeoylquinic acid. In this work, off-line multi-heart cutting CPC-LC separation was set up at industrial scale in order to isolate and produce new high quality reference material of these two antioxidants from Edelweiss. For this purpose, CPC and HPLC methods were developed and optimized at laboratory scale and a comprehensive CPCxHPLC analysis of the crude extract was established. Thereby, the CPC method led to a first separation of the target compounds according to their partition coefficient in the solvent system and the HPLC method was performed on the recovered fractions to lead to a second separation. A 2D CPCxHPLC plot was established in order to know the fractions to select at the industrial scale. Then, the CPC and HPLC methods were transferred at industrial scale and the multi-heart cutting CPC-LC was performed in off-line mode. Using CPC with methyl ter-butyl ether-water 1:1 (v/v) solvent system and LC with Denali C18 column, 2g of crude extract sample were injected and leontopodic acid A and 3,5-dicaffeoylquinic acid were recovered with purity over 97%. The compounds were identified by MS and NMR. Copyright © 2017 Elsevier B.V. All rights reserved.

Modeling of Multi-Tube Pulse Detonation Engine Operation

NASA Technical Reports Server (NTRS)

Ebrahimi, Houshang B.; Mohanraj, Rajendran; Merkle, Charles L.

2001-01-01

The present paper explores some preliminary issues concerning the operational characteristics of multiple-tube pulsed detonation engines (PDEs). The study is based on a two-dimensional analysis of the first-pulse operation of two detonation tubes exhausting through a common nozzle. Computations are first performed to assess isolated tube behavior followed by results for multi-tube flow phenomena. The computations are based on an eight-species, finite-rate transient flow-field model. The results serve as an important precursor to understanding appropriate propellant fill procedures and shock wave propagation in multi-tube, multi-dimensional simulations. Differences in behavior between single and multi-tube PDE models are discussed, The influence of multi-tube geometry and the preferred times for injecting the fresh propellant mixture during multi-tube PDE operation are studied.

Bayesian approach for three-dimensional aquifer characterization at the Hanford 300 Area

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

Murakami, Haruko; Chen, X.; Hahn, Melanie S.

2010-10-21

This study presents a stochastic, three-dimensional characterization of a heterogeneous hydraulic conductivity field within DOE's Hanford 300 Area site, Washington, by assimilating large-scale, constant-rate injection test data with small-scale, three-dimensional electromagnetic borehole flowmeter (EBF) measurement data. We first inverted the injection test data to estimate the transmissivity field, using zeroth-order temporal moments of pressure buildup curves. We applied a newly developed Bayesian geostatistical inversion framework, the method of anchored distributions (MAD), to obtain a joint posterior distribution of geostatistical parameters and local log-transmissivities at multiple locations. The unique aspects of MAD that make it suitable for this purpose are itsmore » ability to integrate multi-scale, multi-type data within a Bayesian framework and to compute a nonparametric posterior distribution. After we combined the distribution of transmissivities with depth-discrete relative-conductivity profile from EBF data, we inferred the three-dimensional geostatistical parameters of the log-conductivity field, using the Bayesian model-based geostatistics. Such consistent use of the Bayesian approach throughout the procedure enabled us to systematically incorporate data uncertainty into the final posterior distribution. The method was tested in a synthetic study and validated using the actual data that was not part of the estimation. Results showed broader and skewed posterior distributions of geostatistical parameters except for the mean, which suggests the importance of inferring the entire distribution to quantify the parameter uncertainty.« less

Recent status scores for version 6 of the Addiction Severity Index (ASI-6).

PubMed

Cacciola, John S; Alterman, Arthur I; Habing, Brian; McLellan, A Thomas

2011-09-01

To describe the derivation of recent status scores (RSSs) for version 6 of the Addiction Severity Index (ASI-6). 118 ASI-6 recent status items were subjected to nonparametric item response theory (NIRT) analyses followed by confirmatory factor analysis (CFA). Generalizability and concurrent validity of the derived scores were determined. A total of 607 recent admissions to variety of substance abuse treatment programs constituted the derivation sample; a subset (n = 252) comprised the validity sample. The ASI-6 interview and a validity battery of primarily self-report questionnaires that included at least one measure corresponding to each of the seven ASI domains were administered. Nine summary scales describing recent status that achieved or approached both high scalability and reliability were derived; one scale for each of six areas (medical, employment/finances, alcohol, drug, legal, psychiatric) and three scales for the family/social area. Intercorrelations among the RSSs also supported the multi-dimensionality of the ASI-6. Concurrent validity analyses yielded strong evidence supporting the validity of six of the RSSs (medical, alcohol, drug, employment, family/social problems, psychiatric). Evidence was weaker for the legal, family/social support and child problems RSSs. Generalizability analyses of the scales to males versus females and whites versus blacks supported the comparability of the findings, with slight exceptions. The psychometric analyses to derive Addiction Severity Index version 6 recent status scores support the multi-dimensionality of the Addiction Severity Index version 6 (i.e. the relative independence of different life functioning areas), consistent with research on earlier editions of the instrument. In general, the Addiction Severity Index version 6 scales demonstrate acceptable scalability, reliability and concurrent validity. While questions remain about the generalizability of some scales to population subgroups, the overall findings coupled with updated and more extensive content in the Addiction Severity Index version 6 support its use in clinical practice and research. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Development of a WRF-RTFDDA-based high-resolution hybrid data-assimilation and forecasting system toward to operation in the Middle East

NASA Astrophysics Data System (ADS)

Liu, Y.; Wu, W.; Zhang, Y.; Kucera, P. A.; Liu, Y.; Pan, L.

2012-12-01

Weather forecasting in the Middle East is challenging because of its complicated geographical nature including massive coastal area and heterogeneous land, and regional spare observational network. Strong air-land-sea interactions form multi-scale weather regimes in the area, which require a numerical weather prediction model capable of properly representing multi-scale atmospheric flow with appropriate initial conditions. The WRF-based Real-Time Four Dimensional Data Assimilation (RTFDDA) system is one of advanced multi-scale weather analysis and forecasting facilities developed at the Research Applications Laboratory (RAL) of NCAR. The forecasting system is applied for the Middle East with careful configuration. To overcome the limitation of the very sparsely available conventional observations in the region, we develop a hybrid data assimilation algorithm combining RTFDDA and WRF-3DVAR, which ingests remote sensing data from satellites and radar. This hybrid data assimilation blends Newtonian nudging FDDA and 3DVAR technology to effectively assimilate both conventional observations and remote sensing measurements and provide improved initial conditions for the forecasting system. For brevity, the forecasting system is called RTF3H (RTFDDA-3DVAR Hybrid). In this presentation, we will discuss the hybrid data assimilation algorithm, and its implementation, and the applications for high-impact weather events in the area. Sensitivity studies are conducted to understand the strength and limitations of this hybrid data assimilation algorithm.

Frigatebird behaviour at the ocean-atmosphere interface: integrating animal behaviour with multi-satellite data.

PubMed

De Monte, Silvia; Cotté, Cedric; d'Ovidio, Francesco; Lévy, Marina; Le Corre, Matthieu; Weimerskirch, Henri

2012-12-07

Marine top predators such as seabirds are useful indicators of the integrated response of the marine ecosystem to environmental variability at different scales. Large-scale physical gradients constrain seabird habitat. Birds however respond behaviourally to physical heterogeneity at much smaller scales. Here, we use, for the first time, three-dimensional GPS tracking of a seabird, the great frigatebird (Fregata minor), in the Mozambique Channel. These data, which provide at the same time high-resolution vertical and horizontal positions, allow us to relate the behaviour of frigatebirds to the physical environment at the (sub-)mesoscale (10-100 km, days-weeks). Behavioural patterns are classified based on the birds' vertical displacement (e.g. fast/slow ascents and descents), and are overlaid on maps of physical properties of the ocean-atmosphere interface, obtained by a nonlinear analysis of multi-satellite data. We find that frigatebirds modify their behaviours concurrently to transport and thermal fronts. Our results suggest that the birds' co-occurrence with these structures is a consequence of their search not only for food (preferentially searched over thermal fronts) but also for upward vertical wind. This is also supported by their relationship with mesoscale patterns of wind divergence. Our multi-disciplinary method can be applied to forthcoming high-resolution animal tracking data, and aims to provide a mechanistic understanding of animals' habitat choice and of marine ecosystem responses to environmental change.

Development of morphogen gradient: The role of dimension and discreteness

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

Teimouri, Hamid; Kolomeisky, Anatoly B.

2014-02-28

The fundamental processes of biological development are governed by multiple signaling molecules that create non-uniform concentration profiles known as morphogen gradients. It is widely believed that the establishment of morphogen gradients is a result of complex processes that involve diffusion and degradation of locally produced signaling molecules. We developed a multi-dimensional discrete-state stochastic approach for investigating the corresponding reaction-diffusion models. It provided a full analytical description for stationary profiles and for important dynamic properties such as local accumulation times, variances, and mean first-passage times. The role of discreteness in developing of morphogen gradients is analyzed by comparing with available continuummore » descriptions. It is found that the continuum models prediction about multiple time scales near the source region in two-dimensional and three-dimensional systems is not supported in our analysis. Using ideas that view the degradation process as an effective potential, the effect of dimensionality on establishment of morphogen gradients is also discussed. In addition, we investigated how these reaction-diffusion processes are modified with changing the size of the source region.« less

Consistency of clinical biomechanical measures between three different institutions: implications for multi-center biomechanical and epidemiological research.

PubMed

Myer, Gregory D; Wordeman, Samuel C; Sugimoto, Dai; Bates, Nathaniel A; Roewer, Benjamin D; Medina McKeon, Jennifer M; DiCesare, Christopher A; Di Stasi, Stephanie L; Barber Foss, Kim D; Thomas, Staci M; Hewett, Timothy E

2014-05-01

Multi-center collaborations provide a powerful alternative to overcome the inherent limitations to single-center investigations. Specifically, multi-center projects can support large-scale prospective, longitudinal studies that investigate relatively uncommon outcomes, such as anterior cruciate ligament injury. This project was conceived to assess within- and between-center reliability of an affordable, clinical nomogram utilizing two-dimensional video methods to screen for risk of knee injury. The authors hypothesized that the two-dimensional screening methods would provide good-to-excellent reliability within and between institutions for assessment of frontal and sagittal plane biomechanics. Nineteen female, high school athletes participated. Two-dimensional video kinematics of the lower extremity during a drop vertical jump task were collected on all 19 study participants at each of the three facilities. Within-center and between-center reliability were assessed with intra- and inter-class correlation coefficients. Within-center reliability of the clinical nomogram variables was consistently excellent, but between-center reliability was fair-to-good. Within-center intra-class correlation coefficient for all nomogram variables combined was 0.98, while combined between-center inter-class correlation coefficient was 0.63. Injury risk screening protocols were reliable within and repeatable between centers. These results demonstrate the feasibility of multi-site biomechanical studies and establish a framework for further dissemination of injury risk screening algorithms. Specifically, multi-center studies may allow for further validation and optimization of two-dimensional video screening tools. 2b.

Defect-Repairable Latent Feature Extraction of Driving Behavior via a Deep Sparse Autoencoder

PubMed Central

Taniguchi, Tadahiro; Takenaka, Kazuhito; Bando, Takashi

2018-01-01

Data representing driving behavior, as measured by various sensors installed in a vehicle, are collected as multi-dimensional sensor time-series data. These data often include redundant information, e.g., both the speed of wheels and the engine speed represent the velocity of the vehicle. Redundant information can be expected to complicate the data analysis, e.g., more factors need to be analyzed; even varying the levels of redundancy can influence the results of the analysis. We assume that the measured multi-dimensional sensor time-series data of driving behavior are generated from low-dimensional data shared by the many types of one-dimensional data of which multi-dimensional time-series data are composed. Meanwhile, sensor time-series data may be defective because of sensor failure. Therefore, another important function is to reduce the negative effect of defective data when extracting low-dimensional time-series data. This study proposes a defect-repairable feature extraction method based on a deep sparse autoencoder (DSAE) to extract low-dimensional time-series data. In the experiments, we show that DSAE provides high-performance latent feature extraction for driving behavior, even for defective sensor time-series data. In addition, we show that the negative effect of defects on the driving behavior segmentation task could be reduced using the latent features extracted by DSAE. PMID:29462931

Nanosecond Plasma Enhanced H2/O2/N2 Premixed Flat Flames

DTIC Science & Technology

2014-01-01

Simulations are conducted with a one-dimensional, multi-scale, pulsed -discharge model with detailed plasma-combustion kinetics to develop additional insight... model framework. The reduced electric field, E/N, during each pulse varies inversely with number density. A significant portion of the input energy is...dimensional numerical model [4, 12] capable of resolving electric field transients over nanosecond timescales (during each discharge pulse ) and radical

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the microphysics developments of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the heavy precipitation processes will be presented.

A variational principle for compressible fluid mechanics: Discussion of the multi-dimensional theory

NASA Technical Reports Server (NTRS)

Prozan, R. J.

1982-01-01

The variational principle for compressible fluid mechanics previously introduced is extended to two dimensional flow. The analysis is stable, exactly conservative, adaptable to coarse or fine grids, and very fast. Solutions for two dimensional problems are included. The excellent behavior and results lend further credence to the variational concept and its applicability to the numerical analysis of complex flow fields.

Damage and failure modelling of hybrid three-dimensional textile composites: a mesh objective multi-scale approach

PubMed Central

Patel, Deepak K.

2016-01-01

This paper is concerned with predicting the progressive damage and failure of multi-layered hybrid textile composites subjected to uniaxial tensile loading, using a novel two-scale computational mechanics framework. These composites include three-dimensional woven textile composites (3DWTCs) with glass, carbon and Kevlar fibre tows. Progressive damage and failure of 3DWTCs at different length scales are captured in the present model by using a macroscale finite-element (FE) analysis at the representative unit cell (RUC) level, while a closed-form micromechanics analysis is implemented simultaneously at the subscale level using material properties of the constituents (fibre and matrix) as input. The N-layers concentric cylinder (NCYL) model (Zhang and Waas 2014 Acta Mech. 225, 1391–1417; Patel et al. submitted Acta Mech.) to compute local stress, srain and displacement fields in the fibre and matrix is used at the subscale. The 2-CYL fibre–matrix concentric cylinder model is extended to fibre and (N−1) matrix layers, keeping the volume fraction constant, and hence is called the NCYL model where the matrix damage can be captured locally within each discrete layer of the matrix volume. The influence of matrix microdamage at the subscale causes progressive degradation of fibre tow stiffness and matrix stiffness at the macroscale. The global RUC stiffness matrix remains positive definite, until the strain softening response resulting from different failure modes (such as fibre tow breakage, tow splitting in the transverse direction due to matrix cracking inside tow and surrounding matrix tensile failure outside of fibre tows) are initiated. At this stage, the macroscopic post-peak softening response is modelled using the mesh objective smeared crack approach (Rots et al. 1985 HERON 30, 1–48; Heinrich and Waas 2012 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, 23–26 April 2012. AIAA 2012-1537). Manufacturing-induced geometric imperfections are included in the simulation, where the FE mesh of the unit cell is generated directly from micro-computed tomography (MCT) real data using a code Simpleware. Results from multi-scale analysis for both an idealized perfect geometry and one that includes geometric imperfections are compared with experimental results (Pankow et al. 2012 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, 23–26 April 2012. AIAA 2012-1572). This article is part of the themed issue ‘Multiscale modelling of the structural integrity of composite materials’. PMID:27242294

Damage and failure modelling of hybrid three-dimensional textile composites: a mesh objective multi-scale approach.

PubMed

Patel, Deepak K; Waas, Anthony M

2016-07-13

This paper is concerned with predicting the progressive damage and failure of multi-layered hybrid textile composites subjected to uniaxial tensile loading, using a novel two-scale computational mechanics framework. These composites include three-dimensional woven textile composites (3DWTCs) with glass, carbon and Kevlar fibre tows. Progressive damage and failure of 3DWTCs at different length scales are captured in the present model by using a macroscale finite-element (FE) analysis at the representative unit cell (RUC) level, while a closed-form micromechanics analysis is implemented simultaneously at the subscale level using material properties of the constituents (fibre and matrix) as input. The N-layers concentric cylinder (NCYL) model (Zhang and Waas 2014 Acta Mech. 225, 1391-1417; Patel et al. submitted Acta Mech.) to compute local stress, srain and displacement fields in the fibre and matrix is used at the subscale. The 2-CYL fibre-matrix concentric cylinder model is extended to fibre and (N-1) matrix layers, keeping the volume fraction constant, and hence is called the NCYL model where the matrix damage can be captured locally within each discrete layer of the matrix volume. The influence of matrix microdamage at the subscale causes progressive degradation of fibre tow stiffness and matrix stiffness at the macroscale. The global RUC stiffness matrix remains positive definite, until the strain softening response resulting from different failure modes (such as fibre tow breakage, tow splitting in the transverse direction due to matrix cracking inside tow and surrounding matrix tensile failure outside of fibre tows) are initiated. At this stage, the macroscopic post-peak softening response is modelled using the mesh objective smeared crack approach (Rots et al. 1985 HERON 30, 1-48; Heinrich and Waas 2012 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, 23-26 April 2012 AIAA 2012-1537). Manufacturing-induced geometric imperfections are included in the simulation, where the FE mesh of the unit cell is generated directly from micro-computed tomography (MCT) real data using a code Simpleware Results from multi-scale analysis for both an idealized perfect geometry and one that includes geometric imperfections are compared with experimental results (Pankow et al. 2012 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Honolulu, HI, 23-26 April 2012 AIAA 2012-1572). This article is part of the themed issue 'Multiscale modelling of the structural integrity of composite materials'. © 2016 The Author(s).

Quantifying Stream-Aquifer Exchanges Over Scales: the Concept of Nested Interfaces

NASA Astrophysics Data System (ADS)

Flipo, N.; Mouhri, A.; Labarthe, B.; Saleh, F. S.

2013-12-01

Recent developments in hydrological modelling are based on a view of the interface being a single continuum through which water flows. These coupled hydrological-hydrogeological models, emphasizing the importance of the stream-aquifer interface (SAI), are more and more used in hydrological sciences for pluri-disciplinary studies aiming at questioning environmental issues. This notion of a single continuum comes from the historical modelling of hydrosystems based on the hypothesis of a homogeneous media that led to the Darcy law. Nowadays, there is a need to first bridge the gap between hydrological and eco-hydrological views of the SAIs, and, second, to rationalize the modelling of SAI within a consistent framework that fully takes into account the multi-dimensionality of the SAIs. We first define the concept of nested SAIs as a key transitional component of continental hydrosystem. We then demonstrate the usefulness of the concept for the multi-dimensional study of the SAI, with a special emphasis on the stream network which is identified as the key component for scaling hydrological processes occurring at the interface. Finally we focus on SAI modelling at various scales with up-to-date methodologies and give some guidance for the multi-dimensional modelling of the interface using the innovative methodology MIM (Measurements-Interpolation-Modelling), which is graphically developed. MIM scales in space three pools of methods needed to fully understand SAIs. The outcome of MIM is the localization in space of the type of SAI that can be studied by a given approach. The efficiency of the method is illustrated from the local (approx. 1m) to the regional scale (> 10 000 km2) with two examples from the Paris basin (France). The first one consists in the implementation of a sampling system of stream-aquifer exchanges, which is coupled with local 2D thermo-hydro models and a pseudo 3D hydro(geo)logical model at the watershed scale (40 km2). The quantification of monthly stream-aquifer exchanges over 14 000 km of river network in the Paris basin (74 000 km2) corresponds to a unique regional scale example.

Construct Validation of the Translated Version of the Work-Family Conflict Scale for Use in Korea

ERIC Educational Resources Information Center

Lim, Doo Hun; Morris, Michael Lane; McMillan, Heather S.

2011-01-01

Recently, the stress of work-family conflict has been a critical workplace issue for Asian countries, especially within those cultures experiencing rapid economic development. Our research purpose is to translate and establish construct validity of a Korean-language version of the Multi-Dimensional Work-Family Conflict (WFC) scale used in the U.S.…

CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets

PubMed Central

Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.

2017-01-01

High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787

Semantic Differential Scale Method Can Reveal Multi-Dimensional Aspects of Mind Perception.

PubMed

Takahashi, Hideyuki; Ban, Midori; Asada, Minoru

2016-01-01

As humans, we tend to perceive minds in both living and non-living entities, such as robots. From a questionnaire developed in a previous mind perception study, authors found that perceived minds could be located on two dimensions "experience" and "agency." This questionnaire allowed the assessment of how we perceive minds of various entities from a multi-dimensional point of view. In this questionnaire, subjects had to evaluate explicit mental capacities of target characters (e.g., capacity to feel hunger). However, we sometimes perceive minds in non-living entities, even though we cannot attribute these evidently biological capacities to the entity. In this study, we performed a large-scale web survey to assess mind perception by using the semantic differential scale method. We revealed that two mind dimensions "emotion" and "intelligence," respectively, corresponded to the two mind dimensions (experience and agency) proposed in a previous mind perception study. We did this without having to ask about specific mental capacities. We believe that the semantic differential scale is a useful method to assess the dimensions of mind perception especially for non-living entities that are hard to be attributed to biological capacities.

EXPERIMENTAL INVESTIGATION OF RELATIVE PERMEABILITY UPSCALING FROM THE MICRO-SCALE TO THE MACRO-SCALE

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

Laura J. Pyrak-Nolte; Ping Yu; JiangTao Cheng

2002-12-01

The principal challenge of upscaling techniques for multi-phase fluid dynamics in porous media is to determine which properties on the micro-scale can be used to predict macroscopic flow and spatial distribution of phases at core- and field-scales. The most notable outcome of recent theories is the identification of interfacial areas per volume for multiple phases as a fundamental parameter that determines much of the multi-phase properties of the porous medium. A formal program of experimental research was begun to directly test upscaling theories in fluid flow through porous media by comparing measurements of relative permeability and capillary-saturation with measurements ofmore » interfacial area per volume. During this reporting period, we have shown experimentally that the coherence detection can be performed in a borescope. The measurement of interfacial area per volume (IAV), capillary pressure and saturation in two dimensional micro-models structures has shown the existence of a unique relationship among these hydraulic parameters for different pore geometry. The measurement of interfacial area per volume on a three-dimensional natural sample, i.e., sandstone, is essentially completed for imbibition conditions.« less

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

Minimum mass design of large-scale space trusses subjected to thermal gradients

NASA Technical Reports Server (NTRS)

Williams, R. Brett; Agnes, Gregory S.

2006-01-01

Lightweight, deployable trusses are commonly used to support space-borne instruments including RF reflectors, radar panels, and telescope optics. While in orbit, these support structures are subjected to thermal gradients that vary with altitude, location in orbit, and self-shadowing. Since these instruments have tight dimensional-stability requirements, their truss members are often covered with multi-layer insulation (MLI) blankets to minimize thermal distortions. This paper develops a radiation heat transfer model to predict the thermal gradient experienced by a triangular truss supporting a long, linear radar panel in Medium Earth Orbit (MEO). The influence of self-shadowing effects of the radar panel are included in the analysis, and the influence of both MLI thickness and outer covers/coatings on the magnitude of the thermal gradient are formed into a simple, two-dimensional analysis. This thermal model is then used to size and estimate the structural mass of a triangular truss that meets a given set of structural requirements.

Bayesian analysis of spatially-dependent functional responses with spatially-dependent multi-dimensional functional predictors

USDA-ARS?s Scientific Manuscript database

Recent advances in technology have led to the collection of high-dimensional data not previously encountered in many scientific environments. As a result, scientists are often faced with the challenging task of including these high-dimensional data into statistical models. For example, data from sen...

Multi-window PIV measurements around a breathing manikin

NASA Astrophysics Data System (ADS)

Marr, David

2005-11-01

The presented work includes multi-scale measurements via a stereo article Image Velocimetry (PIV) system to view a pair of two-component windows of dissimilar scale using a varied focal length. These measurements are taken in the breathing zone of an isothermal breathing manikin (from mouth) in an environmental chamber of average office cubicle dimensions without ventilation and are analogous to an oscillatory jet. From these phase-averaged measurements, we can extract information concerning length scales, turbulence quantities and low dimensional information in order to both determine correlation between data at different length scales as well as continuing research in exposure assessment for the indoor environment. In this talk we will present these turbulence quantities and interpret their influence on the breathing zone. While the largest scale is that of the room itself, we find that the relevant spatial scales associated with the breathing zone are much lower in magnitude. In future experiments, we will expand the multi window PIV technique to include PIV window configured to obtain scales of order the cubicle simultaneously with those of the breathing zone. This will aid in our understanding of the combined impact of these multiple scales on occupant exposure in the indoor environment.

Multi-Scale Analyses of Three Dimensional Woven Composite 3D Shell With a Cut Out Circle

NASA Astrophysics Data System (ADS)

Nguyen, Duc Hai; Wang, Hu

2018-06-01

A composite material are made by combining two or more constituent materials to obtain the desired material properties of each product type. The matrix material which can be polymer and fiber is used as reinforcing material. Currently, the polymer matrix is widely used in many different fields with differently designed structures such as automotive structures and aviation, aerospace, marine, etc. because of their excellent mechanical properties; in addition, they possess the high level of hardness and durability together with a significant reduction in weight compared to traditional materials. However, during design process of structure, there will be many interruptions created for the purpose of assembling the structures together or for many other design purposes. Therefore, when this structure is subject to load-bearing, its failure occurs at these interruptions due to stress concentration. This paper proposes multi-scale modeling and optimization strategies in evaluation of the effectiveness of fiber orientation in an E-glass/Epoxy woven composite 3D shell with circular holes at the center investigated by FEA results. A multi-scale model approach was developed to predict the mechanical behavior of woven composite 3D shell with circular holes at the center with different designs of material and structural parameters. Based on the analysis result of laminae, we have found that the 3D shell with fiber direction of 450 shows the best stress and strain bearing capacity. Thus combining several layers of 450 fiber direction in a multi-layer composite 3D shell reduces the stresses concentrated on the cuts of the structures.

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

A Novel Multi-Scale Domain Overlapping CFD/STH Coupling Methodology for Multi-Dimensional Flows Relevant to Nuclear Applications

NASA Astrophysics Data System (ADS)

Grunloh, Timothy P.

The objective of this dissertation is to develop a 3-D domain-overlapping coupling method that leverages the superior flow field resolution of the Computational Fluid Dynamics (CFD) code STAR-CCM+ and the fast execution of the System Thermal Hydraulic (STH) code TRACE to efficiently and accurately model thermal hydraulic transport properties in nuclear power plants under complex conditions of regulatory and economic importance. The primary contribution is the novel Stabilized Inertial Domain Overlapping (SIDO) coupling method, which allows for on-the-fly correction of TRACE solutions for local pressures and velocity profiles inside multi-dimensional regions based on the results of the CFD simulation. The method is found to outperform the more frequently-used domain decomposition coupling methods. An STH code such as TRACE is designed to simulate large, diverse component networks, requiring simplifications to the fluid flow equations for reasonable execution times. Empirical correlations are therefore required for many sub-grid processes. The coarse grids used by TRACE diminish sensitivity to small scale geometric details such as Reactor Pressure Vessel (RPV) internals. A CFD code such as STAR-CCM+ uses much finer computational meshes that are sensitive to the geometric details of reactor internals. In turbulent flows, it is infeasible to fully resolve the flow solution, but the correlations used to model turbulence are at a low level. The CFD code can therefore resolve smaller scale flow processes. The development of a 3-D coupling method was carried out with the intention of improving predictive capabilities of transport properties in the downcomer and lower plenum regions of an RPV in reactor safety calculations. These regions are responsible for the multi-dimensional mixing effects that determine the distribution at the core inlet of quantities with reactivity implications, such as fluid temperature and dissolved neutron absorber concentration.

Multi-Scale Microstructural Thermoelectric Materials: Transport Behavior, Non-Equilibrium Preparation, and Applications.

PubMed

Su, Xianli; Wei, Ping; Li, Han; Liu, Wei; Yan, Yonggao; Li, Peng; Su, Chuqi; Xie, Changjun; Zhao, Wenyu; Zhai, Pengcheng; Zhang, Qingjie; Tang, Xinfeng; Uher, Ctirad

2017-05-01

Considering only about one third of the world's energy consumption is effectively utilized for functional uses, and the remaining is dissipated as waste heat, thermoelectric (TE) materials, which offer a direct and clean thermal-to-electric conversion pathway, have generated a tremendous worldwide interest. The last two decades have witnessed a remarkable development in TE materials. This Review summarizes the efforts devoted to the study of non-equilibrium synthesis of TE materials with multi-scale structures, their transport behavior, and areas of applications. Studies that work towards the ultimate goal of developing highly efficient TE materials possessing multi-scale architectures are highlighted, encompassing the optimization of TE performance via engineering the structures with different dimensional aspects spanning from the atomic and molecular scales, to nanometer sizes, and to the mesoscale. In consideration of the practical applications of high-performance TE materials, the non-equilibrium approaches offer a fast and controllable fabrication of multi-scale microstructures, and their scale up to industrial-size manufacturing is emphasized here. Finally, the design of two integrated power generating TE systems are described-a solar thermoelectric-photovoltaic hybrid system and a vehicle waste heat harvesting system-that represent perhaps the most important applications of thermoelectricity in the energy conversion area. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Real-Time Three-Dimensional Cell Segmentation in Large-Scale Microscopy Data of Developing Embryos.

PubMed

Stegmaier, Johannes; Amat, Fernando; Lemon, William C; McDole, Katie; Wan, Yinan; Teodoro, George; Mikut, Ralf; Keller, Philipp J

2016-01-25

We present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55-330 times faster and 2-5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS. Copyright © 2016 Elsevier Inc. All rights reserved.

A Multi-dimensional Model for Vehicle Impact on Traffic Safety, Congestion, and Environment

DOT National Transportation Integrated Search

2012-01-01

The Intelligent Transportation System (ITS) has recently received great attention in the research : community. It offers a revolutionary vision of transportation, in which a full-scale : communication scheme between vehicles (V2V) and vehicles and in...

Three-dimensional flow characteristics of aluminum alloy in multi-pass equal channel angular pressing

NASA Astrophysics Data System (ADS)

Jin, Young-Gwan; Son, Il-Heon; Im, Yong-Taek

2010-06-01

Experiments with a square specimen made of commercially pure aluminum alloy (AA1050) were conducted to investigate deformation behaviour during a multi-pass Equal Channel Angular Pressing (ECAP) for routes A, Bc, and C up to four passes. Three-dimensional finite element numerical simulations of the multi-pass ECAP were carried out in order to evaluate the influence of processing routes and number of passes on local flow behaviour by applying a simplified saturation model of flow stress under an isothermal condition. Simulation results were investigated by comparing them with the experimentally measured data in terms of load variations and microhardness distributions. Also, transmission electron microscopy analysis was employed to investigate the microstructural changes. The present work clearly shows that the three-dimensional flow characteristics of the deformed specimen were dependent on the strain path changes due to the processing routes and number of passes that occurred during the multi-pass ECAP.

Self-dissimilar landscapes: Revealing the signature of geologic constraints on landscape dissection via topologic and multi-scale analysis

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Tejedor, Alejandro; Foufoula-Georgiou, Efi

2017-10-01

Climatic or geologic controls, such as tectonics or glacial drainage, might impose constraints on landscape self-organization resulting in spatial patterns of rivers and valleys which do not obey the typical self-similar relationships found in most landscapes. The goal of this study is to quantify how such geologic constraints express themselves on channel network topology, spatial heterogeneity of drainage patterns, and emergence of preferred scales of landscape dissection. We use as an example a basin located in the Upper Midwestern United States where successive glaciations over the past thousand years have led to a pronounced spatially anisotropic channel network structure which defeats most scaling laws of fluvial landscapes. This is contrasted with another river basin in the North-Central U.S. which has been organized under the absence of major geologic influences and follows a typical self-similar channel network organization. We show how the geologic constraints have imposed a competition for space which is captured in the slope-local drainage density probabilistic structure, in the failure of self-similarity in basin-wide river network topology, and in the length-area scaling relationship being not typical of fluvial landscapes. Via a two-dimensional wavelet analysis and synthesis, we demonstrate the occurrence of a gap in the power spectrum which corresponds to the presence of preferred scales of organization, and characterize them through multi-scale detrending. The developed methodologies can be useful in advancing our geomorphologic understanding of how external controls might manifest themselves in creating a landscape dissection that is outside the norm and how this dissection can be studied objectively for understanding cause and effect.

Final Technical Report: Mathematical Foundations for Uncertainty Quantification in Materials Design

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

Plechac, Petr; Vlachos, Dionisios G.

We developed path-wise information theory-based and goal-oriented sensitivity analysis and parameter identification methods for complex high-dimensional dynamics and in particular of non-equilibrium extended molecular systems. The combination of these novel methodologies provided the first methods in the literature which are capable to handle UQ questions for stochastic complex systems with some or all of the following features: (a) multi-scale stochastic models such as (bio)chemical reaction networks, with a very large number of parameters, (b) spatially distributed systems such as Kinetic Monte Carlo or Langevin Dynamics, (c) non-equilibrium processes typically associated with coupled physico-chemical mechanisms, driven boundary conditions, hybrid micro-macro systems,more » etc. A particular computational challenge arises in simulations of multi-scale reaction networks and molecular systems. Mathematical techniques were applied to in silico prediction of novel materials with emphasis on the effect of microstructure on model uncertainty quantification (UQ). We outline acceleration methods to make calculations of real chemistry feasible followed by two complementary tasks on structure optimization and microstructure-induced UQ.« less

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

NASA Astrophysics Data System (ADS)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy precipitation processes will be discussed.

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei--Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2010-01-01

In recent years, exponentially increasing computer power extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 sq km in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale models can be run in grid size similar to cloud resolving models through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model). (2) a regional scale model (a NASA unified weather research and forecast, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

The Influence of Multi-Scale Stratal Architecture on Multi-Phase Flow

NASA Astrophysics Data System (ADS)

Soltanian, M.; Gershenzon, N. I.; Ritzi, R. W.; Dominic, D.; Ramanathan, R.

2012-12-01

Geological heterogeneity affects flow and transport in porous media, including the migration and entrapment patterns of oil, and efforts for enhanced oil recovery. Such effects are only understood through their relation to a hierarchy of reservoir heterogeneities over a range of scales. Recent work on modern rivers and ancient sediments has led to a conceptual model of the hierarchy of fluvial forms within channel-belts of gravelly braided rivers, and a quantitative model for the corresponding scales of heterogeneity within the stratal architecture (e.g. [Lunt et al (2004) Sedimentology, 51 (3), 377]). In related work, a three-dimensional digital model was developed which represents these scales of fluvial architecture, the associated spatial distribution of permeability, and the connectivity of high-permeability pathways across the different scales of the stratal hierarchy [Ramanathan et al, (2010) Water Resour. Res., 46, W04515; Guin et al, (2010) Water Resour. Res., 46, W04516]. In the present work we numerically examine three-phase fluid flow (water-oil-gas) incorporating the multi-scale model for reservoir heterogeneity spanning the scales from 10^-1 to 10^3 meters. Comparison with results of flow in a reservoir with homogeneous permeability is made showing essentially different flow dynamics.

Physics in space-time with scale-dependent metrics

NASA Astrophysics Data System (ADS)

Balankin, Alexander S.

2013-10-01

We construct three-dimensional space Rγ3 with the scale-dependent metric and the corresponding Minkowski space-time Mγ,β4 with the scale-dependent fractal (DH) and spectral (DS) dimensions. The local derivatives based on scale-dependent metrics are defined and differential vector calculus in Rγ3 is developed. We state that Mγ,β4 provides a unified phenomenological framework for dimensional flow observed in quite different models of quantum gravity. Nevertheless, the main attention is focused on the special case of flat space-time M1/3,14 with the scale-dependent Cantor-dust-like distribution of admissible states, such that DH increases from DH=2 on the scale ≪ℓ0 to DH=4 in the infrared limit ≫ℓ0, where ℓ0 is the characteristic length (e.g. the Planck length, or characteristic size of multi-fractal features in heterogeneous medium), whereas DS≡4 in all scales. Possible applications of approach based on the scale-dependent metric to systems of different nature are briefly discussed.

Upscale Impact of Mesoscale Disturbances of Tropical Convection on Convectively Coupled Kelvin Waves

NASA Astrophysics Data System (ADS)

Yang, Q.; Majda, A.

2017-12-01

Tropical convection associated with convectively coupled Kelvin waves (CCKWs) is typically organized by an eastward-moving synoptic-scale convective envelope with numerous embedded westward-moving mesoscale disturbances. It is of central importance to assess upscale impact of mesoscale disturbances on CCKWs as mesoscale disturbances propagate at various tilt angles and speeds. Here a simple multi-scale model is used to capture this multi-scale structure, where mesoscale fluctuations are directly driven by mesoscale heating and synoptic-scale circulation is forced by mean heating and eddy transfer of momentum and temperature. The two-dimensional version of the multi-scale model drives the synoptic-scale circulation, successfully reproduces key features of flow fields with a front-to-rear tilt and compares well with results from a cloud resolving model. In the scenario with an elevated upright mean heating, the tilted vertical structure of synoptic-scale circulation is still induced by the upscale impact of mesoscale disturbances. In a faster propagation scenario, the upscale impact becomes less important, while the synoptic-scale circulation response to mean heating dominates. In the unrealistic scenario with upward/westward tilted mesoscale heating, positive potential temperature anomalies are induced in the leading edge, which will suppress shallow convection in a moist environment. In its three-dimensional version, results show that upscale impact of mesoscale disturbances that propagate at tilt angles (110o 250o) induces negative lower-tropospheric potential temperature anomalies in the leading edge, providing favorable conditions for shallow convection in a moist environment, while the remaining tilt angle cases have opposite effects. Even in the presence of upright mean heating, the front-to-rear tilted synoptic-scale circulation can still be induced by eddy terms at tilt angles (120o 240o). In the case with fast propagating mesoscale heating, positive potential temperature anomalies are induced in the lower troposphere, suppressing convection in a moist environment. This simple model also reproduces convective momentum transport and CCKWs in agreement with results from a recent cloud resolving simulation.

Anonymous voting for multi-dimensional CV quantum system

NASA Astrophysics Data System (ADS)

Rong-Hua, Shi; Yi, Xiao; Jin-Jing, Shi; Ying, Guo; Moon-Ho, Lee

2016-06-01

We investigate the design of anonymous voting protocols, CV-based binary-valued ballot and CV-based multi-valued ballot with continuous variables (CV) in a multi-dimensional quantum cryptosystem to ensure the security of voting procedure and data privacy. The quantum entangled states are employed in the continuous variable quantum system to carry the voting information and assist information transmission, which takes the advantage of the GHZ-like states in terms of improving the utilization of quantum states by decreasing the number of required quantum states. It provides a potential approach to achieve the efficient quantum anonymous voting with high transmission security, especially in large-scale votes. Project supported by the National Natural Science Foundation of China (Grant Nos. 61272495, 61379153, and 61401519), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20130162110012), and the MEST-NRF of Korea (Grant No. 2012-002521).

D Reconstruction and Visualization of Cultural Heritage: Analyzing Our Legacy Through Time

NASA Astrophysics Data System (ADS)

Rodríguez-Gonzálvez, P.; Muñoz-Nieto, A. L.; del Pozo, S.; Sanchez-Aparicio, L. J.; Gonzalez-Aguilera, D.; Micoli, L.; Gonizzi Barsanti, S.; Guidi, G.; Mills, J.; Fieber, K.; Haynes, I.; Hejmanowska, B.

2017-02-01

Temporal analyses and multi-temporal 3D reconstruction are fundamental for the preservation and maintenance of all forms of Cultural Heritage (CH) and are the basis for decisions related to interventions and promotion. Introducing the fourth dimension of time into three-dimensional geometric modelling of real data allows the creation of a multi-temporal representation of a site. In this way, scholars from various disciplines (surveyors, geologists, archaeologists, architects, philologists, etc.) are provided with a new set of tools and working methods to support the study of the evolution of heritage sites, both to develop hypotheses about the past and to model likely future developments. The capacity to "see" the dynamic evolution of CH assets across different spatial scales (e.g. building, site, city or territory) compressed in diachronic model, affords the possibility to better understand the present status of CH according to its history. However, there are numerous challenges in order to carry out 4D modelling and the requisite multi-data source integration. It is necessary to identify the specifications, needs and requirements of the CH community to understand the required levels of 4D model information. In this way, it is possible to determine the optimum material and technologies to be utilised at different CH scales, as well as the data management and visualization requirements. This manuscript aims to provide a comprehensive approach for CH time-varying representations, analysis and visualization across different working scales and environments: rural landscape, urban landscape and architectural scales. Within this aim, the different available metric data sources are systemized and evaluated in terms of their suitability.

Multi-Scale Analysis for Characterizing Near-Field Constituent Concentrations in the Context of a Macro-Scale Semi-Lagrangian Numerical Model

NASA Astrophysics Data System (ADS)

Yearsley, J. R.

2017-12-01

The semi-Lagrangian numerical scheme employed by RBM, a model for simulating time-dependent, one-dimensional water quality constituents in advection-dominated rivers, is highly scalable both in time and space. Although the model has been used at length scales of 150 meters and time scales of three hours, the majority of applications have been at length scales of 1/16th degree latitude/longitude (about 5 km) or greater and time scales of one day. Applications of the method at these scales has proven successful for characterizing the impacts of climate change on water temperatures in global rivers and on the vulnerability of thermoelectric power plants to changes in cooling water temperatures in large river systems. However, local effects can be very important in terms of ecosystem impacts, particularly in the case of developing mixing zones for wastewater discharges with pollutant loadings limited by regulations imposed by the Federal Water Pollution Control Act (FWPCA). Mixing zone analyses have usually been decoupled from large-scale watershed influences by developing scenarios that represent critical scenarios for external processes associated with streamflow and weather conditions . By taking advantage of the particle-tracking characteristics of the numerical scheme, RBM can provide results at any point in time within the model domain. We develop a proof of concept for locations in the river network where local impacts such as mixing zones may be important. Simulated results from the semi-Lagrangian numerical scheme are treated as input to a finite difference model of the two-dimensional diffusion equation for water quality constituents such as water temperature or toxic substances. Simulations will provide time-dependent, two-dimensional constituent concentration in the near-field in response to long-term basin-wide processes. These results could provide decision support to water quality managers for evaluating mixing zone characteristics.

Simultaneous Multi-Scale Diffusion Estimation and Tractography Guided by Entropy Spectrum Pathways

PubMed Central

Galinsky, Vitaly L.; Frank, Lawrence R.

2015-01-01

We have developed a method for the simultaneous estimation of local diffusion and the global fiber tracts based upon the information entropy flow that computes the maximum entropy trajectories between locations and depends upon the global structure of the multi-dimensional and multi-modal diffusion field. Computation of the entropy spectrum pathways requires only solving a simple eigenvector problem for the probability distribution for which efficient numerical routines exist, and a straight forward integration of the probability conservation through ray tracing of the convective modes guided by a global structure of the entropy spectrum coupled with a small scale local diffusion. The intervoxel diffusion is sampled by multi b-shell multi q-angle DWI data expanded in spherical waves. This novel approach to fiber tracking incorporates global information about multiple fiber crossings in every individual voxel and ranks it in the most scientifically rigorous way. This method has potential significance for a wide range of applications, including studies of brain connectivity. PMID:25532167

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

Structural and Practical Identifiability Issues of Immuno-Epidemiological Vector-Host Models with Application to Rift Valley Fever.

PubMed

Tuncer, Necibe; Gulbudak, Hayriye; Cannataro, Vincent L; Martcheva, Maia

2016-09-01

In this article, we discuss the structural and practical identifiability of a nested immuno-epidemiological model of arbovirus diseases, where host-vector transmission rate, host recovery, and disease-induced death rates are governed by the within-host immune system. We incorporate the newest ideas and the most up-to-date features of numerical methods to fit multi-scale models to multi-scale data. For an immunological model, we use Rift Valley Fever Virus (RVFV) time-series data obtained from livestock under laboratory experiments, and for an epidemiological model we incorporate a human compartment to the nested model and use the number of human RVFV cases reported by the CDC during the 2006-2007 Kenya outbreak. We show that the immunological model is not structurally identifiable for the measurements of time-series viremia concentrations in the host. Thus, we study the non-dimensionalized and scaled versions of the immunological model and prove that both are structurally globally identifiable. After fixing estimated parameter values for the immunological model derived from the scaled model, we develop a numerical method to fit observable RVFV epidemiological data to the nested model for the remaining parameter values of the multi-scale system. For the given (CDC) data set, Monte Carlo simulations indicate that only three parameters of the epidemiological model are practically identifiable when the immune model parameters are fixed. Alternatively, we fit the multi-scale data to the multi-scale model simultaneously. Monte Carlo simulations for the simultaneous fitting suggest that the parameters of the immunological model and the parameters of the immuno-epidemiological model are practically identifiable. We suggest that analytic approaches for studying the structural identifiability of nested models are a necessity, so that identifiable parameter combinations can be derived to reparameterize the nested model to obtain an identifiable one. This is a crucial step in developing multi-scale models which explain multi-scale data.

Wavelet-based multiscale adjoint waveform-difference tomography using body and surface waves

NASA Astrophysics Data System (ADS)

Yuan, Y. O.; Simons, F. J.; Bozdag, E.

2014-12-01

We present a multi-scale scheme for full elastic waveform-difference inversion. Using a wavelet transform proves to be a key factor to mitigate cycle-skipping effects. We start with coarse representations of the seismogram to correct a large-scale background model, and subsequently explain the residuals in the fine scales of the seismogram to map the heterogeneities with great complexity. We have previously applied the multi-scale approach successfully to body waves generated in a standard model from the exploration industry: a modified two-dimensional elastic Marmousi model. With this model we explored the optimal choice of wavelet family, number of vanishing moments and decomposition depth. For this presentation we explore the sensitivity of surface waves in waveform-difference tomography. The incorporation of surface waves is rife with cycle-skipping problems compared to the inversions considering body waves only. We implemented an envelope-based objective function probed via a multi-scale wavelet analysis to measure the distance between predicted and target surface-wave waveforms in a synthetic model of heterogeneous near-surface structure. Our proposed method successfully purges the local minima present in the waveform-difference misfit surface. An elastic shallow model with 100~m in depth is used to test the surface-wave inversion scheme. We also analyzed the sensitivities of surface waves and body waves in full waveform inversions, as well as the effects of incorrect density information on elastic parameter inversions. Based on those numerical experiments, we ultimately formalized a flexible scheme to consider both body and surface waves in adjoint tomography. While our early examples are constructed from exploration-style settings, our procedure will be very valuable for the study of global network data.

Viscous/potential flow about multi-element two-dimensional and infinite-span swept wings: Theory and experiment

NASA Technical Reports Server (NTRS)

Olson, L. E.; Dvorak, F. A.

1975-01-01

The viscous subsonic flow past two-dimensional and infinite-span swept multi-component airfoils is studied theoretically and experimentally. The computerized analysis is based on iteratively coupled boundary layer and potential flow analysis. The method, which is restricted to flows with only slight separation, gives surface pressure distribution, chordwise and spanwise boundary layer characteristics, lift, drag, and pitching moment for airfoil configurations with up to four elements. Merging confluent boundary layers are treated. Theoretical predictions are compared with an exact theoretical potential flow solution and with experimental measures made in the Ames 40- by 80-Foot Wind Tunnel for both two-dimensional and infinite-span swept wing configurations. Section lift characteristics are accurately predicted for zero and moderate sweep angles where flow separation effects are negligible.

Xarray: multi-dimensional data analysis in Python

NASA Astrophysics Data System (ADS)

Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

2017-04-01

xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.

Three-Dimensional Model of Strengths: Examination of Invariance Across Gender, Age, Education Levels, and Marriage Status.

PubMed

Duan, Wenjie; Ho, Samuel Mun Yin

2017-02-01

Strengths are positive qualities that significantly contributed to well-being of individuals and community. Therefore, a reliable and valid measure of strengths for research and practice is needed. The Brief Strengths Scale (BSS) is a newly developed tool for measuring the three-dimensional strengths model (i.e., temperance, intellectual, and interpersonal strength). However, empirical support for the measurement invariance of the BSS has not been obtained. This study examined the three-factor structure of BSS across gender, age, education, and marriage groups in a community sample (n = 375) using multi-group confirmatory factor analysis. After removing one item of each subscale from the original version, the revised model provided a good fit to the data at different subgroups. The revised nine-item BSS indicated that measurement invariance across gender and age groups was achieved. In addition, the measurement was more influenced by social-cultural factors than biological factors.

The application of a multi-dimensional assessment approach to talent identification in Australian football.

PubMed

Woods, Carl T; Raynor, Annette J; Bruce, Lyndell; McDonald, Zane; Robertson, Sam

2016-07-01

This study investigated whether a multi-dimensional assessment could assist with talent identification in junior Australian football (AF). Participants were recruited from an elite under 18 (U18) AF competition and classified into two groups; talent identified (State U18 Academy representatives; n = 42; 17.6 ± 0.4 y) and non-talent identified (non-State U18 Academy representatives; n = 42; 17.4 ± 0.5 y). Both groups completed a multi-dimensional assessment, which consisted of physical (standing height, dynamic vertical jump height and 20 m multistage fitness test), technical (kicking and handballing tests) and perceptual-cognitive (video decision-making task) performance outcome tests. A multivariate analysis of variance tested the main effect of status on the test criterions, whilst a receiver operating characteristic curve assessed the discrimination provided from the full assessment. The talent identified players outperformed their non-talent identified peers in each test (P < 0.05). The receiver operating characteristic curve reflected near perfect discrimination (AUC = 95.4%), correctly classifying 95% and 86% of the talent identified and non-talent identified participants, respectively. When compared to single assessment approaches, this multi-dimensional assessment reflects a more comprehensive means of talent identification in AF. This study further highlights the importance of assessing multi-dimensional performance qualities when identifying talented team sports.

Multi-scale theory-assisted nano-engineering of plasmonic-organic hybrid electro-optic device performance

NASA Astrophysics Data System (ADS)

Elder, Delwin L.; Johnson, Lewis E.; Tillack, Andreas F.; Robinson, Bruce H.; Haffner, Christian; Heni, Wolfgang; Hoessbacher, Claudia; Fedoryshyn, Yuriy; Salamin, Yannick; Baeuerle, Benedikt; Josten, Arne; Ayata, Masafumi; Koch, Ueli; Leuthold, Juerg; Dalton, Larry R.

2018-02-01

Multi-scale (correlated quantum and statistical mechanics) modeling methods have been advanced and employed to guide the improvement of organic electro-optic (OEO) materials, including by analyzing electric field poling induced electro-optic activity in nanoscopic plasmonic-organic hybrid (POH) waveguide devices. The analysis of in-device electro-optic activity emphasizes the importance of considering both the details of intermolecular interactions within organic electro-optic materials and interactions at interfaces between OEO materials and device architectures. Dramatic improvement in electro-optic device performance-including voltage-length performance, bandwidth, energy efficiency, and lower optical losses have been realized. These improvements are critical to applications in telecommunications, computing, sensor technology, and metrology. Multi-scale modeling methods illustrate the complexity of improving the electro-optic activity of organic materials, including the necessity of considering the trade-off between improving poling-induced acentric order through chromophore modification and the reduction of chromophore number density associated with such modification. Computational simulations also emphasize the importance of developing chromophore modifications that serve multiple purposes including matrix hardening for enhanced thermal and photochemical stability, control of matrix dimensionality, influence on material viscoelasticity, improvement of chromophore molecular hyperpolarizability, control of material dielectric permittivity and index of refraction properties, and control of material conductance. Consideration of new device architectures is critical to the implementation of chipscale integration of electronics and photonics and achieving the high bandwidths for applications such as next generation (e.g., 5G) telecommunications.

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error.

PubMed

Kazmierczak, Steven C; Leen, Todd K; Erdogmus, Deniz; Carreira-Perpinan, Miguel A

2007-01-01

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Micro-computed tomography pore-scale study of flow in porous media: Effect of voxel resolution

NASA Astrophysics Data System (ADS)

Shah, S. M.; Gray, F.; Crawshaw, J. P.; Boek, E. S.

2016-09-01

A fundamental understanding of flow in porous media at the pore-scale is necessary to be able to upscale average displacement processes from core to reservoir scale. The study of fluid flow in porous media at the pore-scale consists of two key procedures: Imaging - reconstruction of three-dimensional (3D) pore space images; and modelling such as with single and two-phase flow simulations with Lattice-Boltzmann (LB) or Pore-Network (PN) Modelling. Here we analyse pore-scale results to predict petrophysical properties such as porosity, single-phase permeability and multi-phase properties at different length scales. The fundamental issue is to understand the image resolution dependency of transport properties, in order to up-scale the flow physics from pore to core scale. In this work, we use a high resolution micro-computed tomography (micro-CT) scanner to image and reconstruct three dimensional pore-scale images of five sandstones (Bentheimer, Berea, Clashach, Doddington and Stainton) and five complex carbonates (Ketton, Estaillades, Middle Eastern sample 3, Middle Eastern sample 5 and Indiana Limestone 1) at four different voxel resolutions (4.4 μm, 6.2 μm, 8.3 μm and 10.2 μm), scanning the same physical field of view. Implementing three phase segmentation (macro-pore phase, intermediate phase and grain phase) on pore-scale images helps to understand the importance of connected macro-porosity in the fluid flow for the samples studied. We then compute the petrophysical properties for all the samples using PN and LB simulations in order to study the influence of voxel resolution on petrophysical properties. We then introduce a numerical coarsening scheme which is used to coarsen a high voxel resolution image (4.4 μm) to lower resolutions (6.2 μm, 8.3 μm and 10.2 μm) and study the impact of coarsening data on macroscopic and multi-phase properties. Numerical coarsening of high resolution data is found to be superior to using a lower resolution scan because it avoids the problem of partial volume effects and reduces the scaling effect by preserving the pore-space properties influencing the transport properties. This is evidently compared in this study by predicting several pore network properties such as number of pores and throats, average pore and throat radius and coordination number for both scan based analysis and numerical coarsened data.

A Re-Unification of Two Competing Models for Document Retrieval.

ERIC Educational Resources Information Center

Bodoff, David

1999-01-01

Examines query-oriented versus document-oriented information retrieval and feedback learning. Highlights include a reunification of the two approaches for probabilistic document retrieval and for vector space model (VSM) retrieval; learning in VSM and in probabilistic models; multi-dimensional scaling; and ongoing field studies. (LRW)

Accelerating large-scale simulation of seismic wave propagation by multi-GPUs and three-dimensional domain decomposition

NASA Astrophysics Data System (ADS)

Okamoto, Taro; Takenaka, Hiroshi; Nakamura, Takeshi; Aoki, Takayuki

2010-12-01

We adopted the GPU (graphics processing unit) to accelerate the large-scale finite-difference simulation of seismic wave propagation. The simulation can benefit from the high-memory bandwidth of GPU because it is a "memory intensive" problem. In a single-GPU case we achieved a performance of about 56 GFlops, which was about 45-fold faster than that achieved by a single core of the host central processing unit (CPU). We confirmed that the optimized use of fast shared memory and registers were essential for performance. In the multi-GPU case with three-dimensional domain decomposition, the non-contiguous memory alignment in the ghost zones was found to impose quite long time in data transfer between GPU and the host node. This problem was solved by using contiguous memory buffers for ghost zones. We achieved a performance of about 2.2 TFlops by using 120 GPUs and 330 GB of total memory: nearly (or more than) 2200 cores of host CPUs would be required to achieve the same performance. The weak scaling was nearly proportional to the number of GPUs. We therefore conclude that GPU computing for large-scale simulation of seismic wave propagation is a promising approach as a faster simulation is possible with reduced computational resources compared to CPUs.

Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education

ERIC Educational Resources Information Center

Schwalbe, Michelle Kristin

2010-01-01

This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…

The LSST Data Mining Research Agenda

NASA Astrophysics Data System (ADS)

Borne, K.; Becla, J.; Davidson, I.; Szalay, A.; Tyson, J. A.

2008-12-01

We describe features of the LSST science database that are amenable to scientific data mining, object classification, outlier identification, anomaly detection, image quality assurance, and survey science validation. The data mining research agenda includes: scalability (at petabytes scales) of existing machine learning and data mining algorithms; development of grid-enabled parallel data mining algorithms; designing a robust system for brokering classifications from the LSST event pipeline (which may produce 10,000 or more event alerts per night) multi-resolution methods for exploration of petascale databases; indexing of multi-attribute multi-dimensional astronomical databases (beyond spatial indexing) for rapid querying of petabyte databases; and more.

Scale of Unpredictability Beliefs: Reliability and Validity.

PubMed

Ross, Lisa Thomson; Short, Stephen D; Garofano, Marina

2016-11-16

Experiencing unpredictability in the environment has a variety of negative outcomes. However, these are difficult to ascertain due to the lack of a psychometrically sound measure of unpredictability beliefs. This article summarizes the development of the Scale of Unpredictability Beliefs (SUB), which assesses perceptions about unpredictability in one's life, in other people, and in the world. In Study I, college students (N = 305) responded to 68 potential items as well as other scales. Exploratory factor analysis yielded three internally consistent subscales (Self, People, and World; 16 items total). Higher SUB scores correlated with more childhood family unpredictability, greater likelihood of parental alcohol abuse, stronger causal uncertainty, and lower self-efficacy. In Study II, a confirmatory factor analysis supported the three-factor solution (N = 186 college students). SUB scores correlated with personality, childhood family unpredictability, and control beliefs. In most instances the SUB predicted family unpredictability and control beliefs beyond existing unpredictability measures. Study III confirmed the factor structure and replicated family unpredictability associations in an adult sample (N = 483). This article provides preliminary support for this new multi-dimensional, self-report assessment of unpredictability beliefs, and ideas for future research are discussed.

Towards a Holistic Cortical Thickness Descriptor: Heat Kernel-Based Grey Matter Morphology Signatures.

PubMed

Wang, Gang; Wang, Yalin

2017-02-15

In this paper, we propose a heat kernel based regional shape descriptor that may be capable of better exploiting volumetric morphological information than other available methods, thereby improving statistical power on brain magnetic resonance imaging (MRI) analysis. The mechanism of our analysis is driven by the graph spectrum and the heat kernel theory, to capture the volumetric geometry information in the constructed tetrahedral meshes. In order to capture profound brain grey matter shape changes, we first use the volumetric Laplace-Beltrami operator to determine the point pair correspondence between white-grey matter and CSF-grey matter boundary surfaces by computing the streamlines in a tetrahedral mesh. Secondly, we propose multi-scale grey matter morphology signatures to describe the transition probability by random walk between the point pairs, which reflects the inherent geometric characteristics. Thirdly, a point distribution model is applied to reduce the dimensionality of the grey matter morphology signatures and generate the internal structure features. With the sparse linear discriminant analysis, we select a concise morphology feature set with improved classification accuracies. In our experiments, the proposed work outperformed the cortical thickness features computed by FreeSurfer software in the classification of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment, on publicly available data from the Alzheimer's Disease Neuroimaging Initiative. The multi-scale and physics based volumetric structure feature may bring stronger statistical power than some traditional methods for MRI-based grey matter morphology analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Study of multi-dimensional radiative energy transfer in molecular gases

NASA Technical Reports Server (NTRS)

Liu, Jiwen; Tiwari, S. N.

1993-01-01

The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.

A multi-scale GIS and hydrodynamic modelling approach to fish passage assessment: Clarence and Shoalhaven Rivers, NSW Australia

NASA Astrophysics Data System (ADS)

Bonetti, Rita M.; Reinfelds, Ivars V.; Butler, Gavin L.; Walsh, Chris T.; Broderick, Tony J.; Chisholm, Laurie A.

2016-05-01

Natural barriers such as waterfalls, cascades, rapids and riffles limit the dispersal and in-stream range of migratory fish, yet little is known of the interplay between these gradient dependent landforms, their hydraulic characteristics and flow rates that facilitate fish passage. The resurgence of dam construction in numerous river basins world-wide provides impetus to the development of robust techniques for assessment of the effects of downstream flow regime changes on natural fish passage barriers and associated consequences as to the length of rivers available to migratory species. This paper outlines a multi-scale technique for quantifying the relative magnitude of natural fish passage barriers in river systems and flow rates that facilitate passage by fish. First, a GIS-based approach is used to quantify channel gradients for the length of river or reach under investigation from a high resolution DEM, setting the magnitude of identified passage barriers in a longer context (tens to hundreds of km). Second, LiDAR, topographic and bathymetric survey-based hydrodynamic modelling is used to assess flow rates that can be regarded as facilitating passage across specific barriers identified by the river to reach scale gradient analysis. Examples of multi-scale approaches to fish passage assessment for flood-flow and low-flow passage issues are provided from the Clarence and Shoalhaven Rivers, NSW, Australia. In these river systems, passive acoustic telemetry data on actual movements and migrations by Australian bass (Macquaria novemaculeata) provide a means of validating modelled assessments of flow rates associated with successful fish passage across natural barriers. Analysis of actual fish movements across passage barriers in these river systems indicates that two dimensional hydraulic modelling can usefully quantify flow rates associated with the facilitation of fish passage across natural barriers by a majority of individual fishes for use in management decisions regarding environmental or instream flows.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Applications

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1998-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Application

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1997-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

LHC multijet events as a probe for anomalous dimension-six gluon interactions

DOE PAGES

Krauss, Frank; Kuttimalai, Silvan; Plehn, Tilman

2017-02-22

Higher-dimensional multigluon interactions affect essentially all effective Lagrangian analyses at the LHC. We show that, contrary to common lore, such operators are best constrained in multijet production. Our limit on the corresponding new physics scale in the multi-TeV range exceeds the typical reach of global dimension-six Higgs boson and top analyses. As a result, this implies that the pure Yang-Mills operator can safely be neglected in almost all specific higher-dimensional analyses at Run II.

LHC multijet events as a probe for anomalous dimension-six gluon interactions

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

Krauss, Frank; Kuttimalai, Silvan; Plehn, Tilman

Higher-dimensional multigluon interactions affect essentially all effective Lagrangian analyses at the LHC. We show that, contrary to common lore, such operators are best constrained in multijet production. Our limit on the corresponding new physics scale in the multi-TeV range exceeds the typical reach of global dimension-six Higgs boson and top analyses. As a result, this implies that the pure Yang-Mills operator can safely be neglected in almost all specific higher-dimensional analyses at Run II.

Duke Workshop on High-Dimensional Data Sensing and Analysis

DTIC Science & Technology

2015-05-06

Bayesian sparse factor analysis formulation of Chen et al . ( 2011 ) this work develops multi-label PCA (MLPCA), a generative dimension reduction...version of this problem was recently treated by Banerjee et al . [1], Ravikumar et al . [2], Kolar and Xing [3], and Ho ̈fling and Tibshirani [4]. As...Not applicable. Final Report Duke Workshop on High-Dimensional Data Sensing and Analysis Workshop Dates: July 26-28, 2011

Situation exploration in a persistent surveillance system with multidimensional data

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.

2013-03-01

There is an emerging need for fusing hard and soft sensor data in an efficient surveillance system to provide accurate estimation of situation awareness. These mostly abstract, multi-dimensional and multi-sensor data pose a great challenge to the user in performing analysis of multi-threaded events efficiently and cohesively. To address this concern an interactive Visual Analytics (VA) application is developed for rapid assessment and evaluation of different hypotheses based on context-sensitive ontology spawn from taxonomies describing human/human and human/vehicle/object interactions. A methodology is described here for generating relevant ontology in a Persistent Surveillance System (PSS) and demonstrates how they can be utilized in the context of PSS to track and identify group activities pertaining to potential threats. The proposed VA system allows for visual analysis of raw data as well as metadata that have spatiotemporal representation and content-based implications. Additionally in this paper, a technique for rapid search of tagged information contingent to ranking and confidence is explained for analysis of multi-dimensional data. Lastly the issue of uncertainty associated with processing and interpretation of heterogeneous data is also addressed.

MULTI-SCALE GRID DEFINITION IMPACTS ON REGIONAL, THREE-DIMENSIONAL AIR QUALITY MODEL PREDICTIONS AND PERFORMANCE. (R825821)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

3MRA: A MULTI-MEDIA HUMAN AND ECOLOGICAL MODELING SYSTEM FOR SITE-SPECIFIC TO NATIONAL SCALE REGULATORY APPLICATIONS

EPA Science Inventory

3MRA provides a technology that fully integrates the full dimensionality of human and ecological exposure and risk assessment, thus allowing regulatory decisions a more complete expression of potential adverse health effects related to the disposal and reuse of contaminated waste...

Evidence for a Multi-Dimensional Latent Structural Model of Externalizing Disorders

ERIC Educational Resources Information Center

Witkiewitz, Katie; King, Kevin; McMahon, Robert J.; Wu, Johnny; Luk, Jeremy; Bierman, Karen L.; Coie, John D.; Dodge, Kenneth A.; Greenberg, Mark T.; Lochman, John E.; Pinderhughes, Ellen E.

2013-01-01

Strong associations between conduct disorder (CD), antisocial personality disorder (ASPD) and substance use disorders (SUD) seem to reflect a general vulnerability to externalizing behaviors. Recent studies have characterized this vulnerability on a continuous scale, rather than as distinct categories, suggesting that the revision of the…

Ferroelectric nanostructure having switchable multi-stable vortex states

DOEpatents

Naumov, Ivan I [Fayetteville, AR; Bellaiche, Laurent M [Fayetteville, AR; Prosandeev, Sergey A [Fayetteville, AR; Ponomareva, Inna V [Fayetteville, AR; Kornev, Igor A [Fayetteville, AR

2009-09-22

A ferroelectric nanostructure formed as a low dimensional nano-scale ferroelectric material having at least one vortex ring of polarization generating an ordered toroid moment switchable between multi-stable states. A stress-free ferroelectric nanodot under open-circuit-like electrical boundary conditions maintains such a vortex structure for their local dipoles when subject to a transverse inhomogeneous static electric field controlling the direction of the macroscopic toroidal moment. Stress is also capable of controlling the vortex's chirality, because of the electromechanical coupling that exists in ferroelectric nanodots.

Computer simulation of ion beam analysis of laterally inhomogeneous materials

NASA Astrophysics Data System (ADS)

Mayer, M.

2016-03-01

The program STRUCTNRA for the simulation of ion beam analysis charged particle spectra from arbitrary two-dimensional distributions of materials is described. The code is validated by comparison to experimental backscattering data from a silicon grating on tantalum at different orientations and incident angles. Simulated spectra for several types of rough thin layers and a chessboard-like arrangement of materials as example for a multi-phase agglomerate material are presented. Ambiguities between back-scattering spectra from two-dimensional and one-dimensional sample structures are discussed.

Measuring strategies for learning regulation in medical education: scale reliability and dimensionality in a Swedish sample.

PubMed

Edelbring, Samuel

2012-08-15

The degree of learners' self-regulated learning and dependence on external regulation influence learning processes in higher education. These regulation strategies are commonly measured by questionnaires developed in other settings than in which they are being used, thereby requiring renewed validation. The aim of this study was to psychometrically evaluate the learning regulation strategy scales from the Inventory of Learning Styles with Swedish medical students (N = 206). The regulation scales were evaluated regarding their reliability, scale dimensionality and interrelations. The primary evaluation focused on dimensionality and was performed with Mokken scale analysis. To assist future scale refinement, additional item analysis, such as item-to-scale correlations, was performed. Scale scores in the Swedish sample displayed good reliability in relation to published results: Cronbach's alpha: 0.82, 0.72, and 0.65 for self-regulation, external regulation and lack of regulation scales respectively. The dimensionalities in scales were adequate for self-regulation and its subscales, whereas external regulation and lack of regulation displayed less unidimensionality. The established theoretical scales were largely replicated in the exploratory analysis. The item analysis identified two items that contributed little to their respective scales. The results indicate that these scales have an adequate capacity for detecting the three theoretically proposed learning regulation strategies in the medical education sample. Further construct validity should be sought by interpreting scale scores in relation to specific learning activities. Using established scales for measuring students' regulation strategies enables a broad empirical base for increasing knowledge on regulation strategies in relation to different disciplinary settings and contributes to theoretical development.

Synchronization and an application of a novel fractional order King Cobra chaotic system

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

Muthukumar, P., E-mail: muthukumardgl@gmail.com; Balasubramaniam, P., E-mail: balugru@gmail.com; Ratnavelu, K., E-mail: kuru052001@gmail.com

2014-09-01

In this paper, we design a new three dimensional King Cobra face shaped fractional order chaotic system. The multi-scale synchronization scheme of two fractional order chaotic systems is described. The necessary conditions for the multi-scale synchronization of two identical fractional order King Cobra chaotic systems are derived through feedback control. A new cryptosystem is proposed for an image encryption and decryption by using synchronized fractional order King Cobra chaotic systems with the supports of multiple cryptographic assumptions. The security of the proposed cryptosystem is analyzed by the well known algebraic attacks. Numerical simulations are given to show the effectiveness ofmore » the proposed theoretical results.« less

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

Local variance for multi-scale analysis in geomorphometry.

PubMed

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-07-15

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements.

Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

Investigating Hydrocarbon Seep Environments with High-Resolution, Three-Dimensional Geographic Visualizations.

NASA Astrophysics Data System (ADS)

Doolittle, D. F.; Gharib, J. J.; Mitchell, G. A.

2015-12-01

Detailed photographic imagery and bathymetric maps of the seafloor acquired by deep submergence vehicles such as Autonomous Underwater Vehicles (AUV) and Remotely Operated Vehicles (ROV) are expanding how scientists and the public view and ultimately understand the seafloor and the processes that modify it. Several recently acquired optical and acoustic datasets, collected during ECOGIG (Ecosystem Impacts of Oil and Gas Inputs to the Gulf) and other Gulf of Mexico expeditions using the National Institute for Undersea Science Technology (NIUST) Eagle Ray, and Mola Mola AUVs, have been fused with lower resolution data to create unique three-dimensional geovisualizations. Included in these data are multi-scale and multi-resolution visualizations over hydrocarbon seeps and seep related features. Resolution of the data range from 10s of mm to 10s of m. When multi-resolution data is integrated into a single three-dimensional visual environment, new insights into seafloor and seep processes can be obtained from the intuitive nature of three-dimensional data exploration. We provide examples and demonstrate how integration of multibeam bathymetry, seafloor backscatter data, sub-bottom profiler data, textured photomosaics, and hull-mounted multibeam acoustic midwater imagery are made into a series a three-dimensional geovisualizations of actively seeping sites and associated chemosynthetic communities. From these combined and merged datasets, insights on seep community structure, morphology, ecology, fluid migration dynamics, and process geomorphology can be investigated from new spatial perspectives. Such datasets also promote valuable inter-comparisons of sensor resolution and performance.

Accessing Multi-Dimensional Images and Data Cubes in the Virtual Observatory

NASA Astrophysics Data System (ADS)

Tody, Douglas; Plante, R. L.; Berriman, G. B.; Cresitello-Dittmar, M.; Good, J.; Graham, M.; Greene, G.; Hanisch, R. J.; Jenness, T.; Lazio, J.; Norris, P.; Pevunova, O.; Rots, A. H.

2014-01-01

Telescopes across the spectrum are routinely producing multi-dimensional images and datasets, such as Doppler velocity cubes, polarization datasets, and time-resolved “movies.” Examples of current telescopes producing such multi-dimensional images include the JVLA, ALMA, and the IFU instruments on large optical and near-infrared wavelength telescopes. In the near future, both the LSST and JWST will also produce such multi-dimensional images routinely. High-energy instruments such as Chandra produce event datasets that are also a form of multi-dimensional data, in effect being a very sparse multi-dimensional image. Ensuring that the data sets produced by these telescopes can be both discovered and accessed by the community is essential and is part of the mission of the Virtual Observatory (VO). The Virtual Astronomical Observatory (VAO, http://www.usvao.org/), in conjunction with its international partners in the International Virtual Observatory Alliance (IVOA), has developed a protocol and an initial demonstration service designed for the publication, discovery, and access of arbitrarily large multi-dimensional images. The protocol describing multi-dimensional images is the Simple Image Access Protocol, version 2, which provides the minimal set of metadata required to characterize a multi-dimensional image for its discovery and access. A companion Image Data Model formally defines the semantics and structure of multi-dimensional images independently of how they are serialized, while providing capabilities such as support for sparse data that are essential to deal effectively with large cubes. A prototype data access service has been deployed and tested, using a suite of multi-dimensional images from a variety of telescopes. The prototype has demonstrated the capability to discover and remotely access multi-dimensional data via standard VO protocols. The prototype informs the specification of a protocol that will be submitted to the IVOA for approval, with an operational data cube service to be delivered in mid-2014. An associated user-installable VO data service framework will provide the capabilities required to publish VO-compatible multi-dimensional images or data cubes.

Quadratic Frequency Modulation Signals Parameter Estimation Based on Two-Dimensional Product Modified Parameterized Chirp Rate-Quadratic Chirp Rate Distribution.

PubMed

Qu, Zhiyu; Qu, Fuxin; Hou, Changbo; Jing, Fulong

2018-05-19

In an inverse synthetic aperture radar (ISAR) imaging system for targets with complex motion, the azimuth echo signals of the target are always modeled as multicomponent quadratic frequency modulation (QFM) signals. The chirp rate (CR) and quadratic chirp rate (QCR) estimation of QFM signals is very important to solve the ISAR image defocus problem. For multicomponent QFM (multi-QFM) signals, the conventional QR and QCR estimation algorithms suffer from the cross-term and poor anti-noise ability. This paper proposes a novel estimation algorithm called a two-dimensional product modified parameterized chirp rate-quadratic chirp rate distribution (2D-PMPCRD) for QFM signals parameter estimation. The 2D-PMPCRD employs a multi-scale parametric symmetric self-correlation function and modified nonuniform fast Fourier transform-Fast Fourier transform to transform the signals into the chirp rate-quadratic chirp rate (CR-QCR) domains. It can greatly suppress the cross-terms while strengthening the auto-terms by multiplying different CR-QCR domains with different scale factors. Compared with high order ambiguity function-integrated cubic phase function and modified Lv's distribution, the simulation results verify that the 2D-PMPCRD acquires higher anti-noise performance and obtains better cross-terms suppression performance for multi-QFM signals with reasonable computation cost.

Optimization of coupled multiphysics methodology for safety analysis of pebble bed modular reactor

NASA Astrophysics Data System (ADS)

Mkhabela, Peter Tshepo

The research conducted within the framework of this PhD thesis is devoted to the high-fidelity multi-physics (based on neutronics/thermal-hydraulics coupling) analysis of Pebble Bed Modular Reactor (PBMR), which is a High Temperature Reactor (HTR). The Next Generation Nuclear Plant (NGNP) will be a HTR design. The core design and safety analysis methods are considerably less developed and mature for HTR analysis than those currently used for Light Water Reactors (LWRs). Compared to LWRs, the HTR transient analysis is more demanding since it requires proper treatment of both slower and much longer transients (of time scale in hours and days) and fast and short transients (of time scale in minutes and seconds). There is limited operation and experimental data available for HTRs for validation of coupled multi-physics methodologies. This PhD work developed and verified reliable high fidelity coupled multi-physics models subsequently implemented in robust, efficient, and accurate computational tools to analyse the neutronics and thermal-hydraulic behaviour for design optimization and safety evaluation of PBMR concept The study provided a contribution to a greater accuracy of neutronics calculations by including the feedback from thermal hydraulics driven temperature calculation and various multi-physics effects that can influence it. Consideration of the feedback due to the influence of leakage was taken into account by development and implementation of improved buckling feedback models. Modifications were made in the calculation procedure to ensure that the xenon depletion models were accurate for proper interpolation from cross section tables. To achieve this, the NEM/THERMIX coupled code system was developed to create the system that is efficient and stable over the duration of transient calculations that last over several tens of hours. Another achievement of the PhD thesis was development and demonstration of full-physics, three-dimensional safety analysis methodology for the PBMR to provide reference solutions. Investigation of different aspects of the coupled methodology and development of efficient kinetics treatment for the PBMR were carried out, which accounts for all feedback phenomena in an efficient manner. The OECD/NEA PBMR-400 coupled code benchmark was used as a test matrix for the proposed investigations. The integrated thermal-hydraulics and neutronics (multi-physics) methods were extended to enable modeling of a wider range of transients pertinent to the PBMR. First, the effect of the spatial mapping schemes (spatial coupling) was studied and quantified for different types of transients, which resulted in implementation of improved mapping methodology based on user defined criteria. The second aspect that was studied and optimized is the temporal coupling and meshing schemes between the neutronics and thermal-hydraulics time step selection algorithms. The coupled code convergence was achieved supplemented by application of methods to accelerate it. Finally, the modeling of all feedback phenomena in PBMRs was investigated and a novel treatment of cross-section dependencies was introduced for improving the representation of cross-section variations. The added benefit was that in the process of studying and improving the coupled multi-physics methodology more insight was gained into the physics and dynamics of PBMR, which will help also to optimize the PBMR design and improve its safety. One unique contribution of the PhD research is the investigation of the importance of the correct representation of the three-dimensional (3-D) effects in the PBMR analysis. The performed studies demonstrated that explicit 3-D modeling of control rod movement is superior and removes the errors associated with the grey curtain (2-D homogenized) approximation.

Multi-dimensional photonic states from a quantum dot

NASA Astrophysics Data System (ADS)

Lee, J. P.; Bennett, A. J.; Stevenson, R. M.; Ellis, D. J. P.; Farrer, I.; Ritchie, D. A.; Shields, A. J.

2018-04-01

Quantum states superposed across multiple particles or degrees of freedom offer an advantage in the development of quantum technologies. Creating these states deterministically and with high efficiency is an ongoing challenge. A promising approach is the repeated excitation of multi-level quantum emitters, which have been shown to naturally generate light with quantum statistics. Here we describe how to create one class of higher dimensional quantum state, a so called W-state, which is superposed across multiple time bins. We do this by repeated Raman scattering of photons from a charged quantum dot in a pillar microcavity. We show this method can be scaled to larger dimensions with no reduction in coherence or single-photon character. We explain how to extend this work to enable the deterministic creation of arbitrary time-bin encoded qudits.

Dimensionality of the Hospital Anxiety and Depression Scale (HADS) in Cardiac Patients: Comparison of Mokken Scale Analysis and Factor Analysis

ERIC Educational Resources Information Center

Emons, Wilco H. M.; Sijtsma, Klaas; Pedersen, Susanne S.

2012-01-01

The Hospital Anxiety and Depression Scale (HADS) measures anxiety and depressive symptoms and is widely used in clinical and nonclinical populations. However, there is some debate about the number of dimensions represented by the HADS. In a sample of 534 Dutch cardiac patients, this study examined (a) the dimensionality of the HADS using Mokken…

Enhancement of low visibility aerial images using histogram truncation and an explicit Retinex representation for balancing contrast and color consistency

NASA Astrophysics Data System (ADS)

Liu, Changjiang; Cheng, Irene; Zhang, Yi; Basu, Anup

2017-06-01

This paper presents an improved multi-scale Retinex (MSR) based enhancement for ariel images under low visibility. For traditional multi-scale Retinex, three scales are commonly employed, which limits its application scenarios. We extend our research to a general purpose enhanced method, and design an MSR with more than three scales. Based on the mathematical analysis and deductions, an explicit multi-scale representation is proposed that balances image contrast and color consistency. In addition, a histogram truncation technique is introduced as a post-processing strategy to remap the multi-scale Retinex output to the dynamic range of the display. Analysis of experimental results and comparisons with existing algorithms demonstrate the effectiveness and generality of the proposed method. Results on image quality assessment proves the accuracy of the proposed method with respect to both objective and subjective criteria.

Bioinspired Fabrication of one dimensional graphene fiber with collection of droplets application.

PubMed

Song, Yun-Yun; Liu, Yan; Jiang, Hao-Bo; Li, Shu-Yi; Kaya, Cigdem; Stegmaier, Thomas; Han, Zhi-Wu; Ren, Lu-Quan

2017-09-21

We designed a kind of smart bioinspired fiber with multi-gradient and multi-scale spindle knots by combining polydimethylsiloxane (PDMS) and graphene oxide (GO). Multilayered graphene structures can produce obvious wettability change after laser etching due to increased roughness. We demonstrate that the cooperation between curvature and the controllable wettability play an important role in water gathering, which regulate effectively the motion of tiny water droplets. In addition, due to the effective cooperation of multi-gradient and multi-scale hydrophilic spindle knots, the length of the three-phase contact line (TCL) can be longer, which makes a great contribution to the improvement of collecting efficiency and water-hanging ability. This study offers a novel insight into the design of smart materials that may control the transport of tiny drops reversibly in directions, which could potentially be extended to the realms of in microfluidics, fog harvesting filtration and condensers designs, and further increase water collection efficiency and hanging ability.

Coupled multi-disciplinary composites behavior simulation

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Murthy, Pappu L. N.; Chamis, Christos C.

1993-01-01

The capabilities of the computer code CSTEM (Coupled Structural/Thermal/Electro-Magnetic Analysis) are discussed and demonstrated. CSTEM computationally simulates the coupled response of layered multi-material composite structures subjected to simultaneous thermal, structural, vibration, acoustic, and electromagnetic loads and includes the effect of aggressive environments. The composite material behavior and structural response is determined at its various inherent scales: constituents (fiber/matrix), ply, laminate, and structural component. The thermal and mechanical properties of the constituents are considered to be nonlinearly dependent on various parameters such as temperature and moisture. The acoustic and electromagnetic properties also include dependence on vibration and electromagnetic wave frequencies, respectively. The simulation is based on a three dimensional finite element analysis in conjunction with composite mechanics and with structural tailoring codes, and with acoustic and electromagnetic analysis methods. An aircraft engine composite fan blade is selected as a typical structural component to demonstrate the CSTEM capabilities. Results of various coupled multi-disciplinary heat transfer, structural, vibration, acoustic, and electromagnetic analyses for temperature distribution, stress and displacement response, deformed shape, vibration frequencies, mode shapes, acoustic noise, and electromagnetic reflection from the fan blade are discussed for their coupled effects in hot and humid environments. Collectively, these results demonstrate the effectiveness of the CSTEM code in capturing the coupled effects on the various responses of composite structures subjected to simultaneous multiple real-life loads.

Arrowland v1.0

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

BIRKEL, GARRETT; GARCIA MARTIN, HECTOR; MORRELL, WILLIAM

"Arrowland" is a web-based software application primarily for mapping, integrating and visualizing a variety of metabolism data of living organisms, including but not limited to metabolomics, proteomics, transcriptomics and fluxomics. This software application makes multi-omics data analysis intuitive and interactive. It improves data sharing and communication by enabling users to visualize their omics data using a web browser (on a PC or mobile device). It increases user's productivity by simplifying multi-omics data analysis using well developed maps as a guide. Users using this tool can gain insights into their data sets that would be difficult or even impossible to teasemore » out by looking at raw number, or using their currently existing toolchains to generate static single-use maps. Arrowland helps users save time by visualizing relative changes in different conditions or over time, and helps users to produce more significant insights faster. Preexisting maps decrease the learning curve for beginners in the omics field. Sets of multi-omics data are presented in the browser, as a two-dimensional flowchart resembling a map, with varying levels of detail information, based on the scaling of the map. Users can pan and zoom to explore different maps, compare maps, upload their own research data sets onto desired maps, alter map appearance in ways that facilitate interpretation, visualization and analysis of the given data, and export data, reports and actionable items to help the user initiative.« less

Persistent Topology and Metastable State in Conformational Dynamics

PubMed Central

Chang, Huang-Wei; Bacallado, Sergio; Pande, Vijay S.; Carlsson, Gunnar E.

2013-01-01

The large amount of molecular dynamics simulation data produced by modern computational models brings big opportunities and challenges to researchers. Clustering algorithms play an important role in understanding biomolecular kinetics from the simulation data, especially under the Markov state model framework. However, the ruggedness of the free energy landscape in a biomolecular system makes common clustering algorithms very sensitive to perturbations of the data. Here, we introduce a data-exploratory tool which provides an overview of the clustering structure under different parameters. The proposed Multi-Persistent Clustering analysis combines insights from recent studies on the dynamics of systems with dominant metastable states with the concept of multi-dimensional persistence in computational topology. We propose to explore the clustering structure of the data based on its persistence on scale and density. The analysis provides a systematic way to discover clusters that are robust to perturbations of the data. The dominant states of the system can be chosen with confidence. For the clusters on the borderline, the user can choose to do more simulation or make a decision based on their structural characteristics. Furthermore, our multi-resolution analysis gives users information about the relative potential of the clusters and their hierarchical relationship. The effectiveness of the proposed method is illustrated in three biomolecules: alanine dipeptide, Villin headpiece, and the FiP35 WW domain. PMID:23565139

The impact of pediatric nephrotic syndrome on parents' health-related quality of life and family functioning: an assessment made by the PedsQL 4.0 family impact module.

PubMed

Mishra, Kirtisudha; Ramachandran, Smita; Firdaus, Saima; Rath, Bimbadhar

2015-03-01

The multi-dimensional impact on the quality of life (QOL) of families of children with the nephrotic syndrome (NS) has not been studied sufficiently in the literature. We aimed to study this aspect and the predictors of poor QOL among Indian families having children with NS. A cross-sectional study was conducted to compare the parents of children with chronic NS on treatment for at least one year with parents of a matched healthy control group. The parents of both groups were asked to complete the standard self-administered multi-dimensional questionnaire of Pediatric Quality of Life Inventory 4 (PedsQL TM ) Family Impact Module (FIM). Descriptive and analytical statistics were performed to compare scores between the two groups. Possible predictors of poor outcome in each of the summary scales among the cases were assessed by both univariate and multivariate analysis. The parents of 61 cases and 72 controls completed the PedsQL TM FIM questionnaire. The scores in each of the categories, namely FIM Total Scale Score, Parent HRQOL Summary Score, Family Functioning Summary Score and eight individual domains, were found to be significantly higher among controls. Female gender of the affected child was an independent risk factor for poor Family Functioning Summary Score. Also, presence of serious complications during the course of the disease independently predicted poor Total FIM and Parent HRQOL Summary Scores. Even a relatively benign and potentially curable chronic disorder in children, like the NS, can disturb the QOL of parents in multiple domains of functioning.

Empirical validation of the English version of the Fear of Cancer Recurrence Inventory.

PubMed

Lebel, Sophie; Simard, Sebastien; Harris, Cheryl; Feldstain, Andrea; Beattie, Sara; McCallum, Megan; Lefebvre, Monique; Savard, Josée; Devins, Gerald M

2016-02-01

Cancer patients report that help in managing fear of cancer recurrence (FCR) is one of their greatest unmet needs. Research on FCR has been limited by the very few validated, multi-dimensional measures of this construct. One exception is the Fear of Cancer Recurrence Inventory (FCRI), originally developed and empirically validated in French. The present study validated the English version of the FCRI. The FCRI was translated into English using a forward-backward translation procedure and pilot-tested with 17 English-speaking cancer patients. Cross-cultural equivalency of the French and English versions was established by administering both forms to 42 bilingual cancer patients. Last, 350 English-speaking breast, colon, prostate, or lung cancer patients were asked to complete the FCRI. A subsample (n = 135) was mailed the FCRI again one month later to evaluate test-retest reliability. The English translation of the FCRI was well accepted by participants. There was no item-bias when comparing bilingual participants' answers on both versions. A confirmatory factor analysis supported the hypothesized seven-factor structure. The English version has high internal consistency (α = .96 for the total scale and .71-.94 for the subscales) and test-retest reliability (r = .88 for the total scale and 56-.87 for the subscales). The English version of the FCRI is a reliable and valid measure of FCR applicable to breast, colon, prostate, and lung cancer patients. Its multi-dimensional nature makes it an attractive research and clinical tool to further our knowledge of FCR.

Some applications of the multi-dimensional fractional order for the Riemann-Liouville derivative

NASA Astrophysics Data System (ADS)

Ahmood, Wasan Ajeel; Kiliçman, Adem

2017-01-01

In this paper, the aim of this work is to study theorem for the one-dimensional space-time fractional deriative, generalize some function for the one-dimensional fractional by table represents the fractional Laplace transforms of some elementary functions to be valid for the multi-dimensional fractional Laplace transform and give the definition of the multi-dimensional fractional Laplace transform. This study includes that, dedicate the one-dimensional fractional Laplace transform for functions of only one independent variable and develop of the one-dimensional fractional Laplace transform to multi-dimensional fractional Laplace transform based on the modified Riemann-Liouville derivative.

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Time and length scales within a fire and implications for numerical simulation

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

TIESZEN,SHELDON R.

2000-02-02

A partial non-dimensionalization of the Navier-Stokes equations is used to obtain order of magnitude estimates of the rate-controlling transport processes in the reacting portion of a fire plume as a function of length scale. Over continuum length scales, buoyant times scales vary as the square root of the length scale; advection time scales vary as the length scale, and diffusion time scales vary as the square of the length scale. Due to the variation with length scale, each process is dominant over a given range. The relationship of buoyancy and baroclinc vorticity generation is highlighted. For numerical simulation, first principlesmore » solution for fire problems is not possible with foreseeable computational hardware in the near future. Filtered transport equations with subgrid modeling will be required as two to three decades of length scale are captured by solution of discretized conservation equations. By whatever filtering process one employs, one must have humble expectations for the accuracy obtainable by numerical simulation for practical fire problems that contain important multi-physics/multi-length-scale coupling with up to 10 orders of magnitude in length scale.« less

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

PubMed Central

Wang, Guohua; Liu, Qiong

2015-01-01

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

PubMed

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Three dimensional profile measurement using multi-channel detector MVM-SEM

NASA Astrophysics Data System (ADS)

Yoshikawa, Makoto; Harada, Sumito; Ito, Keisuke; Murakawa, Tsutomu; Shida, Soichi; Matsumoto, Jun; Nakamura, Takayuki

2014-07-01

In next generation lithography (NGL) for the 1x nm node and beyond, the three dimensional (3D) shape measurements such as side wall angle (SWA) and height of feature on photomask become more critical for the process control. Until today, AFM (Atomic Force Microscope), X-SEM (cross-section Scanning Electron Microscope) and TEM (Transmission Electron Microscope) tools are normally used for 3D measurements, however, these techniques require time-consuming preparation and observation. And both X-SEM and TEM are destructive measurement techniques. This paper presents a technology for quick and non-destructive 3D shape analysis using multi-channel detector MVM-SEM (Multi Vision Metrology SEM), and also reports its accuracy and precision.

Multi-Scale Measures of Rugosity, Slope and Aspect from Benthic Stereo Image Reconstructions

PubMed Central

Friedman, Ariell; Pizarro, Oscar; Williams, Stefan B.; Johnson-Roberson, Matthew

2012-01-01

This paper demonstrates how multi-scale measures of rugosity, slope and aspect can be derived from fine-scale bathymetric reconstructions created from geo-referenced stereo imagery. We generate three-dimensional reconstructions over large spatial scales using data collected by Autonomous Underwater Vehicles (AUVs), Remotely Operated Vehicles (ROVs), manned submersibles and diver-held imaging systems. We propose a new method for calculating rugosity in a Delaunay triangulated surface mesh by projecting areas onto the plane of best fit using Principal Component Analysis (PCA). Slope and aspect can be calculated with very little extra effort, and fitting a plane serves to decouple rugosity from slope. We compare the results of the virtual terrain complexity calculations with experimental results using conventional in-situ measurement methods. We show that performing calculations over a digital terrain reconstruction is more flexible, robust and easily repeatable. In addition, the method is non-contact and provides much less environmental impact compared to traditional survey techniques. For diver-based surveys, the time underwater needed to collect rugosity data is significantly reduced and, being a technique based on images, it is possible to use robotic platforms that can operate beyond diver depths. Measurements can be calculated exhaustively at multiple scales for surveys with tens of thousands of images covering thousands of square metres. The technique is demonstrated on data gathered by a diver-rig and an AUV, on small single-transect surveys and on a larger, dense survey that covers over . Stereo images provide 3D structure as well as visual appearance, which could potentially feed into automated classification techniques. Our multi-scale rugosity, slope and aspect measures have already been adopted in a number of marine science studies. This paper presents a detailed description of the method and thoroughly validates it against traditional in-situ measurements. PMID:23251370

Large scale and cloud-based multi-model analytics experiments on climate change data in the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Płóciennik, Marcin; Doutriaux, Charles; Blanquer, Ignacio; Barbera, Roberto; Donvito, Giacinto; Williams, Dean N.; Anantharaj, Valentine; Salomoni, Davide D.; Aloisio, Giovanni

2017-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated, such as the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). A case study on climate models intercomparison data analysis addressing several classes of multi-model experiments is being implemented in the context of the EU H2020 INDIGO-DataCloud project. Such experiments require the availability of large amount of data (multi-terabyte order) related to the output of several climate models simulations as well as the exploitation of scientific data management tools for large-scale data analytics. More specifically, the talk discusses in detail a use case on precipitation trend analysis in terms of requirements, architectural design solution, and infrastructural implementation. The experiment has been tested and validated on CMIP5 datasets, in the context of a large scale distributed testbed across EU and US involving three ESGF sites (LLNL, ORNL, and CMCC) and one central orchestrator site (PSNC). The general "environment" of the case study relates to: (i) multi-model data analysis inter-comparison challenges; (ii) addressed on CMIP5 data; and (iii) which are made available through the IS-ENES/ESGF infrastructure. The added value of the solution proposed in the INDIGO-DataCloud project are summarized in the following: (i) it implements a different paradigm (from client- to server-side); (ii) it intrinsically reduces data movement; (iii) it makes lightweight the end-user setup; (iv) it fosters re-usability (of data, final/intermediate products, workflows, sessions, etc.) since everything is managed on the server-side; (v) it complements, extends and interoperates with the ESGF stack; (vi) it provides a "tool" for scientists to run multi-model experiments, and finally; and (vii) it can drastically reduce the time-to-solution for these experiments from weeks to hours. At the time the contribution is being written, the proposed testbed represents the first concrete implementation of a distributed multi-model experiment in the ESGF/CMIP context joining server-side and parallel processing, end-to-end workflow management and cloud computing. As opposed to the current scenario based on search & discovery, data download, and client-based data analysis, the INDIGO-DataCloud architectural solution described in this contribution addresses the scientific computing & analytics requirements by providing a paradigm shift based on server-side and high performance big data frameworks jointly with two-level workflow management systems realized at the PaaS level via a cloud infrastructure.

A cross-national study on the multidimensional characteristics of the five-item psychological demands scale of the Job Content Questionnaire.

PubMed

Choi, BongKyoo; Kawakami, Norito; Chang, SeiJin; Koh, SangBaek; Bjorner, Jakob; Punnett, Laura; Karasek, Robert

2008-01-01

The five-item psychological demands scale of the Job Content Questionnaire (JCQ) has been assumed to be one-dimensional in practice. To examine whether the scale has sufficient internal consistency and external validity to be treated as a single scale, using the cross-national JCQ datasets from the United States, Korea, and Japan. Exploratory factor analyses with 22 JCQ items, confirmatory factor analyses with the five psychological demands items, and correlations analyses with mental health indexes. Generally, exploratory factor analyses displayed the predicted demand/control/support structure with three and four factors extracted. However, at more detailed levels of exploratory and confirmatory factor analyses, the demands scale showed clear evidence of multi-factor structure. The correlations of items and subscales of the demands scale with mental health indexes were similar to those of the full scale in the Korean and Japanese datasets, but not in the U.S. data. In 4 out of 16 sub-samples of the U.S. data, several significant correlations of the components of the demands scale with job dissatisfaction and life dissatisfaction were obscured by the full scale. The multidimensionality of the psychological demands scale should be considered in psychometric analysis and interpretation, occupational epidemiologic studies, and future scale extension.

MEETING IN TUCSON: 3MRA: A MULTI-MEDIA HUMAN AND ECOLOGICAL MODELING SYSTEM FOR SITE-SPECIFIC TO NATIONAL SCALE REGULATORY APPLICATIONS

EPA Science Inventory

3MRA provides a technology that fully integrates the full dimensionality of human and ecological exposure and risk assessment, thus allowing regulatory decisions a more complete expression of potential adverse health effects related to the disposal and reuse of contaminated waste...

Multi-Dimensional Scaling based grouping of known complexes and intelligent protein complex detection.

PubMed

Rehman, Zia Ur; Idris, Adnan; Khan, Asifullah

2018-06-01

Protein-Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.

The multi-dimensional measure of informed choice: a validation study.

PubMed

Michie, Susan; Dormandy, Elizabeth; Marteau, Theresa M

2002-09-01

The aim of this prospective study is to assess the reliability and validity of a multi-dimensional measure of informed choice (MMIC). Participants were 225 pregnant women in two general hospitals in the UK, women receiving low-risk results following serum screening for Down syndrome. The MMIC was administered before testing and the Ottawa Decisional Conflict Scale was administered 6 weeks later. The component scales of the MMIC, knowledge and attitude, were internally consistent (alpha values of 0.68 and 0.78, respectively). Those who made a choice categorised as informed using the MMIC rated their decision 6 weeks later as being more informed, better supported and of higher quality than women whose choice was categorised as uninformed. This provides evidence of predictive validity, whilst the lack of association between the MMIC and anxiety shows construct (discriminant) validity. Thus, the MMIC has been shown to be psychometrically robust in pregnant women offered the choice to undergo prenatal screening for Down syndrome and receiving a low-risk result. Replication of this finding in other groups, facing other decisions, with other outcomes, should be assessed in future research.

Quantitative analysis of voids in percolating structures in two-dimensional N-body simulations

NASA Technical Reports Server (NTRS)

Harrington, Patrick M.; Melott, Adrian L.; Shandarin, Sergei F.

1993-01-01

We present in this paper a quantitative method for defining void size in large-scale structure based on percolation threshold density. Beginning with two-dimensional gravitational clustering simulations smoothed to the threshold of nonlinearity, we perform percolation analysis to determine the large scale structure. The resulting objective definition of voids has a natural scaling property, is topologically interesting, and can be applied immediately to redshift surveys.

Multi-scale statistical analysis of coronal solar activity

DOE PAGES

Gamborino, Diana; del-Castillo-Negrete, Diego; Martinell, Julio J.

2016-07-08

Multi-filter images from the solar corona are used to obtain temperature maps that are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions, we show that the multi-scale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also to be extracted from the analysis.

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

Portable laser synthesizer for high-speed multi-dimensional spectroscopy

DOEpatents

Demos, Stavros G [Livermore, CA; Shverdin, Miroslav Y [Sunnyvale, CA; Shirk, Michael D [Brentwood, CA

2012-05-29

Portable, field-deployable laser synthesizer devices designed for multi-dimensional spectrometry and time-resolved and/or hyperspectral imaging include a coherent light source which simultaneously produces a very broad, energetic, discrete spectrum spanning through or within the ultraviolet, visible, and near infrared wavelengths. The light output is spectrally resolved and each wavelength is delayed with respect to each other. A probe enables light delivery to a target. For multidimensional spectroscopy applications, the probe can collect the resulting emission and deliver this radiation to a time gated spectrometer for temporal and spectral analysis.

Three-dimensional computed topography analysis of a patient with an unusual anatomy of the maxillary second and third molars.

PubMed

Zhao, Jin; Li, Yan; Yang, Zhi-Wei; Wang, Wei; Meng, Yan

2011-10-01

We present a case of a patient with rare anatomy of a maxillary second molar with three mesiobuccal root canals and a maxillary third molar with four separate roots, identified using multi-slice computed topography (CT) and three-dimensional reconstruction techniques. The described case enriched/might enrich our knowledge about possible anatomical aberrations of maxillary molars. In addition, we demonstrate the role of multi-slice CT as an objective tool for confirmatory diagnosis and successful endodontic management.

Simulating and mapping spatial complexity using multi-scale techniques

USGS Publications Warehouse

De Cola, L.

1994-01-01

A central problem in spatial analysis is the mapping of data for complex spatial fields using relatively simple data structures, such as those of a conventional GIS. This complexity can be measured using such indices as multi-scale variance, which reflects spatial autocorrelation, and multi-fractal dimension, which characterizes the values of fields. These indices are computed for three spatial processes: Gaussian noise, a simple mathematical function, and data for a random walk. Fractal analysis is then used to produce a vegetation map of the central region of California based on a satellite image. This analysis suggests that real world data lie on a continuum between the simple and the random, and that a major GIS challenge is the scientific representation and understanding of rapidly changing multi-scale fields. -Author

Subgrid-scale stresses and scalar fluxes constructed by the multi-scale turnover Lagrangian map

NASA Astrophysics Data System (ADS)

AL-Bairmani, Sukaina; Li, Yi; Rosales, Carlos; Xie, Zheng-tong

2017-04-01

The multi-scale turnover Lagrangian map (MTLM) [C. Rosales and C. Meneveau, "Anomalous scaling and intermittency in three-dimensional synthetic turbulence," Phys. Rev. E 78, 016313 (2008)] uses nested multi-scale Lagrangian advection of fluid particles to distort a Gaussian velocity field and, as a result, generate non-Gaussian synthetic velocity fields. Passive scalar fields can be generated with the procedure when the fluid particles carry a scalar property [C. Rosales, "Synthetic three-dimensional turbulent passive scalar fields via the minimal Lagrangian map," Phys. Fluids 23, 075106 (2011)]. The synthetic fields have been shown to possess highly realistic statistics characterizing small scale intermittency, geometrical structures, and vortex dynamics. In this paper, we present a study of the synthetic fields using the filtering approach. This approach, which has not been pursued so far, provides insights on the potential applications of the synthetic fields in large eddy simulations and subgrid-scale (SGS) modelling. The MTLM method is first generalized to model scalar fields produced by an imposed linear mean profile. We then calculate the subgrid-scale stress, SGS scalar flux, SGS scalar variance, as well as related quantities from the synthetic fields. Comparison with direct numerical simulations (DNSs) shows that the synthetic fields reproduce the probability distributions of the SGS energy and scalar dissipation rather well. Related geometrical statistics also display close agreement with DNS results. The synthetic fields slightly under-estimate the mean SGS energy dissipation and slightly over-predict the mean SGS scalar variance dissipation. In general, the synthetic fields tend to slightly under-estimate the probability of large fluctuations for most quantities we have examined. Small scale anisotropy in the scalar field originated from the imposed mean gradient is captured. The sensitivity of the synthetic fields on the input spectra is assessed by using truncated spectra or model spectra as the input. Analyses show that most of the SGS statistics agree well with those from MTLM fields with DNS spectra as the input. For the mean SGS energy dissipation, some significant deviation is observed. However, it is shown that the deviation can be parametrized by the input energy spectrum, which demonstrates the robustness of the MTLM procedure.

Polynomial Chaos Based Acoustic Uncertainty Predictions from Ocean Forecast Ensembles

NASA Astrophysics Data System (ADS)

Dennis, S.

2016-02-01

Most significant ocean acoustic propagation occurs at tens of kilometers, at scales small compared basin and to most fine scale ocean modeling. To address the increased emphasis on uncertainty quantification, for example transmission loss (TL) probability density functions (PDF) within some radius, a polynomial chaos (PC) based method is utilized. In order to capture uncertainty in ocean modeling, Navy Coastal Ocean Model (NCOM) now includes ensembles distributed to reflect the ocean analysis statistics. Since the ensembles are included in the data assimilation for the new forecast ensembles, the acoustic modeling uses the ensemble predictions in a similar fashion for creating sound speed distribution over an acoustically relevant domain. Within an acoustic domain, singular value decomposition over the combined time-space structure of the sound speeds can be used to create Karhunen-Loève expansions of sound speed, subject to multivariate normality testing. These sound speed expansions serve as a basis for Hermite polynomial chaos expansions of derived quantities, in particular TL. The PC expansion coefficients result from so-called non-intrusive methods, involving evaluation of TL at multi-dimensional Gauss-Hermite quadrature collocation points. Traditional TL calculation from standard acoustic propagation modeling could be prohibitively time consuming at all multi-dimensional collocation points. This method employs Smolyak order and gridding methods to allow adaptive sub-sampling of the collocation points to determine only the most significant PC expansion coefficients to within a preset tolerance. Practically, the Smolyak order and grid sizes grow only polynomially in the number of Karhunen-Loève terms, alleviating the curse of dimensionality. The resulting TL PC coefficients allow the determination of TL PDF normality and its mean and standard deviation. In the non-normal case, PC Monte Carlo methods are used to rapidly establish the PDF. This work was sponsored by the Office of Naval Research

Detecting Shielded Special Nuclear Materials Using Multi-Dimensional Neutron Source and Detector Geometries

NASA Astrophysics Data System (ADS)

Santarius, John; Navarro, Marcos; Michalak, Matthew; Fancher, Aaron; Kulcinski, Gerald; Bonomo, Richard

2016-10-01

A newly initiated research project will be described that investigates methods for detecting shielded special nuclear materials by combining multi-dimensional neutron sources, forward/adjoint calculations modeling neutron and gamma transport, and sparse data analysis of detector signals. The key tasks for this project are: (1) developing a radiation transport capability for use in optimizing adaptive-geometry, inertial-electrostatic confinement (IEC) neutron source/detector configurations for neutron pulses distributed in space and/or phased in time; (2) creating distributed-geometry, gas-target, IEC fusion neutron sources; (3) applying sparse data and noise reduction algorithms, such as principal component analysis (PCA) and wavelet transform analysis, to enhance detection fidelity; and (4) educating graduate and undergraduate students. Funded by DHS DNDO Project 2015-DN-077-ARI095.

Multi-scale characterization of topographic anisotropy

NASA Astrophysics Data System (ADS)

Roy, S. G.; Koons, P. O.; Osti, B.; Upton, P.; Tucker, G. E.

2016-05-01

We present the every-direction variogram analysis (EVA) method for quantifying orientation and scale dependence of topographic anisotropy to aid in differentiation of the fluvial and tectonic contributions to surface evolution. Using multi-directional variogram statistics to track the spatial persistence of elevation values across a landscape, we calculate anisotropy as a multiscale, direction-sensitive variance in elevation between two points on a surface. Tectonically derived topographic anisotropy is associated with the three-dimensional kinematic field, which contributes (1) differential surface displacement and (2) crustal weakening along fault structures, both of which amplify processes of surface erosion. Based on our analysis, tectonic displacements dominate the topographic field at the orogenic scale, while a combination of the local displacement and strength fields are well represented at the ridge and valley scale. Drainage network patterns tend to reflect the geometry of underlying active or inactive tectonic structures due to the rapid erosion of faults and differential uplift associated with fault motion. Regions that have uniform environmental conditions and have been largely devoid of tectonic strain, such as passive coastal margins, have predominantly isotropic topography with typically dendritic drainage network patterns. Isolated features, such as stratovolcanoes, are nearly isotropic at their peaks but exhibit a concentric pattern of anisotropy along their flanks. The methods we provide can be used to successfully infer the settings of past or present tectonic regimes, and can be particularly useful in predicting the location and orientation of structural features that would otherwise be impossible to elude interpretation in the field. Though we limit the scope of this paper to elevation, EVA can be used to quantify the anisotropy of any spatially variable property.

Multi-scale mechanics of granular solids from grain-resolved X-ray measurements

NASA Astrophysics Data System (ADS)

Hurley, R. C.; Hall, S. A.; Wright, J. P.

2017-11-01

This work discusses an experimental technique for studying the mechanics of three-dimensional (3D) granular solids. The approach combines 3D X-ray diffraction and X-ray computed tomography to measure grain-resolved strains, kinematics and contact fabric in the bulk of a granular solid, from which continuum strains, grain stresses, interparticle forces and coarse-grained elasto-plastic moduli can be determined. We demonstrate the experimental approach and analysis of selected results on a sample of 1099 stiff, frictional grains undergoing multiple uniaxial compression cycles. We investigate the inter-particle force network, elasto-plastic moduli and associated length scales, reversibility of mechanical responses during cyclic loading, the statistics of microscopic responses and microstructure-property relationships. This work serves to highlight both the fundamental insight into granular mechanics that is furnished by combined X-ray measurements and describes future directions in the field of granular materials that can be pursued with such approaches.

[Multi-dimensional exploration of the characteristics of emotional regulation in children with attention-deficit/hyperactivity disorder].

PubMed

Yu, Xiaoyan; Liu, Lu; Sun, Li; Qian, Ying; Qian, Qiujin; Wu, Zhaomin; Cao, Qingjiu; Wang, Yufeng

2015-10-20

To explore the characteristics of emotional regulation in children with attention-deficit/hyperactivity disorder (ADHD). Two hundred and eighty-two children who were diagnosed as ADHD according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) were recruited from the child psychiatric clinic of Peking University Sixth Hospital/Institute of Mental Health from August 2012 to April 2014. And 260 normal children from the local primary schools were selected as the healthy control group. The emotional factors or items of Conners' Parent Rating Scale, Behavior Rating Inventory of Executive Function (BRIEF), Achenbach's Child Behavior Checklist (CBCL) and Rutter Children Behavior Questionnaire were used to assess the characteristics of emotional regulation multi-dimensionally. After controlling for the effects of age, sex and intelligence quotient (IQ), in Conner scale, the emotional lability (EL) scores of ADHD group were significantly higher than that of healthy control group [(4.3±2.6) vs (1.4±1.5), P<0.001]. In BRIEF scale, the emotional control (ECTRL) scores of ADHD group were significantly higher than that of control group [(16.1±4.4) vs (12.0±2.5), P<0.001]. In CBCL scale, the deficient emotional self-regulation (DESR) scores of ADHD group were significantly higher than that of control group [(26.8±11.0) vs (6.6±6.8), P<0.001]. In Rutter questionnaire, the emotional symptoms (ES) scores of ADHD group were significantly higher than that of control group [(2.7±2.0) vs (1.7±1.5), P<0.001]. Based on the receiver operating characteristics (ROC) curve, the area under the curve (AUC) of EL was 0.84 with 95% Confidence Intervals (CI) 0.81-0.87. The AUC of ECTRL was 0.81 with 95%CI 0.77-0.84. The AUC of DESR was 0.95 with 95%CI 0.93-0.97. The AUC of ES was 0.66 with 95%CI 0.61-0.70. The study multi-dimensionally indicated that children with ADHD displayed significant deficient emotional regulation.

Associations between trait emotional intelligence and loneliness in Chinese undergraduate students: mediating effects of self-esteem and social support.

PubMed

Zou, Jilin

2014-06-01

Prior studies indicate that trait emotional intelligence (EI) is associated negatively with loneliness. However, the mechanisms underlying the relationship are not clear. This study assessed whether both self-esteem and social support mediated the associations between trait EI and loneliness. 469 Chinese undergraduate participants whose age ranged from 18 to 23 years (208 women) were asked to complete four self-report questionnaires, including the Wong Law Emotional Intelligence Scale, the Social and Emotional Loneliness Scale, the Rosenberg Self-esteem Scale, and the Multi-Dimensional Scale of Perceived Social Support. Analyses indicated that self-esteem and social support fully mediated the associations between trait EI and loneliness. Effect contrasts indicated that the specific indirect effect through social support was significantly greater than that through self-esteem. Moreover, a multiple-group analysis indicated that no path differed significantly by sex. These results suggest that social support is more important than self-esteem in the association between trait EI and loneliness. Furthermore, both sexes appear to share the same mechanism underlying this association.

Effects of exercise dependence on psychological health of Chinese college students.

PubMed

Li, Menglong; Nie, Jingsong; Ren, Yujia

2015-12-01

The aim of this study was to investigate the effects of exercise dependence on the psychological health of Chinese college students. A total of 1601 college students from three universities in Hunan, China, were selected as research subjects. Several measurement scales, including the Exercise Addiction Inventory, the State-Trait Anxiety Inventory, the Center for Epidemiologic Studies Depression Scale, and the Subjective Well-being Scale, were used to survey the psychological health problem of these students and to analyze the effects of exercise dependence on their psychological health. Exercise dependence, based on the structural equation model analysis, can positively influence state anxiety (P<0.05), depression (P<0.05), and subjective well-being (P<0.05) of Chinese students. By contrast, exercise dependence negatively influences students' self-satisfaction (P<0.05), social behavior (P<0.05), and vigor (P<0.05). Exercise dependence adversely affects the psychological health of college students. Further research using multi-dimensional exercise addiction scales should be conducted to identify all the negative effects of exercise addiction factors on psychological health.

Teaching the Falling Ball Problem with Dimensional Analysis

ERIC Educational Resources Information Center

Sznitman, Josué; Stone, Howard A.; Smits, Alexander J.; Grotberg, James B.

2013-01-01

Dimensional analysis is often a subject reserved for students of fluid mechanics. However, the principles of scaling and dimensional analysis are applicable to various physical problems, many of which can be introduced early on in a university physics curriculum. Here, we revisit one of the best-known examples from a first course in classic…

Rasch analysis of the Chedoke-McMaster Attitudes towards Children with Handicaps scale.

PubMed

Armstrong, Megan; Morris, Christopher; Tarrant, Mark; Abraham, Charles; Horton, Mike C

2017-02-01

Aim To assess whether the Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) 36-item total scale and subscales fit the unidimensional Rasch model. Method The CATCH was administered to 1881 children, aged 7-16 years in a cross-sectional survey. Data were used from a random sample of 416 for the initial Rasch analysis. The analysis was performed on the 36-item scale and then separately for each subscale. The analysis explored fit to the Rasch model in terms of overall scale fit, individual item fit, item response categories, and unidimensionality. Item bias for gender and school level was also assessed. Revised scales were then tested on an independent second random sample of 415 children. Results Analyses indicated that the 36-item overall scale was not unidimensional and did not fit the Rasch model. Two scales of affective attitudes and behavioural intention were retained after four items were removed from each due to misfit to the Rasch model. Additionally, the scaling was improved when the two most negative response categories were aggregated. There was no item bias by gender or school level on the revised scales. Items assessing cognitive attitudes did not fit the Rasch model and had low internal consistency as a scale. Conclusion Affective attitudes and behavioural intention CATCH sub-scales should be treated separately. Caution should be exercised when using the cognitive subscale. Implications for Rehabilitation The 36-item Chedoke-McMaster Attitudes towards Children with Handicaps (CATCH) scale as a whole did not fit the Rasch model; thus indicating a multi-dimensional scale. Researchers should use two revised eight-item subscales of affective attitudes and behavioural intentions when exploring interventions aiming to improve children's attitudes towards disabled people or factors associated with those attitudes. Researchers should use the cognitive subscale with caution, as it did not create a unidimensional and internally consistent scale. Therefore, conclusions drawn from this scale may not accurately reflect children's attitudes.

Progress in multi-dimensional upwind differencing

NASA Technical Reports Server (NTRS)

Vanleer, Bram

1992-01-01

Multi-dimensional upwind-differencing schemes for the Euler equations are reviewed. On the basis of the first-order upwind scheme for a one-dimensional convection equation, the two approaches to upwind differencing are discussed: the fluctuation approach and the finite-volume approach. The usual extension of the finite-volume method to the multi-dimensional Euler equations is not entirely satisfactory, because the direction of wave propagation is always assumed to be normal to the cell faces. This leads to smearing of shock and shear waves when these are not grid-aligned. Multi-directional methods, in which upwind-biased fluxes are computed in a frame aligned with a dominant wave, overcome this problem, but at the expense of robustness. The same is true for the schemes incorporating a multi-dimensional wave model not based on multi-dimensional data but on an 'educated guess' of what they could be. The fluctuation approach offers the best possibilities for the development of genuinely multi-dimensional upwind schemes. Three building blocks are needed for such schemes: a wave model, a way to achieve conservation, and a compact convection scheme. Recent advances in each of these components are discussed; putting them all together is the present focus of a worldwide research effort. Some numerical results are presented, illustrating the potential of the new multi-dimensional schemes.

CFD analysis of a full-scale ceramic kiln module under actual operating conditions

NASA Astrophysics Data System (ADS)

Milani, Massimo; Montorsi, Luca; Stefani, Matteo; Venturelli, Matteo

2017-11-01

The paper focuses on the CFD analysis of a full-scale module of an industrial ceramic kiln under actual operating conditions. The multi-dimensional analysis includes the real geometry of a ceramic kiln module employed in the preheating and firing sections and investigates the heat transfer between the tiles and the burners' flame as well as the many components that comprise the module. Particular attention is devoted to the simulation of the convective flow field in the upper and lower chambers and to the effects of radiation on the different materials is addressed. The assessment of the radiation contribution to the tiles temperature is paramount to the improvement of the performance of the kiln in terms of energy efficiency and fuel consumption. The CFD analysis is combined to a lumped and distributed parameter model of the entire kiln in order to simulate the module behaviour at the boundaries under actual operating conditions. Finally, the CFD simulation is employed to address the effects of the module operating conditions on the tiles' temperature distribution in order to improve the temperature uniformity as well as to enhance the energy efficiency of the system and thus to reduce the fuel consumption.

Seasonal-Scale Optimization of Conventional Hydropower Operations in the Upper Colorado System

NASA Astrophysics Data System (ADS)

Bier, A.; Villa, D.; Sun, A.; Lowry, T. S.; Barco, J.

2011-12-01

Sandia National Laboratories is developing the Hydropower Seasonal Concurrent Optimization for Power and the Environment (Hydro-SCOPE) tool to examine basin-wide conventional hydropower operations at seasonal time scales. This tool is part of an integrated, multi-laboratory project designed to explore different aspects of optimizing conventional hydropower operations. The Hydro-SCOPE tool couples a one-dimensional reservoir model with a river routing model to simulate hydrology and water quality. An optimization engine wraps around this model framework to solve for long-term operational strategies that best meet the specific objectives of the hydrologic system while honoring operational and environmental constraints. The optimization routines are provided by Sandia's open source DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) software. Hydro-SCOPE allows for multi-objective optimization, which can be used to gain insight into the trade-offs that must be made between objectives. The Hydro-SCOPE tool is being applied to the Upper Colorado Basin hydrologic system. This system contains six reservoirs, each with its own set of objectives (such as maximizing revenue, optimizing environmental indicators, meeting water use needs, or other objectives) and constraints. This leads to a large optimization problem with strong connectedness between objectives. The systems-level approach used by the Hydro-SCOPE tool allows simultaneous analysis of these objectives, as well as understanding of potential trade-offs related to different objectives and operating strategies. The seasonal-scale tool will be tightly integrated with the other components of this project, which examine day-ahead and real-time planning, environmental performance, hydrologic forecasting, and plant efficiency.

Scientific Visualization Tools for Enhancement of Undergraduate Research

NASA Astrophysics Data System (ADS)

Rodriguez, W. J.; Chaudhury, S. R.

2001-05-01

Undergraduate research projects that utilize remote sensing satellite instrument data to investigate atmospheric phenomena pose many challenges. A significant challenge is processing large amounts of multi-dimensional data. Remote sensing data initially requires mining; filtering of undesirable spectral, instrumental, or environmental features; and subsequently sorting and reformatting to files for easy and quick access. The data must then be transformed according to the needs of the investigation(s) and displayed for interpretation. These multidimensional datasets require views that can range from two-dimensional plots to multivariable-multidimensional scientific visualizations with animations. Science undergraduate students generally find these data processing tasks daunting. Generally, researchers are required to fully understand the intricacies of the dataset and write computer programs or rely on commercially available software, which may not be trivial to use. In the time that undergraduate researchers have available for their research projects, learning the data formats, programming languages, and/or visualization packages is impractical. When dealing with large multi-dimensional data sets appropriate Scientific Visualization tools are imperative in allowing students to have a meaningful and pleasant research experience, while producing valuable scientific research results. The BEST Lab at Norfolk State University has been creating tools for multivariable-multidimensional analysis of Earth Science data. EzSAGE and SAGE4D have been developed to sort, analyze and visualize SAGE II (Stratospheric Aerosol and Gas Experiment) data with ease. Three- and four-dimensional visualizations in interactive environments can be produced. EzSAGE provides atmospheric slices in three-dimensions where the researcher can change the scales in the three-dimensions, color tables and degree of smoothing interactively to focus on particular phenomena. SAGE4D provides a navigable four-dimensional interactive environment. These tools allow students to make higher order decisions based on large multidimensional sets of data while diminishing the level of frustration that results from dealing with the details of processing large data sets.

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

3-d finite element model development for biomechanics: a software demonstration

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

Hollerbach, K.; Hollister, A.M.; Ashby, E.

1997-03-01

Finite element analysis is becoming an increasingly important part of biomechanics and orthopedic research, as computational resources become more powerful, and data handling algorithms become more sophisticated. Until recently, tools with sufficient power did not exist or were not accessible to adequately model complicated, three-dimensional, nonlinear biomechanical systems. In the past, finite element analyses in biomechanics have often been limited to two-dimensional approaches, linear analyses, or simulations of single tissue types. Today, we have the resources to model fully three-dimensional, nonlinear, multi-tissue, and even multi-joint systems. The authors will present the process of developing these kinds of finite element models,more » using human hand and knee examples, and will demonstrate their software tools.« less

Analysis on the multi-dimensional spectrum of the thrust force for the linear motor feed drive system in machine tools

NASA Astrophysics Data System (ADS)

Yang, Xiaojun; Lu, Dun; Ma, Chengfang; Zhang, Jun; Zhao, Wanhua

2017-01-01

The motor thrust force has lots of harmonic components due to the nonlinearity of drive circuit and motor itself in the linear motor feed drive system. What is more, in the motion process, these thrust force harmonics may vary with the position, velocity, acceleration and load, which affects the displacement fluctuation of the feed drive system. Therefore, in this paper, on the basis of the thrust force spectrum obtained by the Maxwell equation and the electromagnetic energy method, the multi-dimensional variation of each thrust harmonic is analyzed under different motion parameters. Then the model of the servo system is established oriented to the dynamic precision. The influence of the variation of the thrust force spectrum on the displacement fluctuation is discussed. At last the experiments are carried out to verify the theoretical analysis above. It can be found that the thrust harmonics show multi-dimensional spectrum characteristics under different motion parameters and loads, which should be considered to choose the motion parameters and optimize the servo control parameters in the high-speed and high-precision machine tools equipped with the linear motor feed drive system.

Modeling the relaxation of internal DNA segments during genome mapping in nanochannels.

PubMed

Jain, Aashish; Sheats, Julian; Reifenberger, Jeffrey G; Cao, Han; Dorfman, Kevin D

2016-09-01

We have developed a multi-scale model describing the dynamics of internal segments of DNA in nanochannels used for genome mapping. In addition to the channel geometry, the model takes as its inputs the DNA properties in free solution (persistence length, effective width, molecular weight, and segmental hydrodynamic radius) and buffer properties (temperature and viscosity). Using pruned-enriched Rosenbluth simulations of a discrete wormlike chain model with circa 10 base pair resolution and a numerical solution for the hydrodynamic interactions in confinement, we convert these experimentally available inputs into the necessary parameters for a one-dimensional, Rouse-like model of the confined chain. The resulting coarse-grained model resolves the DNA at a length scale of approximately 6 kilobase pairs in the absence of any global hairpin folds, and is readily studied using a normal-mode analysis or Brownian dynamics simulations. The Rouse-like model successfully reproduces both the trends and order of magnitude of the relaxation time of the distance between labeled segments of DNA obtained in experiments. The model also provides insights that are not readily accessible from experiments, such as the role of the molecular weight of the DNA and location of the labeled segments that impact the statistical models used to construct genome maps from data acquired in nanochannels. The multi-scale approach used here, while focused towards a technologically relevant scenario, is readily adapted to other channel sizes and polymers.

Topological patterns of mesh textures in serpentinites

NASA Astrophysics Data System (ADS)

Miyazawa, M.; Suzuki, A.; Shimizu, H.; Okamoto, A.; Hiraoka, Y.; Obayashi, I.; Tsuji, T.; Ito, T.

2017-12-01

Serpentinization is a hydration process that forms serpentine minerals and magnetite within the oceanic lithosphere. Microfractures crosscut these minerals during the reactions, and the structures look like mesh textures. It has been known that the patterns of microfractures and the system evolutions are affected by the hydration reaction and fluid transport in fractures and within matrices. This study aims at quantifying the topological patterns of the mesh textures and understanding possible conditions of fluid transport and reaction during serpentinization in the oceanic lithosphere. Two-dimensional simulation by the distinct element method (DEM) generates fracture patterns due to serpentinization. The microfracture patterns are evaluated by persistent homology, which measures features of connected components of a topological space and encodes multi-scale topological features in the persistence diagrams. The persistence diagrams of the different mesh textures are evaluated by principal component analysis to bring out the strong patterns of persistence diagrams. This approach help extract feature values of fracture patterns from high-dimensional and complex datasets.

Three-dimensional microstructure simulation of Ni-based superalloy investment castings

NASA Astrophysics Data System (ADS)

Pan, Dong; Xu, Qingyan; Liu, Baicheng

2011-05-01

An integrated macro and micro multi-scale model for the three-dimensional microstructure simulation of Ni-based superalloy investment castings was developed, and applied to industrial castings to investigate grain evolution during solidification. A ray tracing method was used to deal with the complex heat radiation transfer. The microstructure evolution was simulated based on the Modified Cellular Automaton method, which was coupled with three-dimensional nested macro and micro grids. Experiments for Ni-based superalloy turbine wheel investment casting were carried out, which showed a good correspondence with the simulated results. It is indicated that the proposed model is able to predict the microstructure of the casting precisely, which provides a tool for the optimizing process.

Optimal design of groundwater remediation system using a probabilistic multi-objective fast harmony search algorithm under uncertainty

NASA Astrophysics Data System (ADS)

Luo, Qiankun; Wu, Jianfeng; Yang, Yun; Qian, Jiazhong; Wu, Jichun

2014-11-01

This study develops a new probabilistic multi-objective fast harmony search algorithm (PMOFHS) for optimal design of groundwater remediation systems under uncertainty associated with the hydraulic conductivity (K) of aquifers. The PMOFHS integrates the previously developed deterministic multi-objective optimization method, namely multi-objective fast harmony search algorithm (MOFHS) with a probabilistic sorting technique to search for Pareto-optimal solutions to multi-objective optimization problems in a noisy hydrogeological environment arising from insufficient K data. The PMOFHS is then coupled with the commonly used flow and transport codes, MODFLOW and MT3DMS, to identify the optimal design of groundwater remediation systems for a two-dimensional hypothetical test problem and a three-dimensional Indiana field application involving two objectives: (i) minimization of the total remediation cost through the engineering planning horizon, and (ii) minimization of the mass remaining in the aquifer at the end of the operational period, whereby the pump-and-treat (PAT) technology is used to clean up contaminated groundwater. Also, Monte Carlo (MC) analysis is employed to evaluate the effectiveness of the proposed methodology. Comprehensive analysis indicates that the proposed PMOFHS can find Pareto-optimal solutions with low variability and high reliability and is a potentially effective tool for optimizing multi-objective groundwater remediation problems under uncertainty.

Flyby Error Analysis Based on Contour Plots for the Cassini Tour

NASA Technical Reports Server (NTRS)

Stumpf, P. W.; Gist, E. M.; Goodson, T. D.; Hahn, Y.; Wagner, S. V.; Williams, P. N.

2008-01-01

The maneuver cancellation analysis consists of cost contour plots employed by the Cassini maneuver team. The plots are two-dimensional linear representations of a larger six-dimensional solution to a multi-maneuver, multi-encounter mission at Saturn. By using contours plotted with the dot product of vectors B and R and the dot product of vectors B and T components, it is possible to view the effects delta V on for various encounter positions in the B-plane. The plot is used in operations to help determine if the Approach Maneuver (ensuing encounter minus three days) and/or the Cleanup Maneuver (ensuing encounter plus three days) can be cancelled and also is a linear check of an integrated solution.

Multi-segmental movement patterns reflect juggling complexity and skill level.

PubMed

Zago, Matteo; Pacifici, Ilaria; Lovecchio, Nicola; Galli, Manuela; Federolf, Peter Andreas; Sforza, Chiarella

2017-08-01

The juggling action of six experts and six intermediates jugglers was recorded with a motion capture system and decomposed into its fundamental components through Principal Component Analysis. The aim was to quantify trends in movement dimensionality, multi-segmental patterns and rhythmicity as a function of proficiency level and task complexity. Dimensionality was quantified in terms of Residual Variance, while the Relative Amplitude was introduced to account for individual differences in movement components. We observed that: experience-related modifications in multi-segmental actions exist, such as the progressive reduction of error-correction movements, especially in complex task condition. The systematic identification of motor patterns sensitive to the acquisition of specific experience could accelerate the learning process. Copyright © 2017 Elsevier B.V. All rights reserved.

Adopting Learning Design with LAMS: Multi-Dimensional, Synchronous Large-Scale Adoption of Innovation

ERIC Educational Resources Information Center

Badilescu-Buga, Emil

2012-01-01

Learning Activity Management System (LAMS) has been trialled and used by users from many countries around the globe, but despite the positive attitude towards its potential benefits to pedagogical processes its adoption in practice has been uneven, reflecting how difficult it is to make a new technology based concept an integral part of the…

Demographic Determinants of Students Susceptibility to Peer Victimization in Secondary Schools in Osun State, Nigeria

ERIC Educational Resources Information Center

Adefunke, Ehindero Serifat

2015-01-01

This study examined age, sex, class and religion as determinants of students' susceptibility to peer victimization. One thousand five hundred students from 10 public secondary schools were selected by stratified sampling technique using class level as strata. A validated multi-dimensional peer victimization scale (MPVS) was used to collect data…

A Multi-Dimensional Approach to Measuring News Media Literacy

ERIC Educational Resources Information Center

Vraga, Emily; Tully, Melissa; Kotcher, John E.; Smithson, Anne-Bennett; Broeckelman-Post, Melissa

2015-01-01

Measuring news media literacy is important in order for it to thrive in a variety of educational and civic contexts. This research builds on existing measures of news media literacy and two new scales are presented that measure self-perceived media literacy (SPML) and perceptions of the value of media literacy (VML). Research with a larger sample…

Differences in Student Evaluations of Limited-Term Lecturers and Full-Time Faculty

ERIC Educational Resources Information Center

Cho, Jeong-Il; Otani, Koichiro; Kim, B. Joon

2014-01-01

This study compared student evaluations of teaching (SET) for limited-term lecturers (LTLs) and full-time faculty (FTF) using a Likert-scaled survey administered to students (N = 1,410) at the end of university courses. Data were analyzed using a general linear regression model to investigate the influence of multi-dimensional evaluation items on…

Multi-mode phase speed measurements with array-based analysis: Application to the North American continent

NASA Astrophysics Data System (ADS)

Matsuzawa, H.; Yoshizawa, K.

2017-12-01

Recent high-density broad-band seismic networks allow us to construct improved 3-D upper mantle models with unprecedented horizontal resolution using surface waves. Such dispersion measurements have been primarily based on the analysis of fundamental mode. Higher-mode information can be of help in enhancing vertical resolution of 3-D models, but their dispersion analysis is intrinsically difficult, since wave-packets of several modes are overlapped each other in an observed seismogram. In this study, we measure phase dispersion of multi-mode surface waves with an array-based analysis. Our method is modeled on a one-dimensional frequency-wavenumber method originally developed by Nolet (1975, GRL), which can be applied to a set of broadband seismic records observed in a linear array along a great circle path. Through this analysis, we can obtain a spectrogram in c-T (phase speed - period) domain, which is characterized by mode-branch dispersion curves and relative spectral powers for each mode. Synthetic experiments indicate that we can separate the modal contribution using a long linear array with typical array length of about 2000 to 4000 km. The method is applied to a large data set from USArray using nearly 400 seismic events in 2007 - 2014 with Mw 6.5 or greater. Our phase-speed maps for the fundamental-mode Love and Rayleigh waves and the first higher-mode Rayleigh waves match well with the earlier models. The phase speed maps reflect typical large-scale features of regional seismic structure in North America, but smaller-scale variations are less constrained in our model, since our measured phase speeds represent path-average features over a long path (about a few thousands kilometers). Our multi-mode dispersion measurements can also be used for the extraction of mode-branch waveforms for the first a few modes. This can be done by applying a narrow filter around the dispersion curves of a target mode in c-T spectrogram. The mode-branch waveforms can then be reconstructed based on a linear Radon transform (e.g., Luo et al., 2015, GJI). Synthetic experiments suggest that we can successfully retrieve the mode-branch waveforms for several mode branches, which can be used in the secondary analysis for constraining local-scale heterogeneity with enhanced depth resolution.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

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

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Homogenization-based interval analysis for structural-acoustic problem involving periodical composites and multi-scale uncertain-but-bounded parameters.

PubMed

Chen, Ning; Yu, Dejie; Xia, Baizhan; Liu, Jian; Ma, Zhengdong

2017-04-01

This paper presents a homogenization-based interval analysis method for the prediction of coupled structural-acoustic systems involving periodical composites and multi-scale uncertain-but-bounded parameters. In the structural-acoustic system, the macro plate structure is assumed to be composed of a periodically uniform microstructure. The equivalent macro material properties of the microstructure are computed using the homogenization method. By integrating the first-order Taylor expansion interval analysis method with the homogenization-based finite element method, a homogenization-based interval finite element method (HIFEM) is developed to solve a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters. The corresponding formulations of the HIFEM are deduced. A subinterval technique is also introduced into the HIFEM for higher accuracy. Numerical examples of a hexahedral box and an automobile passenger compartment are given to demonstrate the efficiency of the presented method for a periodical composite structural-acoustic system with multi-scale uncertain-but-bounded parameters.

Navigating a Divided Society: Educational Research Strategies for Post-Conflict Bosnia and Herzegovina

ERIC Educational Resources Information Center

Komatsu, Taro

2012-01-01

This article discusses methodological issues associated with education research in Bosnia and Herzegovina (BiH) and describes strategies taken to address them. Within a case study, mixed methods allowed the author to examine school leaders' perceptions multi-dimensionally. Multi-level analysis was essential to the understanding of policy-making…

Assessment of Perceived Stress Related to Migration and Acculturation in Patients with Psychiatric Disorders (MIGSTR10)-Development, Reliability, and Dimensionality of a Brief Instrument.

PubMed

Müller, Matthias J; Zink, Sabrina; Koch, Eckhardt

2017-09-01

Assessment of stressors related to migration and acculturation in patients with psychiatric disorder and migration background could help improve culturally sensitive concepts of psychiatry and psychotherapy for diagnosis and treatment. The present overview delineates development and psychometric properties of an instrument (MIGSTR10) for assessment of stressors related to migration and acculturation, particularly for application in patients with psychiatric disorders. Ten migration-related stressors were derived from a qualitative content analysis of case histories of patients with psychiatric disorder and migration background and put into a suitable interview and questionnaire format (MIGSTR10; 10 questions, answer format: categorical yes/no, and dimensional 0-10) for self-assessment and observer ratings in several languages. Reliability (interrater agreement, internal consistency) and dimensionality (multi-dimensional scaling, MDS) were investigated in n = 235 patients with migration background and n = 612 indigenous German patients. Interrater agreement (ICC) for MIGSTR10 single items and sum scores (categorical and dimensional) was sufficiently high (≥.58); internal consistency (Cronbach's α) reached medium to high values (.56-.73). MDS revealed a two-dimensional solution with two item clusters (A: communication, migration history, forced marriage, homesickness, discrimination, other stressors; B: family conflicts, loss of status, feelings of shame, guilt feelings). The MIGSTR10 is a rationally developed, straightforward 10-item screening instrument with satisfactory psychometric properties for the assessment of individual and specific stressors related to migration and acculturation.

MultiMetEval: Comparative and Multi-Objective Analysis of Genome-Scale Metabolic Models

PubMed Central

Gevorgyan, Albert; Kierzek, Andrzej M.; Breitling, Rainer; Takano, Eriko

2012-01-01

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEval/downloads. PMID:23272111

Multi-scale modelling of elastic moduli of trabecular bone

PubMed Central

Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz

2012-01-01

We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in the analysis. Good agreement is found between theoretical and experimental results. PMID:22279160

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

PubMed Central

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-01-01

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era. PMID:27649151

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

PubMed

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-09-14

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

EMD-WVD time-frequency distribution for analysis of multi-component signals

NASA Astrophysics Data System (ADS)

Chai, Yunzi; Zhang, Xudong

2016-10-01

Time-frequency distribution (TFD) is two-dimensional function that indicates the time-varying frequency content of one-dimensional signals. And The Wigner-Ville distribution (WVD) is an important and effective time-frequency analysis method. The WVD can efficiently show the characteristic of a mono-component signal. However, a major drawback is the extra cross-terms when multi-component signals are analyzed by WVD. In order to eliminating the cross-terms, we decompose signals into single frequency components - Intrinsic Mode Function (IMF) - by using the Empirical Mode decomposition (EMD) first, then use WVD to analyze each single IMF. In this paper, we define this new time-frequency distribution as EMD-WVD. And the experiment results show that the proposed time-frequency method can solve the cross-terms problem effectively and improve the accuracy of WVD time-frequency analysis.

Multi-photon microfabrication of three-dimensional capillary-scale vascular networks

NASA Astrophysics Data System (ADS)

Skylar-Scott, Mark A.; Liu, Man-Chi; Wu, Yuelong; Yanik, Mehmet Fatih

2017-02-01

Biomimetic models of microvasculature could enable assays of complex cellular behavior at the capillary-level, and enable efficient nutrient perfusion for the maintenance of tissues. However, existing three-dimensional printing methods for generating perfusable microvasculature with have insufficient resolution to recapitulate the microscale geometry of capillaries. Here, we present a collection of multiphoton microfabrication methods that enable the production of precise, three-dimensional, branched microvascular networks in collagen. When endothelial cells are added to the channels, they form perfusable lumens with diameters as small as 10 μm. Using a similar photochemistry, we also demonstrate the micropatterning of proteins embedded in microfabricated collagen scaffolds, producing hybrid scaffolds with both defined microarchitecture with integrated gradients of chemical cues. We provide examples for how these hybrid microfabricated scaffolds could be used in angiogenesis and cell homing assays. Finally, we describe a new method for increasing the micropatterning speed by synchronous laser and stage scanning. Using these technologies, we are working towards large-scale (>1 cm), high resolution ( 1 μm) scaffolds with both microarchitecture and embedded protein cues, with applications in three-dimensional assays of cellular behavior.

Multidimensional scaling for evolutionary algorithms--visualization of the path through search space and solution space using Sammon mapping.

PubMed

Pohlheim, Hartmut

2006-01-01

Multidimensional scaling as a technique for the presentation of high-dimensional data with standard visualization techniques is presented. The technique used is often known as Sammon mapping. We explain the mathematical foundations of multidimensional scaling and its robust calculation. We also demonstrate the use of this technique in the area of evolutionary algorithms. First, we present the visualization of the path through the search space of the best individuals during an optimization run. We then apply multidimensional scaling to the comparison of multiple runs regarding the variables of individuals and multi-criteria objective values (path through the solution space).

The INTERGROWTH-21st Project Neurodevelopment Package: A Novel Method for the Multi-Dimensional Assessment of Neurodevelopment in Pre-School Age Children

PubMed Central

Fernandes, Michelle; Stein, Alan; Newton, Charles R.; Cheikh-Ismail, Leila; Kihara, Michael; Wulff, Katharina; de León Quintana, Enrique; Aranzeta, Luis; Soria-Frisch, Aureli; Acedo, Javier; Ibanez, David; Abubakar, Amina; Giuliani, Francesca; Lewis, Tamsin; Kennedy, Stephen; Villar, Jose

2014-01-01

Background The International Fetal and Newborn Growth Consortium for the 21st Century (INTERGROWTH-21st) Project is a population-based, longitudinal study describing early growth and development in an optimally healthy cohort of 4607 mothers and newborns. At 24 months, children are assessed for neurodevelopmental outcomes with the INTERGROWTH-21st Neurodevelopment Package. This paper describes neurodevelopment tools for preschoolers and the systematic approach leading to the development of the Package. Methods An advisory panel shortlisted project-specific criteria (such as multi-dimensional assessments and suitability for international populations) to be fulfilled by a neurodevelopment instrument. A literature review of well-established tools for preschoolers revealed 47 candidates, none of which fulfilled all the project's criteria. A multi-dimensional assessment was, therefore, compiled using a package-based approach by: (i) categorizing desired outcomes into domains, (ii) devising domain-specific criteria for tool selection, and (iii) selecting the most appropriate measure for each domain. Results The Package measures vision (Cardiff tests); cortical auditory processing (auditory evoked potentials to a novelty oddball paradigm); and cognition, language skills, behavior, motor skills and attention (the INTERGROWTH-21st Neurodevelopment Assessment) in 35–45 minutes. Sleep-wake patterns (actigraphy) are also assessed. Tablet-based applications with integrated quality checks and automated, wireless electroencephalography make the Package easy to administer in the field by non-specialist staff. The Package is in use in Brazil, India, Italy, Kenya and the United Kingdom. Conclusions The INTERGROWTH-21st Neurodevelopment Package is a multi-dimensional instrument measuring early child development (ECD). Its developmental approach may be useful to those involved in large-scale ECD research and surveillance efforts. PMID:25423589

Two antenna, two pass interferometric synthetic aperture radar

DOEpatents

Martinez, Ana; Doerry, Armin W.; Bickel, Douglas L.

2005-06-28

A multi-antenna, multi-pass IFSAR mode utilizing data driven alignment of multiple independent passes can combine the scaling accuracy of a two-antenna, one-pass IFSAR mode with the height-noise performance of a one-antenna, two-pass IFSAR mode. A two-antenna, two-pass IFSAR mode can accurately estimate the larger antenna baseline from the data itself and reduce height-noise, allowing for more accurate information about target ground position locations and heights. The two-antenna, two-pass IFSAR mode can use coarser IFSAR data to estimate the larger antenna baseline. Multi-pass IFSAR can be extended to more than two (2) passes, thereby allowing true three-dimensional radar imaging from stand-off aircraft and satellite platforms.

A geometrical multi-scale numerical method for coupled hygro-thermo-mechanical problems in photovoltaic laminates.

PubMed

Lenarda, P; Paggi, M

A comprehensive computational framework based on the finite element method for the simulation of coupled hygro-thermo-mechanical problems in photovoltaic laminates is herein proposed. While the thermo-mechanical problem takes place in the three-dimensional space of the laminate, moisture diffusion occurs in a two-dimensional domain represented by the polymeric layers and by the vertical channel cracks in the solar cells. Therefore, a geometrical multi-scale solution strategy is pursued by solving the partial differential equations governing heat transfer and thermo-elasticity in the three-dimensional space, and the partial differential equation for moisture diffusion in the two dimensional domains. By exploiting a staggered scheme, the thermo-mechanical problem is solved first via a fully implicit solution scheme in space and time, with a specific treatment of the polymeric layers as zero-thickness interfaces whose constitutive response is governed by a novel thermo-visco-elastic cohesive zone model based on fractional calculus. Temperature and relative displacements along the domains where moisture diffusion takes place are then projected to the finite element model of diffusion, coupled with the thermo-mechanical problem by the temperature and crack opening dependent diffusion coefficient. The application of the proposed method to photovoltaic modules pinpoints two important physical aspects: (i) moisture diffusion in humidity freeze tests with a temperature dependent diffusivity is a much slower process than in the case of a constant diffusion coefficient; (ii) channel cracks through Silicon solar cells significantly enhance moisture diffusion and electric degradation, as confirmed by experimental tests.

Research on the parallel load sharing principle of a novel self-decoupled piezoelectric six-dimensional force sensor.

PubMed

Li, Ying-Jun; Yang, Cong; Wang, Gui-Cong; Zhang, Hui; Cui, Huan-Yong; Zhang, Yong-Liang

2017-09-01

This paper presents a novel integrated piezoelectric six-dimensional force sensor which can realize dynamic measurement of multi-dimensional space load. Firstly, the composition of the sensor, the spatial layout of force-sensitive components, and measurement principle are analyzed and designed. There is no interference of piezoelectric six-dimensional force sensor in theoretical analysis. Based on the principle of actual work and deformation compatibility coherence, this paper deduces the parallel load sharing principle of the piezoelectric six-dimensional force sensor. The main effect factors which affect the load sharing ratio are obtained. The finite element model of the piezoelectric six-dimensional force sensor is established. In order to verify the load sharing principle of the sensor, a load sharing test device of piezoelectric force sensor is designed and fabricated. The load sharing experimental platform is set up. The experimental results are in accordance with the theoretical analysis and simulation results. The experiments show that the multi-dimensional and heavy force measurement can be realized by the parallel arrangement of the load sharing ring and the force sensitive element in the novel integrated piezoelectric six-dimensional force sensor. The ideal load sharing effect of the sensor can be achieved by appropriate size parameters. This paper has an important guide for the design of the force measuring device according to the load sharing mode. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Universal scaling function in discrete time asymmetric exclusion processes

NASA Astrophysics Data System (ADS)

Chia, Nicholas; Bundschuh, Ralf

2005-03-01

In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.

Status of a standard for neutron skyshine calculation and measurement

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

Westfall, R.M.; Wright, R.Q.; Greenborg, J.

1990-01-01

An effort has been under way for several years to prepare a draft standard, ANS-6.6.2, Calculation and Measurement of Direct and Scattered Neutron Radiation from Contained Sources Due to Nuclear Power Operations. At the outset, the work group adopted a three-phase study involving one-dimensional analyses, a measurements program, and multi-dimensional analyses. Of particular interest are the neutron radiation levels associated with dry-fuel storage at reactor sites. The need for dry storage has been investigated for various scenarios of repository and monitored retrievable storage (MRS) facilities availability with the waste stream analysis model. The concern is with long-term integrated, low-level dosesmore » at long distances from a multiplicity of sources. To evaluate the conservatism associated with one-dimensional analyses, the work group has specified a series of simple problems. Sources as a function of fuel exposure were determined for a Westinghouse 17 x 17 pressurized water reactor assembly with the ORIGEN-S module of the SCALE system. The energy degradation of the 35 GWd/ton U sources was determined for two generic designs of dry-fuel storage casks.« less

Building the 3D Geological Model of Wall Rock of Salt Caverns Based on Integration Method of Multi-source data

NASA Astrophysics Data System (ADS)

Yongzhi, WANG; hui, WANG; Lixia, LIAO; Dongsen, LI

2017-02-01

In order to analyse the geological characteristics of salt rock and stability of salt caverns, rough three-dimensional (3D) models of salt rock stratum and the 3D models of salt caverns on study areas are built by 3D GIS spatial modeling technique. During implementing, multi-source data, such as basic geographic data, DEM, geological plane map, geological section map, engineering geological data, and sonar data are used. In this study, the 3D spatial analyzing and calculation methods, such as 3D GIS intersection detection method in three-dimensional space, Boolean operations between three-dimensional space entities, three-dimensional space grid discretization, are used to build 3D models on wall rock of salt caverns. Our methods can provide effective calculation models for numerical simulation and analysis of the creep characteristics of wall rock in salt caverns.

Detection of crossover time scales in multifractal detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Ge, Erjia; Leung, Yee

2013-04-01

Fractal is employed in this paper as a scale-based method for the identification of the scaling behavior of time series. Many spatial and temporal processes exhibiting complex multi(mono)-scaling behaviors are fractals. One of the important concepts in fractals is crossover time scale(s) that separates distinct regimes having different fractal scaling behaviors. A common method is multifractal detrended fluctuation analysis (MF-DFA). The detection of crossover time scale(s) is, however, relatively subjective since it has been made without rigorous statistical procedures and has generally been determined by eye balling or subjective observation. Crossover time scales such determined may be spurious and problematic. It may not reflect the genuine underlying scaling behavior of a time series. The purpose of this paper is to propose a statistical procedure to model complex fractal scaling behaviors and reliably identify the crossover time scales under MF-DFA. The scaling-identification regression model, grounded on a solid statistical foundation, is first proposed to describe multi-scaling behaviors of fractals. Through the regression analysis and statistical inference, we can (1) identify the crossover time scales that cannot be detected by eye-balling observation, (2) determine the number and locations of the genuine crossover time scales, (3) give confidence intervals for the crossover time scales, and (4) establish the statistically significant regression model depicting the underlying scaling behavior of a time series. To substantive our argument, the regression model is applied to analyze the multi-scaling behaviors of avian-influenza outbreaks, water consumption, daily mean temperature, and rainfall of Hong Kong. Through the proposed model, we can have a deeper understanding of fractals in general and a statistical approach to identify multi-scaling behavior under MF-DFA in particular.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2010-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...research, we designed a pilot study utilizing large scale parallel Grid computing harnessing nationwide infrastructure for medical image analysis . Also

Synergies Between ' and Cavity Formation in HT-9 Following High Dose Neutron Irradiation

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

Field, Kevin G.; Parish, Chad M.; Saleh, Tarik A.

Candidate cladding materials for advanced nuclear power reactors including fast reactor designs require materials capable of withstanding high dose neutron irradiation at elevated temperatures. One candidate material, HT-9, through various research programs have demonstrated the ability to withstand significant swelling and other radiation-induced degradation mechanisms in the high dose regime (>50 displacements per atom, dpa) at elevated temperatures (>300 C). Here, high efficiency multi-dimensional scanning transmission electron microscopy (STEM) acquisition with the aid of a three-dimensional (3D) reconstruction and modeling technique is used to probe the microstructural features that contribute to the exceptional swelling resistance of HT-9. In particular, themore » synergies between ' and fine-scale and moderate-scale cavity formation is investigated.« less

On the formalization of multi-scale and multi-science processes for integrative biology

PubMed Central

Díaz-Zuccarini, Vanessa; Pichardo-Almarza, César

2011-01-01

The aim of this work is to introduce the general concept of ‘Bond Graph’ (BG) techniques applied in the context of multi-physics and multi-scale processes. BG modelling has a natural place in these developments. BGs are inherently coherent as the relationships defined between the ‘elements’ of the graph are strictly defined by causality rules and power (energy) conservation. BGs clearly show how power flows between components of the systems they represent. The ‘effort’ and ‘flow’ variables enable bidirectional information flow in the BG model. When the power level of a system is low, BGs degenerate into signal flow graphs in which information is mainly one-dimensional and power is minimal, i.e. they find a natural limitation when dealing with populations of individuals or purely kinetic models, as the concept of energy conservation in these systems is no longer relevant. The aim of this work is twofold: on the one hand, we will introduce the general concept of BG techniques applied in the context of multi-science and multi-scale models and, on the other hand, we will highlight some of the most promising features in the BG methodology by comparing with examples developed using well-established modelling techniques/software that could suggest developments or refinements to the current state-of-the-art tools, by providing a consistent framework from a structural and energetic point of view. PMID:22670211

Multi-temporal Linkages of Net Ecosystem Exchanges (NEE) with the Climatic and Ecohydrologic Drivers in a Florida Everglades Short-hydroperiod Freshwater Marsh

NASA Astrophysics Data System (ADS)

Zaki, M. T.; Abdul-Aziz, O. I.; Ishtiaq, K. S.

2017-12-01

Wetlands are considered one of the most productive and ecologically valuable ecosystems on earth. We investigated the multi-temporal linkages of net ecosystem exchange (NEE) with the relevant climatic and ecohydrological drivers for a Florida Everglades short-hydroperiod freshwater wetland. Hourly NEE observations and the associated driving variables during 2008-12 were collected from the AmeriFlux and EDEN databases, and then averaged for the four temporal scales (1-day, 8-day, 15-day, and 30-day). Pearson correlation and factor analysis were employed to identify the interrelations and grouping patterns among the participatory variables for each time scale. The climatic and ecohydrological linkages of NEE were then reliably estimated using bootstrapped (1000 iterations) partial least squares regressions by resolving multicollinearity. The analytics identified four bio-physical components exhibiting relatively robust interrelations and grouping patterns with NEE across the temporal scales. In general, NEE was most strongly linked with the `radiation-energy (RE)' component, while having a moderate linkage with the `temperature-hydrology (TH)' and `aerodynamic (AD)' components. However, the `ambient atmospheric CO2 (AC)' component was very weakly linked to NEE. Further, RE and TH had a decreasing trend with the increasing time scales (1-30 days). In contrast, the linkages of AD and AC components increased from 1-day to 8-day scales, and then remained relatively invariable at the longer scales of aggregation. The estimated linkages provide insights into the dominant biophysical process components and drivers of ecosystem carbon in the Everglades. The invariant linking pattern and linkages would help to develop low-dimensional models to reliably predict CO2 fluxes from the tidal freshwater wetlands.

Inverse finite-size scaling for high-dimensional significance analysis

NASA Astrophysics Data System (ADS)

Xu, Yingying; Puranen, Santeri; Corander, Jukka; Kabashima, Yoshiyuki

2018-06-01

We propose an efficient procedure for significance determination in high-dimensional dependence learning based on surrogate data testing, termed inverse finite-size scaling (IFSS). The IFSS method is based on our discovery of a universal scaling property of random matrices which enables inference about signal behavior from much smaller scale surrogate data than the dimensionality of the original data. As a motivating example, we demonstrate the procedure for ultra-high-dimensional Potts models with order of 1010 parameters. IFSS reduces the computational effort of the data-testing procedure by several orders of magnitude, making it very efficient for practical purposes. This approach thus holds considerable potential for generalization to other types of complex models.

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Dilational symmetry-breaking in thermodynamics

NASA Astrophysics Data System (ADS)

Lin, Chris L.; Ordóñez, Carlos R.

2017-04-01

Using thermodynamic relations and dimensional analysis we derive a general formula for the thermodynamical trace 2{ E}-DP for nonrelativistic systems and { E}-DP for relativistic systems, where D is the number of spatial dimensions, in terms of the microscopic scales of the system within the grand canonical ensemble. We demonstrate the formula for several cases, including anomalous systems which develop scales through dimensional transmutation. Using this relation, we make explicit the connection between dimensional analysis and the virial theorem. This paper is focused mainly on the non-relativistic aspects of this relation.

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

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

Tourret, D.; Mertens, J. C. E.; Lieberman, E.

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

DOE PAGES

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; ...

2017-09-13

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure,more » supported by quantitative simulations of microstructure formation and its mechanical behavior.« less

From Solidification Processing to Microstructure to Mechanical Properties: A Multi-scale X-ray Study of an Al-Cu Alloy Sample

NASA Astrophysics Data System (ADS)

Tourret, D.; Mertens, J. C. E.; Lieberman, E.; Imhoff, S. D.; Gibbs, J. W.; Henderson, K.; Fezzaa, K.; Deriy, A. L.; Sun, T.; Lebensohn, R. A.; Patterson, B. M.; Clarke, A. J.

2017-11-01

We follow an Al-12 at. pct Cu alloy sample from the liquid state to mechanical failure, using in situ X-ray radiography during directional solidification and tensile testing, as well as three-dimensional computed tomography of the microstructure before and after mechanical testing. The solidification processing stage is simulated with a multi-scale dendritic needle network model, and the micromechanical behavior of the solidified microstructure is simulated using voxelized tomography data and an elasto-viscoplastic fast Fourier transform model. This study demonstrates the feasibility of direct in situ monitoring of a metal alloy microstructure from the liquid processing stage up to its mechanical failure, supported by quantitative simulations of microstructure formation and its mechanical behavior.

METHODS FOR MULTI-SPATIAL SCALE CHARACTERIZATION OF RIPARIAN CORRIDORS

EPA Science Inventory

This paper describes the application of aerial photography and GIS technology to develop flexible and transferable methods for multi-spatial scale characterization and analysis of riparian corridors. Relationships between structural attributes of riparian corridors and indicator...

The Dula Dangerous Driving Index: An Investigation of Reliability and Validity across Cultures

PubMed Central

Willemsen, Jochem; Dula, Chris S.; Declercq, Frédéric; Verhaeghe, Paul

2008-01-01

The aim of this study is to further establish the validity and reliability of the Dula Dangerous Driving Index (DDDI). The reliability and validity of the instrument was investigated by comparing data from a US university sample, a US community sample, and a sample of Belgian traffic offenders. Exploratory and confirmatory factor analysis supported the presence of a four-factor structure with items for Drunk Driving forming a separate scale apart from items for Risky Driving, Negative Cognitive/Emotional Driving and Aggressive Driving. A multi-group confirmatory factor analysis with model constraints supported the validity of the DDDI. Inter-correlations revealed that the DDDI subscales are closely interrelated and uni-dimensionality of the measure was found in all three samples. This suggests the DDDI Total score can be used as a composite measure for dangerous driving. However, the validity of the subscales was demonstrated in the Belgian sample, as specific traffic offender groups (convicted for drunk driving, aggressive driving, speeding) scored higher on corresponding scales (Drunk Driving, Aggressive Driving, and Risky Driving, respectively), indicating that it is clinically meaningful to differentiate the subscales. PMID:18329435

Laser direct-write for fabrication of three-dimensional paper-based devices.

PubMed

He, P J W; Katis, I N; Eason, R W; Sones, C L

2016-08-16

We report the use of a laser-based direct-write (LDW) technique that allows the design and fabrication of three-dimensional (3D) structures within a paper substrate that enables implementation of multi-step analytical assays via a 3D protocol. The technique is based on laser-induced photo-polymerisation, and through adjustment of the laser writing parameters such as the laser power and scan speed we can control the depths of hydrophobic barriers that are formed within a substrate which, when carefully designed and integrated, produce 3D flow paths. So far, we have successfully used this depth-variable patterning protocol for stacking and sealing of multi-layer substrates, for assembly of backing layers for two-dimensional (2D) lateral flow devices and finally for fabrication of 3D devices. Since the 3D flow paths can also be formed via a single laser-writing process by controlling the patterning parameters, this is a distinct improvement over other methods that require multiple complicated and repetitive assembly procedures. This technique is therefore suitable for cheap, rapid and large-scale fabrication of 3D paper-based microfluidic devices.

Hierarchical algorithms for modeling the ocean on hierarchical architectures

NASA Astrophysics Data System (ADS)

Hill, C. N.

2012-12-01

This presentation will describe an approach to using accelerator/co-processor technology that maps hierarchical, multi-scale modeling techniques to an underlying hierarchical hardware architecture. The focus of this work is on making effective use of both CPU and accelerator/co-processor parts of a system, for large scale ocean modeling. In the work, a lower resolution basin scale ocean model is locally coupled to multiple, "embedded", limited area higher resolution sub-models. The higher resolution models execute on co-processor/accelerator hardware and do not interact directly with other sub-models. The lower resolution basin scale model executes on the system CPU(s). The result is a multi-scale algorithm that aligns with hardware designs in the co-processor/accelerator space. We demonstrate this approach being used to substitute explicit process models for standard parameterizations. Code for our sub-models is implemented through a generic abstraction layer, so that we can target multiple accelerator architectures with different programming environments. We will present two application and implementation examples. One uses the CUDA programming environment and targets GPU hardware. This example employs a simple non-hydrostatic two dimensional sub-model to represent vertical motion more accurately. The second example uses a highly threaded three-dimensional model at high resolution. This targets a MIC/Xeon Phi like environment and uses sub-models as a way to explicitly compute sub-mesoscale terms. In both cases the accelerator/co-processor capability provides extra compute cycles that allow improved model fidelity for little or no extra wall-clock time cost.

Correlative multi-scale characterization of a fine grained Nd-Fe-B sintered magnet.

PubMed

Sasaki, T T; Ohkubo, T; Hono, K; Une, Y; Sagawa, M

2013-09-01

The Nd-rich phases in pressless processed fine grained Nd-Fe-B sintered magnets have been characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), and three dimensional atom probe tomography (3DAP). The combination of the backscattered electron (BSE) and in-lens secondary electron (IL-SE) images in SEM led to an unambiguous identification of four types of Nd-rich phases, NdOx, Ia3 type phase, which is isostructural to Nd₂O₃, dhcp-Nd and Nd₁Fe₄B₄. In addition, the 3DAP analysis of thin Nd-rich grain boundary layer indicate that the coercivity has a close correlation with the chemistry of the grain boundary phase. Copyright © 2013 Elsevier B.V. All rights reserved.

Multiphysics Simulations of Hot-Spot Initiation in Shocked Insensitive High-Explosive

NASA Astrophysics Data System (ADS)

Najjar, Fady; Howard, W. M.; Fried, L. E.

2010-11-01

Solid plastic-bonded high-explosive materials consist of crystals with micron-sized pores embedded. Under mechanical or thermal insults, these voids increase the ease of shock initiation by generating high-temperature regions during their collapse that might lead to ignition. Understanding the mechanisms of hot-spot initiation has significant research interest due to safety, reliability and development of new insensitive munitions. Multi-dimensional high-resolution meso-scale simulations are performed using the multiphysics software, ALE3D, to understand the hot-spot initiation. The Cheetah code is coupled to ALE3D, creating multi-dimensional sparse tables for the HE properties. The reaction rates were obtained from MD Quantum computations. Our current predictions showcase several interesting features regarding hot spot dynamics including the formation of a "secondary" jet. We will discuss the results obtained with hydro-thermo-chemical processes leading to ignition growth for various pore sizes and different shock pressures.

Highly Transparent Water-Repelling Surfaces based on Biomimetic Hierarchical Structure

NASA Astrophysics Data System (ADS)

Wooh, Sanghyuk; Koh, Jai; Yoon, Hyunsik; Char, Kookheon

2013-03-01

Nature is a great source of inspiration for creating unique structures with special functions. The representative examples of water-repelling surfaces in nature, such as lotus leaves, rose petals, and insect wings, consist of an array of bumps (or long hairs) and nanoscale surface features with different dimension scales. Herein, we introduced a method of realizing multi-dimensional hierarchical structures and water-repellancy of the surfaces with different drop impact scenarios. The multi-dimensional hierarchical structures were fabricated by soft imprinting method with TiO2 nanoparticle pastes. In order to achieve the enhanced hydrophobicity, fluorinated moieties were attached to the etched surfaces to lower the surface energy. As a result, super-hydrophobic surfaces with high transparency were realized (over 176° water contact angle), and for further investigation, these hierarchical surfaces with different drop impact scenarios were characterized by varying the impact speed, drop size, and the geometry of the surfaces.

Multi-element least square HDMR methods and their applications for stochastic multiscale model reduction

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

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn; Li, Xinping, E-mail: exping@126.com

Stochastic multiscale modeling has become a necessary approach to quantify uncertainty and characterize multiscale phenomena for many practical problems such as flows in stochastic porous media. The numerical treatment of the stochastic multiscale models can be very challengeable as the existence of complex uncertainty and multiple physical scales in the models. To efficiently take care of the difficulty, we construct a computational reduced model. To this end, we propose a multi-element least square high-dimensional model representation (HDMR) method, through which the random domain is adaptively decomposed into a few subdomains, and a local least square HDMR is constructed in eachmore » subdomain. These local HDMRs are represented by a finite number of orthogonal basis functions defined in low-dimensional random spaces. The coefficients in the local HDMRs are determined using least square methods. We paste all the local HDMR approximations together to form a global HDMR approximation. To further reduce computational cost, we present a multi-element reduced least-square HDMR, which improves both efficiency and approximation accuracy in certain conditions. To effectively treat heterogeneity properties and multiscale features in the models, we integrate multiscale finite element methods with multi-element least-square HDMR for stochastic multiscale model reduction. This approach significantly reduces the original model's complexity in both the resolution of the physical space and the high-dimensional stochastic space. We analyze the proposed approach, and provide a set of numerical experiments to demonstrate the performance of the presented model reduction techniques. - Highlights: • Multi-element least square HDMR is proposed to treat stochastic models. • Random domain is adaptively decomposed into some subdomains to obtain adaptive multi-element HDMR. • Least-square reduced HDMR is proposed to enhance computation efficiency and approximation accuracy in certain conditions. • Integrating MsFEM and multi-element least square HDMR can significantly reduce computation complexity.« less

Analysis of Maneuvering Targets with Complex Motions by Two-Dimensional Product Modified Lv's Distribution for Quadratic Frequency Modulation Signals.

PubMed

Jing, Fulong; Jiao, Shuhong; Hou, Changbo; Si, Weijian; Wang, Yu

2017-06-21

For targets with complex motion, such as ships fluctuating with oceanic waves and high maneuvering airplanes, azimuth echo signals can be modeled as multicomponent quadratic frequency modulation (QFM) signals after migration compensation and phase adjustment. For the QFM signal model, the chirp rate (CR) and the quadratic chirp rate (QCR) are two important physical quantities, which need to be estimated. For multicomponent QFM signals, the cross terms create a challenge for detection, which needs to be addressed. In this paper, by employing a novel multi-scale parametric symmetric self-correlation function (PSSF) and modified scaled Fourier transform (mSFT), an effective parameter estimation algorithm is proposed-referred to as the Two-Dimensional product modified Lv's distribution (2D-PMLVD)-for QFM signals. The 2D-PMLVD is simple and can be easily implemented by using fast Fourier transform (FFT) and complex multiplication. These measures are analyzed in the paper, including the principle, the cross term, anti-noise performance, and computational complexity. Compared to the other three representative methods, the 2D-PMLVD can achieve better anti-noise performance. The 2D-PMLVD, which is free of searching and has no identifiability problems, is more suitable for multicomponent situations. Through several simulations and analyses, the effectiveness of the proposed estimation algorithm is verified.

Programming Details for MDPLOT: A Program for Plotting Multi-Dimensional Data

Treesearch

W.L. Nance; B.H. Polmer; G.C. Keith

1975-01-01

The program is written in ASA FORTRAN IV and consists of the main program (MAIN) with 14 subroutines. Subroutines SETUP, PLOT, GRID, SCALE, and 01s are microfilm-dependent and therefore must be replaced with the equivalent routines written for the high resolution plotting device available at the user's installation. The calls to these subroutines are flagged...

Examining the Relation between Social Values Perception and Moral Maturity Level of Folk Dancers

ERIC Educational Resources Information Center

Dogan, Pinar Karacan

2018-01-01

The purpose of the present study is to examine the relation between social values perceptions and moral maturity levels of folk dancers, and evaluate this relation in terms of some variables. The relational screening model was used in the study. The "Multi-dimensional Social Values Scale," which was developed by Bolat (2013), and the…

Exploiting multi-scale parallelism for large scale numerical modelling of laser wakefield accelerators

NASA Astrophysics Data System (ADS)

Fonseca, R. A.; Vieira, J.; Fiuza, F.; Davidson, A.; Tsung, F. S.; Mori, W. B.; Silva, L. O.

2013-12-01

A new generation of laser wakefield accelerators (LWFA), supported by the extreme accelerating fields generated in the interaction of PW-Class lasers and underdense targets, promises the production of high quality electron beams in short distances for multiple applications. Achieving this goal will rely heavily on numerical modelling to further understand the underlying physics and identify optimal regimes, but large scale modelling of these scenarios is computationally heavy and requires the efficient use of state-of-the-art petascale supercomputing systems. We discuss the main difficulties involved in running these simulations and the new developments implemented in the OSIRIS framework to address these issues, ranging from multi-dimensional dynamic load balancing and hybrid distributed/shared memory parallelism to the vectorization of the PIC algorithm. We present the results of the OASCR Joule Metric program on the issue of large scale modelling of LWFA, demonstrating speedups of over 1 order of magnitude on the same hardware. Finally, scalability to over ˜106 cores and sustained performance over ˜2 P Flops is demonstrated, opening the way for large scale modelling of LWFA scenarios.

Rasdaman for Big Spatial Raster Data

NASA Astrophysics Data System (ADS)

Hu, F.; Huang, Q.; Scheele, C. J.; Yang, C. P.; Yu, M.; Liu, K.

2015-12-01

Spatial raster data have grown exponentially over the past decade. Recent advancements on data acquisition technology, such as remote sensing, have allowed us to collect massive observation data of various spatial resolution and domain coverage. The volume, velocity, and variety of such spatial data, along with the computational intensive nature of spatial queries, pose grand challenge to the storage technologies for effective big data management. While high performance computing platforms (e.g., cloud computing) can be used to solve the computing-intensive issues in big data analysis, data has to be managed in a way that is suitable for distributed parallel processing. Recently, rasdaman (raster data manager) has emerged as a scalable and cost-effective database solution to store and retrieve massive multi-dimensional arrays, such as sensor, image, and statistics data. Within this paper, the pros and cons of using rasdaman to manage and query spatial raster data will be examined and compared with other common approaches, including file-based systems, relational databases (e.g., PostgreSQL/PostGIS), and NoSQL databases (e.g., MongoDB and Hive). Earth Observing System (EOS) data collected from NASA's Atmospheric Scientific Data Center (ASDC) will be used and stored in these selected database systems, and a set of spatial and non-spatial queries will be designed to benchmark their performance on retrieving large-scale, multi-dimensional arrays of EOS data. Lessons learnt from using rasdaman will be discussed as well.

Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.

Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

PubMed

Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

2014-01-01

In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Development of fine-resolution analyses and expanded large-scale forcing properties. Part II: Scale-awareness and application to single-column model experiments

DOE PAGES

Feng, Sha; Vogelmann, Andrew M.; Li, Zhijin; ...

2015-01-20

Fine-resolution three-dimensional fields have been produced using the Community Gridpoint Statistical Interpolation (GSI) data assimilation system for the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (ARM) Southern Great Plains region. The GSI system is implemented in a multi-scale data assimilation framework using the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. From the fine-resolution three-dimensional fields, large-scale forcing is derived explicitly at grid-scale resolution; a subgrid-scale dynamic component is derived separately, representing subgrid-scale horizontal dynamic processes. Analyses show that the subgrid-scale dynamic component is often a major component over the large-scale forcing for grid scalesmore » larger than 200 km. The single-column model (SCM) of the Community Atmospheric Model version 5 (CAM5) is used to examine the impact of the grid-scale and subgrid-scale dynamic components on simulated precipitation and cloud fields associated with a mesoscale convective system. It is found that grid-scale size impacts simulated precipitation, resulting in an overestimation for grid scales of about 200 km but an underestimation for smaller grids. The subgrid-scale dynamic component has an appreciable impact on the simulations, suggesting that grid-scale and subgrid-scale dynamic components should be considered in the interpretation of SCM simulations.« less

In search of a footprint: an investigation about the potentiality of large datasets and territorial analysis in disaster and resilience research.

NASA Astrophysics Data System (ADS)

Pregnolato, Marco; Petitta, Marcello; Schneiderbauer, Stefan; Pedoth, Lydia; Iasio, Christian; Kaveckis, Giedrius

2014-05-01

The present investigation aims to contribute to a better understanding if and how coarse scale data can prove useful in a study on resilience of communities towards natural hazards. Main goal of the work is the exploitation of large datasets in search for indicators and information valuable for resilience research; in particular, for marks in the statistical distribution of events as well as in the physical signs on a territory, to be possibly defined as disaster footprints. The approach developed required to start from theoretical considerations about some key concepts, such as footprint and resilience and the possible influence of different types of adverse events on a territory. In particular, the research focuses on statistical signals that can be identified within datasets, concerning the effects of hazardous events against the background of resilience, defined as the "ability of a system and its component parts to anticipate, absorb, accommodate, or recover" from a disaster. The hypothesis for this work was that a disaster footprint could be shown using land features and changes maps. The question linked to this hypothesis was: is there a possibility to recognize on the land a multi-dimensional footprint? Is it possible to do this using land cover/land use data? In order to answer these questions this work proposes a synthetic index, named for convenience Hazard-Territory Index, created to categorize classes of Land Use/Land Cover from the CORINE Land Cover maps, by the mean of different approaches, according to the type of hazard. Through the use and elaboration of CORINE Land Cover data this work investigates whether the land and its use (in a way the relationship between a territory and the community living on it) and its changes over time can reveal some information and results relevant for the analysis of resilience. The investigation, set up in order to analyse these "signs on a map", led to implicate the notion of footprint as a multi-dimensional concept, dealing with different temporal scales and dimensions of resilience and it proposes therefore a definition of disaster footprint, as a multi-parametrical and complex impact indicator (or rather an indicator family). The mutual influence between the land, the hazard and the system on the territory presents different aspects that we tried to synthesize into the same index, differently analyzed according to different dimensions of disaster footprint considered; namely: probability of occurrence, susceptibility to harm, long-term impacts and modifications. The index visualizes the information at national and supra-national scale on maps. Although presenting important theoretical limitations (mainly in the spatial and temporal resolution of the data and in the definition of proxies for physical parameters), the application of this methodology at a supra-national scale has proved useful in the attempt to define the domains of investigations for community resilience studies at a local scale.

Generalized Likelihood Uncertainty Estimation (GLUE) Using Multi-Optimization Algorithm as Sampling Method

NASA Astrophysics Data System (ADS)

Wang, Z.

2015-12-01

For decades, distributed and lumped hydrological models have furthered our understanding of hydrological system. The development of hydrological simulation in large scale and high precision elaborated the spatial descriptions and hydrological behaviors. Meanwhile, the new trend is also followed by the increment of model complexity and number of parameters, which brings new challenges of uncertainty quantification. Generalized Likelihood Uncertainty Estimation (GLUE) has been widely used in uncertainty analysis for hydrological models referring to Monte Carlo method coupled with Bayesian estimation. However, the stochastic sampling method of prior parameters adopted by GLUE appears inefficient, especially in high dimensional parameter space. The heuristic optimization algorithms utilizing iterative evolution show better convergence speed and optimality-searching performance. In light of the features of heuristic optimization algorithms, this study adopted genetic algorithm, differential evolution, shuffled complex evolving algorithm to search the parameter space and obtain the parameter sets of large likelihoods. Based on the multi-algorithm sampling, hydrological model uncertainty analysis is conducted by the typical GLUE framework. To demonstrate the superiority of the new method, two hydrological models of different complexity are examined. The results shows the adaptive method tends to be efficient in sampling and effective in uncertainty analysis, providing an alternative path for uncertainty quantilization.

Dynamics analysis of the fast-slow hydro-turbine governing system with different time-scale coupling

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Wu, Changzhi; Wang, Xiangyu

2018-01-01

Multi-time scales modeling of hydro-turbine governing system is crucial in precise modeling of hydropower plant and provides support for the stability analysis of the system. Considering the inertia and response time of the hydraulic servo system, the hydro-turbine governing system is transformed into the fast-slow hydro-turbine governing system. The effects of the time-scale on the dynamical behavior of the system are analyzed and the fast-slow dynamical behaviors of the system are investigated with different time-scale. Furthermore, the theoretical analysis of the stable regions is presented. The influences of the time-scale on the stable region are analyzed by simulation. The simulation results prove the correctness of the theoretical analysis. More importantly, the methods and results of this paper provide a perspective to multi-time scales modeling of hydro-turbine governing system and contribute to the optimization analysis and control of the system.

Fast Detection of Material Deformation through Structural Dissimilarity

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

Ushizima, Daniela; Perciano, Talita; Parkinson, Dilworth

2015-10-29

Designing materials that are resistant to extreme temperatures and brittleness relies on assessing structural dynamics of samples. Algorithms are critically important to characterize material deformation under stress conditions. Here, we report on our design of coarse-grain parallel algorithms for image quality assessment based on structural information and on crack detection of gigabyte-scale experimental datasets. We show how key steps can be decomposed into distinct processing flows, one based on structural similarity (SSIM) quality measure, and another on spectral content. These algorithms act upon image blocks that fit into memory, and can execute independently. We discuss the scientific relevance of themore » problem, key developments, and decomposition of complementary tasks into separate executions. We show how to apply SSIM to detect material degradation, and illustrate how this metric can be allied to spectral analysis for structure probing, while using tiled multi-resolution pyramids stored in HDF5 chunked multi-dimensional arrays. Results show that the proposed experimental data representation supports an average compression rate of 10X, and data compression scales linearly with the data size. We also illustrate how to correlate SSIM to crack formation, and how to use our numerical schemes to enable fast detection of deformation from 3D datasets evolving in time.« less

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul

2002-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Extension of a System Level Tool for Component Level Analysis

NASA Technical Reports Server (NTRS)

Majumdar, Alok; Schallhorn, Paul; McConnaughey, Paul K. (Technical Monitor)

2001-01-01

This paper presents an extension of a numerical algorithm for network flow analysis code to perform multi-dimensional flow calculation. The one dimensional momentum equation in network flow analysis code has been extended to include momentum transport due to shear stress and transverse component of velocity. Both laminar and turbulent flows are considered. Turbulence is represented by Prandtl's mixing length hypothesis. Three classical examples (Poiseuille flow, Couette flow, and shear driven flow in a rectangular cavity) are presented as benchmark for the verification of the numerical scheme.

Advanced Data Visualization in Astrophysics: The X3D Pathway

NASA Astrophysics Data System (ADS)

Vogt, Frédéric P. A.; Owen, Chris I.; Verdes-Montenegro, Lourdes; Borthakur, Sanchayeeta

2016-02-01

Most modern astrophysical data sets are multi-dimensional; a characteristic that can nowadays generally be conserved and exploited scientifically during the data reduction/simulation and analysis cascades. However, the same multi-dimensional data sets are systematically cropped, sliced, and/or projected to printable two-dimensional diagrams at the publication stage. In this article, we introduce the concept of the “X3D pathway” as a mean of simplifying and easing the access to data visualization and publication via three-dimensional (3D) diagrams. The X3D pathway exploits the facts that (1) the X3D 3D file format lies at the center of a product tree that includes interactive HTML documents, 3D printing, and high-end animations, and (2) all high-impact-factor and peer-reviewed journals in astrophysics are now published (some exclusively) online. We argue that the X3D standard is an ideal vector for sharing multi-dimensional data sets because it provides direct access to a range of different data visualization techniques, is fully open source, and is a well-defined standard from the International Organization for Standardization. Unlike other earlier propositions to publish multi-dimensional data sets via 3D diagrams, the X3D pathway is not tied to specific software (prone to rapid and unexpected evolution), but instead is compatible with a range of open-source software already in use by our community. The interactive HTML branch of the X3D pathway is also actively supported by leading peer-reviewed journals in the field of astrophysics. Finally, this article provides interested readers with a detailed set of practical astrophysical examples designed to act as a stepping stone toward the implementation of the X3D pathway for any other data set.

Computers as an Instrument for Data Analysis. Technical Report No. 11.

ERIC Educational Resources Information Center

Muller, Mervin E.

A review of statistical data analysis involving computers as a multi-dimensional problem provides the perspective for consideration of the use of computers in statistical analysis and the problems associated with large data files. An overall description of STATJOB, a particular system for doing statistical data analysis on a digital computer,…

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Urology Residents' Experience and Attitude Toward Surgical Simulation: Presenting our 4-Year Experience With a Multi-institutional, Multi-modality Simulation Model.

PubMed

Chow, Alexander K; Sherer, Benjamin A; Yura, Emily; Kielb, Stephanie; Kocjancic, Ervin; Eggener, Scott; Turk, Thomas; Park, Sangtae; Psutka, Sarah; Abern, Michael; Latchamsetty, Kalyan C; Coogan, Christopher L

2017-11-01

To evaluate the Urological resident's attitude and experience with surgical simulation in residency education using a multi-institutional, multi-modality model. Residents from 6 area urology training programs rotated through simulation stations in 4 consecutive sessions from 2014 to 2017. Workshops included GreenLight photovaporization of the prostate, ureteroscopic stone extraction, laparoscopic peg transfer, 3-dimensional laparoscopy rope pass, transobturator sling placement, intravesical injection, high definition video system trainer, vasectomy, and Urolift. Faculty members provided teaching assistance, objective scoring, and verbal feedback. Participants completed a nonvalidated questionnaire evaluating utility of the workshop and soliciting suggestions for improvement. Sixty-three of 75 participants (84%) (postgraduate years 1-6) completed the exit questionnaire. Median rating of exercise usefulness on a scale of 1-10 ranged from 7.5 to 9. On a scale of 0-10, cumulative median scores of the course remained high over 4 years: time limit per station (9; interquartile range [IQR] 2), faculty instruction (9, IQR 2), ease of use (9, IQR 2), face validity (8, IQR 3), and overall course (9, IQR 2). On multivariate analysis, there was no difference in rating of domains between postgraduate years. Sixty-seven percent (42/63) believe that simulation training should be a requirement of Urology residency. Ninety-seven percent (63/65) viewed the laboratory as beneficial to their education. This workshop model is a valuable training experience for residents. Most participants believe that surgical simulation is beneficial and should be a requirement for Urology residency. High ratings of usefulness for each exercise demonstrated excellent face validity provided by the course. Copyright © 2017 Elsevier Inc. All rights reserved.

Mission Analysis and Design for Space Based Inter-Satellite Laser Power Beaming

DTIC Science & Technology

2010-03-01

56 4.3.1 Darwin Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62 4.4 Obscuration Analysis...81 Appendix B. Additional Multi-Dimensional Darwin Plots from ModelCenter . 86 Appendix C. STK Access Report for... Darwin Data Explorer Window Showing Optimized Results in Tabular Form

Three-dimensional characterization of microporosity and permeability in fault zones hosted in heterolithic succession

NASA Astrophysics Data System (ADS)

Riegel, H. B.; Zambrano, M.; Jablonska, D.; Emanuele, T.; Agosta, F.; Mattioni, L.; Rustichelli, A.

2017-12-01

The hydraulic properties of fault zones depend upon the individual contributions of the damage zone and the fault core. In the case of the damage zone, it is generally characterized by means of fracture analysis and modelling implementing multiple approaches, for instance the discrete fracture network model, the continuum model, and the channel network model. Conversely, the fault core is more difficult to characterize because it is normally composed of fine grain material generated by friction and wear. If the dimensions of the fault core allows it, the porosity and permeability are normally studied by means of laboratory analysis or in the other case by two dimensional microporosity analysis and in situ measurements of permeability (e.g. micro-permeameter). In this study, a combined approach consisting of fracture modeling, three-dimensional microporosity analysis, and computational fluid dynamics was applied to characterize the hydraulic properties of fault zones. The studied fault zones crosscut a well-cemented heterolithic succession (sandstone and mudstones) and may vary in terms of fault core thickness and composition, fracture properties, kinematics (normal or strike-slip), and displacement. These characteristics produce various splay and fault core behavior. The alternation of sandstone and mudstone layers is responsible for the concurrent occurrence of brittle (fractures) and ductile (clay smearing) deformation. When these alternating layers are faulted, they produce corresponding fault cores which act as conduits or barriers for fluid migration. When analyzing damage zones, accurate field and data acquisition and stochastic modeling was used to determine the hydraulic properties of the rock volume, in relation to the surrounding, undamaged host rock. In the fault cores, the three-dimensional pore network quantitative analysis based on X-ray microtomography images includes porosity, pore connectivity, and specific surface area. In addition, images were used to perform computational fluid simulation (Lattice-Boltzmann multi relaxation time method) and estimate the permeability. These results will be useful for understanding the deformation process and hydraulic properties across meter-scale damage zones.

Task III: Development of an Effective Computational Methodology for Body Force Representation of High-speed Rotor 37

NASA Technical Reports Server (NTRS)

Tan, Choon-Sooi; Suder, Kenneth (Technical Monitor)

2003-01-01

A framework for an effective computational methodology for characterizing the stability and the impact of distortion in high-speed multi-stage compressor is being developed. The methodology consists of using a few isolated-blade row Navier-Stokes solutions for each blade row to construct a body force database. The purpose of the body force database is to replace each blade row in a multi-stage compressor by a body force distribution to produce same pressure rise and flow turning. To do this, each body force database is generated in such a way that it can respond to the changes in local flow conditions. Once the database is generated, no hrther Navier-Stokes computations are necessary. The process is repeated for every blade row in the multi-stage compressor. The body forces are then embedded as source terms in an Euler solver. The method is developed to have the capability to compute the performance in a flow that has radial as well as circumferential non-uniformity with a length scale larger than a blade pitch; thus it can potentially be used to characterize the stability of a compressor under design. It is these two latter features as well as the accompanying procedure to obtain the body force representation that distinguish the present methodology from the streamline curvature method. The overall computational procedures have been developed. A dimensional analysis was carried out to determine the local flow conditions for parameterizing the magnitudes of the local body force representation of blade rows. An Euler solver was modified to embed the body forces as source terms. The results from the dimensional analysis show that the body forces can be parameterized in terms of the two relative flow angles, the relative Mach number, and the Reynolds number. For flow in a high-speed transonic blade row, they can be parameterized in terms of the local relative Mach number alone.

Source Attribution of Near-surface Ozone in the Western US: Improved Estimates by TF HTAP2 Multi-model Experiment and Multi-scale Chemical Data Assimilation

NASA Astrophysics Data System (ADS)

Huang, M.; Bowman, K. W.; Carmichael, G. R.; Lee, M.; Park, R.; Henze, D. K.; Chai, T.; Flemming, J.; Lin, M.; Weinheimer, A. J.; Wisthaler, A.; Jaffe, D. A.

2014-12-01

Near-surface ozone in the western US can be sensitive to transported background pollutants from the free troposphere over the eastern Pacific, as well as various local emissions sources. Accurately estimating ozone source contributions in this region has strong policy-relevant significance as the air quality standards tend to go down. Here we improve modeled contributions from local and non-local sources to western US ozone base on the HTAP2 (Task Force on Hemispheric Transport of Air Pollution) multi-model experiment, along with multi-scale chemical data assimilation. We simulate western US air quality using the STEM regional model on a 12 km horizontal resolution grid, during the NASA ARCTAS field campaign period in June 2008. STEM simulations use time-varying boundary conditions downscaled from global GEOS-Chem model simulations. Standard GEOS-Chem simulation overall underpredicted ozone at 1-5 km in the eastern Pacific, resulting in underestimated contributions from the transported background pollutants to surface ozone inland. These negative biases can be reduced by using the output from several global models that support the HTAP2 experiment, which all ran with the HTAP2 harmonized emission inventory and also calculated the contributions from east Asian anthropogenic emissions. We demonstrate that the biases in GEOS-Chem boundary conditions can be more efficiently reduced via assimilating satellite ozone profiles from the Tropospheric Emission Spectrometer (TES) instrument using the three dimensional variational (3D-Var) approach. Base upon these TES-constrained GEOS-Chem boundary conditions, we then update regional nitrogen dioxide and isoprene emissions in STEM through the four dimensional variational (4D-Var) assimilation of the Ozone Monitoring Instrument (OMI) nitrogen dioxide columns and the NASA DC-8 aircraft isoprene measurements. The 4D-Var assimilation spatially redistributed the emissions of nitrogen oxides and isoprene from various US sources, and in the meantime updated the modeled ozone and its US source contributions. Compared with available independent measurements (e.g., ozone observed on the DC-8 aircraft, and at EPA and Mt. Bachelor monitoring stations) during this period, modeled ozone fields after the multi-scale assimilation show overall improvement.

SPHARA--a generalized spatial Fourier analysis for multi-sensor systems with non-uniformly arranged sensors: application to EEG.

PubMed

Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

2015-01-01

Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications.

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

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

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

NASA Astrophysics Data System (ADS)

Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang

2016-06-01

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

Generalized fourier analyses of the advection-diffusion equation - Part II: two-dimensional domains

NASA Astrophysics Data System (ADS)

Voth, Thomas E.; Martinez, Mario J.; Christon, Mark A.

2004-07-01

Part I of this work presents a detailed multi-methods comparison of the spatial errors associated with the one-dimensional finite difference, finite element and finite volume semi-discretizations of the scalar advection-diffusion equation. In Part II we extend the analysis to two-dimensional domains and also consider the effects of wave propagation direction and grid aspect ratio on the phase speed, and the discrete and artificial diffusivities. The observed dependence of dispersive and diffusive behaviour on propagation direction makes comparison of methods more difficult relative to the one-dimensional results. For this reason, integrated (over propagation direction and wave number) error and anisotropy metrics are introduced to facilitate comparison among the various methods. With respect to these metrics, the consistent mass Galerkin and consistent mass control-volume finite element methods, and their streamline upwind derivatives, exhibit comparable accuracy, and generally out-perform their lumped mass counterparts and finite-difference based schemes. While this work can only be considered a first step in a comprehensive multi-methods analysis and comparison, it serves to identify some of the relative strengths and weaknesses of multiple numerical methods in a common mathematical framework. Published in 2004 by John Wiley & Sons, Ltd.

Controllable 3D architectures of aligned carbon nanotube arrays by multi-step processes

NASA Astrophysics Data System (ADS)

Huang, Shaoming

2003-06-01

An effective way to fabricate large area three-dimensional (3D) aligned CNTs pattern based on pyrolysis of iron(II) phthalocyanine (FePc) by two-step processes is reported. The controllable generation of different lengths and selective growth of the aligned CNT arrays on metal-patterned (e.g., Ag and Au) substrate are the bases for generating such 3D aligned CNTs architectures. By controlling experimental conditions 3D aligned CNT arrays with different lengths/densities and morphologies/structures as well as multi-layered architectures can be fabricated in large scale by multi-step pyrolysis of FePc. These 3D architectures could have interesting properties and be applied for developing novel nanotube-based devices.

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.; Lam, Nina Siu-Ngan; Quattrochi, Dale A.

1999-01-01

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Application of the actor model to large scale NDE data analysis

NASA Astrophysics Data System (ADS)

Coughlin, Chris

2018-03-01

The Actor model of concurrent computation discretizes a problem into a series of independent units or actors that interact only through the exchange of messages. Without direct coupling between individual components, an Actor-based system is inherently concurrent and fault-tolerant. These traits lend themselves to so-called "Big Data" applications in which the volume of data to analyze requires a distributed multi-system design. For a practical demonstration of the Actor computational model, a system was developed to assist with the automated analysis of Nondestructive Evaluation (NDE) datasets using the open source Myriad Data Reduction Framework. A machine learning model trained to detect damage in two-dimensional slices of C-Scan data was deployed in a streaming data processing pipeline. To demonstrate the flexibility of the Actor model, the pipeline was deployed on a local system and re-deployed as a distributed system without recompiling, reconfiguring, or restarting the running application.

Automated X-Ray Diffraction of Irradiated Materials

DOE PAGES

Rodman, John; Lin, Yuewei; Sprouster, David; ...

2017-10-26

Synchrotron-based X-ray diffraction (XRD) and small-angle Xray scattering (SAXS) characterization techniques used on unirradiated and irradiated reactor pressure vessel steels yield large amounts of data. Machine learning techniques, including PCA, offer a novel method of analyzing and visualizing these large data sets in order to determine the effects of chemistry and irradiation conditions on the formation of radiation induced precipitates. In order to run analysis on these data sets, preprocessing must be carried out to convert the data to a usable format and mask the 2-D detector images to account for experimental variations. Once the data has been preprocessed, itmore » can be organized and visualized using principal component analysis (PCA), multi-dimensional scaling, and k-means clustering. In conclusion, from these techniques, it is shown that sample chemistry has a notable effect on the formation of the radiation induced precipitates in reactor pressure vessel steels.« less

Assortativity Patterns in Multi-dimensional Inter-organizational Networks: A Case Study of the Humanitarian Relief Sector

NASA Astrophysics Data System (ADS)

Zhao, Kang; Ngamassi, Louis-Marie; Yen, John; Maitland, Carleen; Tapia, Andrea

We use computational tools to study assortativity patterns in multi-dimensional inter-organizational networks on the basis of different node attributes. In the case study of an inter-organizational network in the humanitarian relief sector, we consider not only macro-level topological patterns, but also assortativity on the basis of micro-level organizational attributes. Unlike assortative social networks, this inter-organizational network exhibits disassortative or random patterns on three node attributes. We believe organizations' seek of complementarity is one of the main reasons for the special patterns. Our analysis also provides insights on how to promote collaborations among the humanitarian relief organizations.

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures.

PubMed

Cao, Peng; Liu, Xiaoli; Yang, Jinzhu; Zhao, Dazhe; Huang, Min; Zhang, Jian; Zaiane, Osmar

2017-12-01

Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their families. Making accurate diagnosis of AD based on brain magnetic resonance imaging (MRI) is becoming more and more critical and emphasized at the earliest stages. However, the high dimensionality and imbalanced data issues are two major challenges in the study of computer aided AD diagnosis. The greatest limitations of existing dimensionality reduction and over-sampling methods are that they assume a linear relationship between the MRI features (predictor) and the disease status (response). To better capture the complicated but more flexible relationship, we propose a multi-kernel based dimensionality reduction and over-sampling approaches. We combined Marginal Fisher Analysis with ℓ 2,1 -norm based multi-kernel learning (MKMFA) to achieve the sparsity of region-of-interest (ROI), which leads to simultaneously selecting a subset of the relevant brain regions and learning a dimensionality transformation. Meanwhile, a multi-kernel over-sampling (MKOS) was developed to generate synthetic instances in the optimal kernel space induced by MKMFA, so as to compensate for the class imbalanced distribution. We comprehensively evaluate the proposed models for the diagnostic classification (binary class and multi-class classification) including all subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The experimental results not only demonstrate the proposed method has superior performance over multiple comparable methods, but also identifies relevant imaging biomarkers that are consistent with prior medical knowledge. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parsimony and goodness-of-fit in multi-dimensional NMR inversion

NASA Astrophysics Data System (ADS)

Babak, Petro; Kryuchkov, Sergey; Kantzas, Apostolos

2017-01-01

Multi-dimensional nuclear magnetic resonance (NMR) experiments are often used for study of molecular structure and dynamics of matter in core analysis and reservoir evaluation. Industrial applications of multi-dimensional NMR involve a high-dimensional measurement dataset with complicated correlation structure and require rapid and stable inversion algorithms from the time domain to the relaxation rate and/or diffusion domains. In practice, applying existing inverse algorithms with a large number of parameter values leads to an infinite number of solutions with a reasonable fit to the NMR data. The interpretation of such variability of multiple solutions and selection of the most appropriate solution could be a very complex problem. In most cases the characteristics of materials have sparse signatures, and investigators would like to distinguish the most significant relaxation and diffusion values of the materials. To produce an easy to interpret and unique NMR distribution with the finite number of the principal parameter values, we introduce a new method for NMR inversion. The method is constructed based on the trade-off between the conventional goodness-of-fit approach to multivariate data and the principle of parsimony guaranteeing inversion with the least number of parameter values. We suggest performing the inversion of NMR data using the forward stepwise regression selection algorithm. To account for the trade-off between goodness-of-fit and parsimony, the objective function is selected based on Akaike Information Criterion (AIC). The performance of the developed multi-dimensional NMR inversion method and its comparison with conventional methods are illustrated using real data for samples with bitumen, water and clay.

A preliminary investigation of the growth of an aneurysm with a multiscale monolithic Fluid-Structure interaction solver

NASA Astrophysics Data System (ADS)

Cerroni, D.; Manservisi, S.; Pozzetti, G.

2015-11-01

In this work we investigate the potentialities of multi-scale engineering techniques to approach complex problems related to biomedical and biological fields. In particular we study the interaction between blood and blood vessel focusing on the presence of an aneurysm. The study of each component of the cardiovascular system is very difficult due to the fact that the movement of the fluid and solid is determined by the rest of system through dynamical boundary conditions. The use of multi-scale techniques allows us to investigate the effect of the whole loop on the aneurysm dynamic. A three-dimensional fluid-structure interaction model for the aneurysm is developed and coupled to a mono-dimensional one for the remaining part of the cardiovascular system, where a point zero-dimensional model for the heart is provided. In this manner it is possible to achieve rigorous and quantitative investigations of the cardiovascular disease without loosing the system dynamic. In order to study this biomedical problem we use a monolithic fluid-structure interaction (FSI) model where the fluid and solid equations are solved together. The use of a monolithic solver allows us to handle the convergence issues caused by large deformations. By using this monolithic approach different solid and fluid regions are treated as a single continuum and the interface conditions are automatically taken into account. In this way the iterative process characteristic of the commonly used segregated approach, it is not needed any more.

Study of multi-functional precision optical measuring system for large scale equipment

NASA Astrophysics Data System (ADS)

Jiang, Wei; Lao, Dabao; Zhou, Weihu; Zhang, Wenying; Jiang, Xingjian; Wang, Yongxi

2017-10-01

The effective application of high performance measurement technology can greatly improve the large-scale equipment manufacturing ability. Therefore, the geometric parameters measurement, such as size, attitude and position, requires the measurement system with high precision, multi-function, portability and other characteristics. However, the existing measuring instruments, such as laser tracker, total station, photogrammetry system, mostly has single function, station moving and other shortcomings. Laser tracker needs to work with cooperative target, but it can hardly meet the requirement of measurement in extreme environment. Total station is mainly used for outdoor surveying and mapping, it is hard to achieve the demand of accuracy in industrial measurement. Photogrammetry system can achieve a wide range of multi-point measurement, but the measuring range is limited and need to repeatedly move station. The paper presents a non-contact opto-electronic measuring instrument, not only it can work by scanning the measurement path but also measuring the cooperative target by tracking measurement. The system is based on some key technologies, such as absolute distance measurement, two-dimensional angle measurement, automatically target recognition and accurate aiming, precision control, assembly of complex mechanical system and multi-functional 3D visualization software. Among them, the absolute distance measurement module ensures measurement with high accuracy, and the twodimensional angle measuring module provides precision angle measurement. The system is suitable for the case of noncontact measurement of large-scale equipment, it can ensure the quality and performance of large-scale equipment throughout the process of manufacturing and improve the manufacturing ability of large-scale and high-end equipment.

Purchasing Nonprescription Contraceptives: The Underlying Structure of a Multi-Item Scale.

ERIC Educational Resources Information Center

Manolis, Chris; Winsor, Robert D.; True, Sheb L.

1999-01-01

Developed a multi-item scale for measuring attitudes associated with purchasing nonprescription contraceptives using construct specification and item generation and confirmatory factor analysis. Demonstrated a high degree of invariance across samples of 81 female and 115 male adult consumers. (SLD)

GENERAL: Scattering Phase Correction for Semiclassical Quantization Rules in Multi-Dimensional Quantum Systems

NASA Astrophysics Data System (ADS)

Huang, Wen-Min; Mou, Chung-Yu; Chang, Cheng-Hung

2010-02-01

While the scattering phase for several one-dimensional potentials can be exactly derived, less is known in multi-dimensional quantum systems. This work provides a method to extend the one-dimensional phase knowledge to multi-dimensional quantization rules. The extension is illustrated in the example of Bogomolny's transfer operator method applied in two quantum wells bounded by step potentials of different heights. This generalized semiclassical method accurately determines the energy spectrum of the systems, which indicates the substantial role of the proposed phase correction. Theoretically, the result can be extended to other semiclassical methods, such as Gutzwiller trace formula, dynamical zeta functions, and semiclassical Landauer-Büttiker formula. In practice, this recipe enhances the applicability of semiclassical methods to multi-dimensional quantum systems bounded by general soft potentials.

Digital Technology in the protection of cultural heritage Bao Fan Temple mural digital mapping survey

NASA Astrophysics Data System (ADS)

Zheng, Y.

2015-08-01

Peng Xi county, Sichuan province, the Bao Fan temple mural digitization survey mapping project: we use three-dimensional laserscanning, multi-baseline definition digital photography, multi-spectral digital image acquisition and other technologies for digital survey mapping. The purpose of this project is to use modern mathematical reconnaissance mapping means to obtain accurate mural shape, color, quality and other data. Combined with field investigation and laboratory analysis results, and based on a comprehensive survey and study, a comprehensive analysis of the historical Bao Fan Temple mural artistic and scientific value was conducted. A study of the mural's many qualities (structural, material, technique, preservation environment, degradation, etc.) reveal all aspects of the information carried by the Bao Fan Temple mural. From multiple angles (archeology, architecture, surveying, conservation science and other disciplines) an assessment for the Bao Fan Temple mural provides basic data and recommendations for conservation of the mural. In order to achieve the conservation of cultural relics in the Bao Fan Temple mural digitization survey mapping process, we try to apply the advantages of three-dimensional laser scanning equipment. For wall murals this means obtaining three-dimensional scale data from the scan of the building and through the analysis of these data to help determine the overall condition of the settlement as well as the deformation of the wall structure. Survey analysis provides an effective set of conclusions and suggestions for appropriate mural conservation. But before data collection, analysis and research need to first to select the appropriate scanning equipment, set the appropriate scanning accuracy and layout position of stations necessary to determine the scope of required data. We use the fine features of the three-dimensional laser scanning measuring arm to scan the mural surface deformation degradation to reflect the actual state of the mural surface patch model. For the degradation of the surface of the pigment layer, we use the patch model to simulate the scan obtained from an analysis. Statistics calculated relatively objective mural surface area from volume data, providing more accurate quantitative data for the mural conservation, especially, providing a viable technology for accurate monitoring of continued degradation. We believe, in order to make use of the three-dimensional laser scanning technology in a digital heritage conservation application, the technology should not only be used to record the object geometry and play a role in record keeping aspects, but, rather, should be used during the investigation to protect against targeted degradation and a more meaningful interpretation function. Like the development of the medical application of X-ray technology not only retains a picture, but more importantly, through this technical interpretation of patient pathology, guides doctors in carrying out the treatment work. Therefore, in the process of digitization of cultural heritage research, the focus should shift to the use of digital technology in the analysis of heritage object degradation and degradation monitoring surveys can promote the application of digital technology in the conservation of cultural heritage.

A New Time-varying Concept of Risk in a Changing Climate.

PubMed

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Multi-scale approach to the modeling of fission gas discharge during hypothetical loss-of-flow accident in gen-IV sodium fast reactor

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

Behafarid, F.; Shaver, D. R.; Bolotnov, I. A.

The required technological and safety standards for future Gen IV Reactors can only be achieved if advanced simulation capabilities become available, which combine high performance computing with the necessary level of modeling detail and high accuracy of predictions. The purpose of this paper is to present new results of multi-scale three-dimensional (3D) simulations of the inter-related phenomena, which occur as a result of fuel element heat-up and cladding failure, including the injection of a jet of gaseous fission products into a partially blocked Sodium Fast Reactor (SFR) coolant channel, and gas/molten sodium transport along the coolant channels. The computational approachmore » to the analysis of the overall accident scenario is based on using two different inter-communicating computational multiphase fluid dynamics (CMFD) codes: a CFD code, PHASTA, and a RANS code, NPHASE-CMFD. Using the geometry and time history of cladding failure and the gas injection rate, direct numerical simulations (DNS), combined with the Level Set method, of two-phase turbulent flow have been performed by the PHASTA code. The model allows one to track the evolution of gas/liquid interfaces at a centimeter scale. The simulated phenomena include the formation and breakup of the jet of fission products injected into the liquid sodium coolant. The PHASTA outflow has been averaged over time to obtain mean phasic velocities and volumetric concentrations, as well as the liquid turbulent kinetic energy and turbulence dissipation rate, all of which have served as the input to the core-scale simulations using the NPHASE-CMFD code. A sliding window time averaging has been used to capture mean flow parameters for transient cases. The results presented in the paper include testing and validation of the proposed models, as well the predictions of fission-gas/liquid-sodium transport along a multi-rod fuel assembly of SFR during a partial loss-of-flow accident. (authors)« less

Mixing effects on nitrogen and oxygen concentrations and the relationship to mean residence time in a hyporheic zone of a riffle-pool sequence

USGS Publications Warehouse

Naranjo, Ramon C.; Niswonger, Richard G.; Clinton Davis,

2015-01-01

Flow paths and residence times in the hyporheic zone are known to influence biogeochemical processes such as nitrification and denitrification. The exchange across the sediment-water interface may involve mixing of surface water and groundwater through complex hyporheic flow paths that contribute to highly variable biogeochemically active zones. Despite the recognition of these patterns in the literature, conceptualization and analysis of flow paths and nitrogen transformations beneath riffle-pool sequences often neglect to consider bed form driven exchange along the entire reach. In this study, the spatial and temporal distribution of dissolved oxygen (DO), nitrate (NO3-) and ammonium (NH4+) were monitored in the hyporheic zone beneath a riffle-pool sequence on a losing section of the Truckee River, NV. Spatially-varying hyporheic exchange and the occurrence of multi-scale hyporheic mixing cells are shown to influence concentrations of DO and NO3- and the mean residence time (MRT) of riffle and pool areas. Distinct patterns observed in piezometers are shown to be influenced by the first large flow event following a steady 8 month period of low flow conditions. Increases in surface water discharge resulted in reversed hydraulic gradients and production of nitrate through nitrification at small vertical spatial scales (0.10 to 0.25 m) beneath the sediment-water interface. In areas with high downward flow rates and low MRT, denitrification may be limited. The use of a longitudinal two-dimensional flow model helped identify important mechanisms such as multi-scale hyporheic mixing cells and spatially varying MRT, an important driver for nitrogen transformation in the riverbed. Our observations of DO and NO3- concentrations and model simulations highlight the role of multi-scale hyporheic mixing cells on MRT and nitrogen transformations in the hyporheic zone of riffle-pool sequences. This article is protected by copyright. All rights reserved.

The Development of an Instrument to Measure the Work Capability of People with Limited Work Capacity (LWC).

PubMed

van Ruitenbeek, Gemma M C; Zijlstra, Fred R H; Hülsheger, Ute R

2018-06-04

Purpose Participation in regular paid jobs positively affects mental and physical health of all people, including people with limited work capacities (LWC), people that are limited in their work capacity as a consequence of their disability, such as chronic mental illness, psychological or developmental disorder. For successful participation, a good fit between on one hand persons' capacities and on the other hand well-suited individual support and a suitable work environment is necessary in order to meet the demands of work. However, to date there is a striking paucity of validated measures that indicate the capability to work of people with LWC and that outline directions for support that facilitate the fit. Goal of the present study was therefore to develop such an instrument. Specifically, we adjusted measures of mental ability, conscientiousness, self-efficacy, and coping by simplifying the language level of these measures to make the scales accessible for people with low literacy. In order to validate these adjusted self-report and observer measures we conducted two studies, using multi-source, longitudinal data. Method Study 1 was a longitudinal multi-source study in which the newly developed instrument was administered twice to people with LWC and their significant other. We statistically tested the psychometric properties with respect to dimensionality and reliability. In Study 2, we collected new multi-source data and conducted a confirmatory factor analysis (CFA). Results Studies yielded a congruous factor structure in both samples, internally consistent measures with adequate content validity of scales and subscales, and high test-retest reliability. The CFA confirmed the factorial validity of the scales. Conclusion The adjusted self-report and the observer scales of mental ability, conscientiousness, self-efficacy, and coping are reliable measures that are well-suited to assess the work capability of people with LWC. Further research is needed to examine criterion-related validity with respect to the work demands such as work-behaviour and task performance.

Pattern recognition invariant under changes of scale and orientation

NASA Astrophysics Data System (ADS)

Arsenault, Henri H.; Parent, Sebastien; Moisan, Sylvain

1997-08-01

We have used a modified method proposed by neiberg and Casasent to successfully classify five kinds of military vehicles. The method uses a wedge filter to achieve scale invariance, and lines in a multi-dimensional feature space correspond to each target with out-of-plane orientations over 360 degrees around a vertical axis. The images were not binarized, but were filtered in a preprocessing step to reduce aliasing. The feature vectors were normalized and orthogonalized by means of a neural network. Out-of-plane rotations of 360 degrees and scale changes of a factor of four were considered. Error-free classification was achieved.

IUTAM Symposium and NATO Advanced Research Workshop on Interpretation of Time Series from Nonlinear Mechanical Systems Held in Coventry, England on 26-30 August 1991. Conference Abstracts

DTIC Science & Technology

1991-08-01

day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis 10:25 Coffee Break 10:50 Read Chaotic...day oscillation in the extratropical atmosphere as identified by multi-channel singular spectrum analysis M. Kimoto, M. Ghil and K.-C. Mo ABSTRACT...The three-dimensional spatial structure of an oscillatory mode in the Northern Hemisphere (NH) extratropics will be describe.d The oscillation is

Towards Careful Practices for Automated Linguistic Analysis of Group Learning

ERIC Educational Resources Information Center

Howley, Iris; Rosé, Carolyn Penstein

2016-01-01

The multifaceted nature of collaborative learning environments necessitates theory to investigate the cognitive, motivational, and relational dimensions of collaboration. Several existing frameworks include aspects related to each of these three. This article explores the capability of multi-dimensional frameworks for analysis of collaborative…

High Fidelity Modeling of Turbulent Mixing and Chemical Kinetics Interactions in a Post-Detonation Flow Field

NASA Astrophysics Data System (ADS)

Sinha, Neeraj; Zambon, Andrea; Ott, James; Demagistris, Michael

2015-06-01

Driven by the continuing rapid advances in high-performance computing, multi-dimensional high-fidelity modeling is an increasingly reliable predictive tool capable of providing valuable physical insight into complex post-detonation reacting flow fields. Utilizing a series of test cases featuring blast waves interacting with combustible dispersed clouds in a small-scale test setup under well-controlled conditions, the predictive capabilities of a state-of-the-art code are demonstrated and validated. Leveraging physics-based, first principle models and solving large system of equations on highly-resolved grids, the combined effects of finite-rate/multi-phase chemical processes (including thermal ignition), turbulent mixing and shock interactions are captured across the spectrum of relevant time-scales and length scales. Since many scales of motion are generated in a post-detonation environment, even if the initial ambient conditions are quiescent, turbulent mixing plays a major role in the fireball afterburning as well as in dispersion, mixing, ignition and burn-out of combustible clouds in its vicinity. Validating these capabilities at the small scale is critical to establish a reliable predictive tool applicable to more complex and large-scale geometries of practical interest.

Personalized medicine: from genotypes, molecular phenotypes and the quantified self, towards improved medicine.

PubMed

Dudley, Joel T; Listgarten, Jennifer; Stegle, Oliver; Brenner, Steven E; Parts, Leopold

2015-01-01

Advances in molecular profiling and sensor technologies are expanding the scope of personalized medicine beyond genotypes, providing new opportunities for developing richer and more dynamic multi-scale models of individual health. Recent studies demonstrate the value of scoring high-dimensional microbiome, immune, and metabolic traits from individuals to inform personalized medicine. Efforts to integrate multiple dimensions of clinical and molecular data towards predictive multi-scale models of individual health and wellness are already underway. Improved methods for mining and discovery of clinical phenotypes from electronic medical records and technological developments in wearable sensor technologies present new opportunities for mapping and exploring the critical yet poorly characterized "phenome" and "envirome" dimensions of personalized medicine. There are ambitious new projects underway to collect multi-scale molecular, sensor, clinical, behavioral, and environmental data streams from large population cohorts longitudinally to enable more comprehensive and dynamic models of individual biology and personalized health. Personalized medicine stands to benefit from inclusion of rich new sources and dimensions of data. However, realizing these improvements in care relies upon novel informatics methodologies, tools, and systems to make full use of these data to advance both the science and translational applications of personalized medicine.

High Performance Analytics with the R3-Cache

NASA Astrophysics Data System (ADS)

Eavis, Todd; Sayeed, Ruhan

Contemporary data warehouses now represent some of the world’s largest databases. As these systems grow in size and complexity, however, it becomes increasingly difficult for brute force query processing approaches to meet the performance demands of end users. Certainly, improved indexing and more selective view materialization are helpful in this regard. Nevertheless, with warehouses moving into the multi-terabyte range, it is clear that the minimization of external memory accesses must be a primary performance objective. In this paper, we describe the R 3-cache, a natively multi-dimensional caching framework designed specifically to support sophisticated warehouse/OLAP environments. R 3-cache is based upon an in-memory version of the R-tree that has been extended to support buffer pages rather than disk blocks. A key strength of the R 3-cache is that it is able to utilize multi-dimensional fragments of previous query results so as to significantly minimize the frequency and scale of disk accesses. Moreover, the new caching model directly accommodates the standard relational storage model and provides mechanisms for pro-active updates that exploit the existence of query “hot spots”. The current prototype has been evaluated as a component of the Sidera DBMS, a “shared nothing” parallel OLAP server designed for multi-terabyte analytics. Experimental results demonstrate significant performance improvements relative to simpler alternatives.

Multi-Scale Simulations of Carbon Nanotubes: Mechanics and Electronics

NASA Technical Reports Server (NTRS)

Srivastava, Deepak

2003-01-01

Carbon Nanotube (CNT) is a tubular form of carbon with diameter as small as 1 nm. Length: few mn to microns. CNT is configurationally equivalent to a two dimensional graphene sheet rolled into a tube. CNT exhibits extraordinary mechanical properties; Young's modulus over 1 Tera Pascal, as stiff as diamond, and tensile strength approx. 200 GPa. CNT can be metallic or semiconducting, depending on chirality.

Motivation and Engagement in the United States, Canada, United Kingdom, Australia, and China: Testing a Multi-Dimensional Framework

ERIC Educational Resources Information Center

Martin, Andrew J.; Yu, Kai; Papworth, Brad; Ginns, Paul; Collie, Rebecca J.

2015-01-01

This study explored motivation and engagement among North American (the United States and Canada; n = 1,540), U.K. (n = 1,558), Australian (n = 2,283), and Chinese (n = 3,753) secondary school students. Motivation and engagement were assessed via students' responses to the Motivation and Engagement Scale-High School (MES-HS). Confirmatory factor…

Note: An absolute X-Y-Θ position sensor using a two-dimensional phase-encoded binary scale

NASA Astrophysics Data System (ADS)

Kim, Jong-Ahn; Kim, Jae Wan; Kang, Chu-Shik; Jin, Jonghan

2018-04-01

This Note presents a new absolute X-Y-Θ position sensor for measuring planar motion of a precision multi-axis stage system. By analyzing the rotated image of a two-dimensional phase-encoded binary scale (2D), the absolute 2D position values at two separated points were obtained and the absolute X-Y-Θ position could be calculated combining these values. The sensor head was constructed using a board-level camera, a light-emitting diode light source, an imaging lens, and a cube beam-splitter. To obtain the uniform intensity profiles from the vignette scale image, we selected the averaging directions deliberately, and higher resolution in the angle measurement could be achieved by increasing the allowable offset size. The performance of a prototype sensor was evaluated in respect of resolution, nonlinearity, and repeatability. The sensor could resolve 25 nm linear and 0.001° angular displacements clearly, and the standard deviations were less than 18 nm when 2D grid positions were measured repeatedly.

Hemodynamic analysis of sequential graft from right coronary system to left coronary system.

PubMed

Wang, Wenxin; Mao, Boyan; Wang, Haoran; Geng, Xueying; Zhao, Xi; Zhang, Huixia; Xie, Jinsheng; Zhao, Zhou; Lian, Bo; Liu, Youjun

2016-12-28

Sequential and single grafting are two surgical procedures of coronary artery bypass grafting. However, it remains unclear if the sequential graft can be used between the right and left coronary artery system. The purpose of this paper is to clarify the possibility of right coronary artery system anastomosis to left coronary system. A patient-specific 3D model was first reconstructed based on coronary computed tomography angiography (CCTA) images. Two different grafts, the normal multi-graft (Model 1) and the novel multi-graft (Model 2), were then implemented on this patient-specific model using virtual surgery techniques. In Model 1, the single graft was anastomosed to right coronary artery (RCA) and the sequential graft was adopted to anastomose left anterior descending (LAD) and left circumflex artery (LCX). While in Model 2, the single graft was anastomosed to LAD and the sequential graft was adopted to anastomose RCA and LCX. A zero-dimensional/three-dimensional (0D/3D) coupling method was used to realize the multi-scale simulation of both the pre-operative and two post-operative models. Flow rates in the coronary artery and grafts were obtained. The hemodynamic parameters were also showed, including wall shear stress (WSS) and oscillatory shear index (OSI). The area of low WSS and OSI in Model 1 was much less than that in Model 2. Model 1 shows optimistic hemodynamic modifications which may enhance the long-term patency of grafts. The anterior segments of sequential graft have better long-term patency than the posterior segments. With rational spatial position of the heart vessels, the last anastomosis of sequential graft should be connected to the main branch.

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, George P.; Skeate, Michael F.

1996-01-01

An apparatus for multi-dimensional computation which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination.

Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD

NASA Astrophysics Data System (ADS)

Favorskaya, M. N.; Savchina, E. I.

2017-05-01

Medical Image Watermarking (MIW) is a special field of a watermarking due to the requirements of the Digital Imaging and COmmunications in Medicine (DICOM) standard since 1993. All 20 parts of the DICOM standard are revised periodically. The main idea of the MIW is to embed various types of information including the doctor's digital signature, fragile watermark, electronic patient record, and main watermark in a view of region of interest for the doctor into the host medical image. These four types of information are represented in different forms; some of them are encrypted according to the DICOM requirements. However, all types of information ought to be resulted into the generalized binary stream for embedding. The generalized binary stream may have a huge volume. Therefore, not all watermarking methods can be applied successfully. Recently, the digital shearlet transform had been introduced as a rigorous mathematical framework for the geometric representation of multi-dimensional data. Some modifications of the shearlet transform, particularly the non-subsampled shearlet transform, can be associated to a multi-resolution analysis that provides a fully shift-invariant, multi-scale, and multi-directional expansion. During experiments, a quality of the extracted watermarks under the JPEG compression and typical internet attacks was estimated using several metrics, including the peak signal to noise ratio, structural similarity index measure, and bit error rate.

Design synthesis and optimization of permanent magnet synchronous machines based on computationally-efficient finite element analysis

NASA Astrophysics Data System (ADS)

Sizov, Gennadi Y.

In this dissertation, a model-based multi-objective optimal design of permanent magnet ac machines, supplied by sine-wave current regulated drives, is developed and implemented. The design procedure uses an efficient electromagnetic finite element-based solver to accurately model nonlinear material properties and complex geometric shapes associated with magnetic circuit design. Application of an electromagnetic finite element-based solver allows for accurate computation of intricate performance parameters and characteristics. The first contribution of this dissertation is the development of a rapid computational method that allows accurate and efficient exploration of large multi-dimensional design spaces in search of optimum design(s). The computationally efficient finite element-based approach developed in this work provides a framework of tools that allow rapid analysis of synchronous electric machines operating under steady-state conditions. In the developed modeling approach, major steady-state performance parameters such as, winding flux linkages and voltages, average, cogging and ripple torques, stator core flux densities, core losses, efficiencies and saturated machine winding inductances, are calculated with minimum computational effort. In addition, the method includes means for rapid estimation of distributed stator forces and three-dimensional effects of stator and/or rotor skew on the performance of the machine. The second contribution of this dissertation is the development of the design synthesis and optimization method based on a differential evolution algorithm. The approach relies on the developed finite element-based modeling method for electromagnetic analysis and is able to tackle large-scale multi-objective design problems using modest computational resources. Overall, computational time savings of up to two orders of magnitude are achievable, when compared to current and prevalent state-of-the-art methods. These computational savings allow one to expand the optimization problem to achieve more complex and comprehensive design objectives. The method is used in the design process of several interior permanent magnet industrial motors. The presented case studies demonstrate that the developed finite element-based approach practically eliminates the need for using less accurate analytical and lumped parameter equivalent circuit models for electric machine design optimization. The design process and experimental validation of the case-study machines are detailed in the dissertation.

Visualizing Phenology and Climate Data at the National Scale

NASA Astrophysics Data System (ADS)

Rosemartin, A.; Marsh, L.

2013-12-01

Nature's Notebook is the USA National Phenology Network's national-scale plant and animal phenology observation program, designed to address the challenges posed by global change and its impacts on ecosystems and human health. Since its inception in 2009, 2,500 participants in Nature's Notebook have submitted 2.3 million records on the phenology of 17,000 organisms across the United States. An information architecture has been developed to facilitate collaboration and participatory data collection and digitization. Browser-based and mobile applications support data submission, and a MySQL/Drupal multi-site infrastructure enables data storage, access and discovery. Web services are available for both input and export of data resources. In this presentation we will focus on a tool for visualizing phenology data at the national scale. Effective data exploration for this multi-dimensional dataset requires the ability to plot sites, select species and phenophases, graph organismal phenology through time, and view integrated precipitation and temperature data. We will demonstrate the existing tool's capacity, discuss future directions and solicit feedback from the community.

EDDA 1.0: integrated simulation of debris flow erosion, deposition and property changes

NASA Astrophysics Data System (ADS)

Chen, H. X.; Zhang, L. M.

2015-03-01

Debris flow material properties change during the initiation, transportation and deposition processes, which influences the runout characteristics of the debris flow. A quasi-three-dimensional depth-integrated numerical model, EDDA (Erosion-Deposition Debris flow Analysis), is presented in this paper to simulate debris flow erosion, deposition and induced material property changes. The model considers changes in debris flow density, yield stress and dynamic viscosity during the flow process. The yield stress of the debris flow mixture determined at limit equilibrium using the Mohr-Coulomb equation is applicable to clear water flow, hyper-concentrated flow and fully developed debris flow. To assure numerical stability and computational efficiency at the same time, an adaptive time stepping algorithm is developed to solve the governing differential equations. Four numerical tests are conducted to validate the model. The first two tests involve a one-dimensional debris flow with constant properties and a two-dimensional dam-break water flow. The last two tests involve erosion and deposition, and the movement of multi-directional debris flows. The changes in debris flow mass and properties due to either erosion or deposition are shown to affect the runout characteristics significantly. The model is also applied to simulate a large-scale debris flow in Xiaojiagou Ravine to test the performance of the model in catchment-scale simulations. The results suggest that the model estimates well the volume, inundated area, and runout distance of the debris flow. The model is intended for use as a module in a real-time debris flow warning system.

O the Development and Use of Four-Dimensional Data Assimilation in Limited-Area Mesoscale Models Used for Meteorological Analysis.

NASA Astrophysics Data System (ADS)

Stauffer, David R.

1990-01-01

The application of dynamic relationships to the analysis problem for the atmosphere is extended to use a full-physics limited-area mesoscale model as the dynamic constraint. A four-dimensional data assimilation (FDDA) scheme based on Newtonian relaxation or "nudging" is developed and evaluated in the Penn State/National Center for Atmospheric Research (PSU/NCAR) mesoscale model, which is used here as a dynamic-analysis tool. The thesis is to determine what assimilation strategies and what meterological fields (mass, wind or both) have the greatest positive impact on the 72-h numerical simulations (dynamic analyses) of two mid-latitude, real-data cases. The basic FDDA methodology is tested in a 10-layer version of the model with a bulk-aerodynamic (single-layer) representation of the planetary boundary layer (PBL), and refined in a 15-layer version of the model by considering the effects of data assimilation within a multi-layer PBL scheme. As designed, the model solution can be relaxed toward either gridded analyses ("analysis nudging"), or toward the actual observations ("obs nudging"). The data used for assimilation include standard 12-hourly rawinsonde data, and also 3-hourly mesoalpha-scale surface data which are applied within the model's multi-layer PBL. Continuous assimilation of standard-resolution rawinsonde data into the 10-layer model successfully reduced large-scale amplitude and phase errors while the model realistically simulated mesoscale structures poorly defined or absent in the rawinsonde analyses and in the model simulations without FDDA. Nudging the model fields directly toward the rawinsonde observations generally produced results comparable to nudging toward gridded analyses. This obs -nudging technique is especially attractive for the assimilation of high-frequency, asynoptic data. Assimilation of 3-hourly surface wind and moisture data into the 15-layer FDDA system was most effective for improving the simulated precipitation fields because a significant portion of the vertically integrated moisture convergence often occurs in the PBL. Overall, the best dynamic analyses for the PBL, mass, wind and precipitation fields were obtained by nudging toward analyses of rawinsonde wind, temperature and moisture (the latter uses a weaker nudging coefficient) above the model PBL and toward analyses of surface-layer wind and moisture within the model PBL.

Multidisciplinary tailoring of hot composite structures

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.; Chamis, Christos C.

1993-01-01

A computational simulation procedure is described for multidisciplinary analysis and tailoring of layered multi-material hot composite engine structural components subjected to simultaneous multiple discipline-specific thermal, structural, vibration, and acoustic loads. The effect of aggressive environments is also simulated. The simulation is based on a three-dimensional finite element analysis technique in conjunction with structural mechanics codes, thermal/acoustic analysis methods, and tailoring procedures. The integrated multidisciplinary simulation procedure is general-purpose including the coupled effects of nonlinearities in structure geometry, material, loading, and environmental complexities. The composite material behavior is assessed at all composite scales, i.e., laminate/ply/constituents (fiber/matrix), via a nonlinear material characterization hygro-thermo-mechanical model. Sample tailoring cases exhibiting nonlinear material/loading/environmental behavior of aircraft engine fan blades, are presented. The various multidisciplinary loads lead to different tailored designs, even those competing with each other, as in the case of minimum material cost versus minimum structure weight and in the case of minimum vibration frequency versus minimum acoustic noise.

Generation Algorithm of Discrete Line in Multi-Dimensional Grids

NASA Astrophysics Data System (ADS)

Du, L.; Ben, J.; Li, Y.; Wang, R.

2017-09-01

Discrete Global Grids System (DGGS) is a kind of digital multi-resolution earth reference model, in terms of structure, it is conducive to the geographical spatial big data integration and mining. Vector is one of the important types of spatial data, only by discretization, can it be applied in grids system to make process and analysis. Based on the some constraint conditions, this paper put forward a strict definition of discrete lines, building a mathematic model of the discrete lines by base vectors combination method. Transforming mesh discrete lines issue in n-dimensional grids into the issue of optimal deviated path in n-minus-one dimension using hyperplane, which, therefore realizing dimension reduction process in the expression of mesh discrete lines. On this basis, we designed a simple and efficient algorithm for dimension reduction and generation of the discrete lines. The experimental results show that our algorithm not only can be applied in the two-dimensional rectangular grid, also can be applied in the two-dimensional hexagonal grid and the three-dimensional cubic grid. Meanwhile, when our algorithm is applied in two-dimensional rectangular grid, it can get a discrete line which is more similar to the line in the Euclidean space.

Multi-scale simulations of space problems with iPIC3D

NASA Astrophysics Data System (ADS)

Lapenta, Giovanni; Bettarini, Lapo; Markidis, Stefano

The implicit Particle-in-Cell method for the computer simulation of space plasma, and its im-plementation in a three-dimensional parallel code, called iPIC3D, are presented. The implicit integration in time of the Vlasov-Maxwell system removes the numerical stability constraints and enables kinetic plasma simulations at magnetohydrodynamics scales. Simulations of mag-netic reconnection in plasma are presented to show the effectiveness of the algorithm. In particular we will show a number of simulations done for large scale 3D systems using the physical mass ratio for Hydrogen. Most notably one simulation treats kinetically a box of tens of Earth radii in each direction and was conducted using about 16000 processors of the Pleiades NASA computer. The work is conducted in collaboration with the MMS-IDS theory team from University of Colorado (M. Goldman, D. Newman and L. Andersson). Reference: Stefano Markidis, Giovanni Lapenta, Rizwan-uddin Multi-scale simulations of plasma with iPIC3D Mathematics and Computers in Simulation, Available online 17 October 2009, http://dx.doi.org/10.1016/j.matcom.2009.08.038

Fine-scale multi-species aggregations of oceanic zooplankton

NASA Astrophysics Data System (ADS)

Haury, L. R.; Wiebe, P. H.

1982-07-01

Sixteen Longhurst-Hardy Plankton Recorder tows were taken at different depths in the northwest Atlantic for analysis of fine-scale horizontal patchiness. Abundant species were non-randomly distributed in patches with scales of tens to hundreds of meters. Positive correlations between species abundances dominated, indicating that the patches were multi-species associations. Most horizontal pattern appeared to be of biological origin.

The positive mental health instrument: development and validation of a culturally relevant scale in a multi-ethnic Asian population.

PubMed

Vaingankar, Janhavi Ajit; Subramaniam, Mythily; Chong, Siow Ann; Abdin, Edimansyah; Orlando Edelen, Maria; Picco, Louisa; Lim, Yee Wei; Phua, Mei Yen; Chua, Boon Yiang; Tee, Joseph Y S; Sherbourne, Cathy

2011-10-31

Instruments to measure mental health and well-being are largely developed and often used within Western populations and this compromises their validity in other cultures. A previous qualitative study in Singapore demonstrated the relevance of spiritual and religious practices to mental health, a dimension currently not included in exiting multi-dimensional measures. The objective of this study was to develop a self-administered measure that covers all key and culturally appropriate domains of mental health, which can be applied to compare levels of mental health across different age, gender and ethnic groups. We present the item reduction and validation of the Positive Mental Health (PMH) instrument in a community-based adult sample in Singapore. Surveys were conducted among adult (21-65 years) residents belonging to Chinese, Malay and Indian ethnicities. Exploratory and confirmatory factor analysis (EFA, CFA) were conducted and items were reduced using item response theory tests (IRT). The final version of the PMH instrument was tested for internal consistency and criterion validity. Items were tested for differential item functioning (DIF) to check if items functioned in the same way across all subgroups. EFA and CFA identified six first-order factor structure (General coping, Personal growth and autonomy, Spirituality, Interpersonal skills, Emotional support, and Global affect) under one higher-order dimension of Positive Mental Health (RMSEA=0.05, CFI=0.96, TLI=0.96). A 47-item self-administered multi-dimensional instrument with a six-point Likert response scale was constructed. The slope estimates and strength of the relation to the theta for all items in each six PMH subscales were high (range:1.39 to 5.69), suggesting good discrimination properties. The threshold estimates for the instrument ranged from -3.45 to 1.61 indicating that the instrument covers entire spectrums for the six dimensions. The instrument demonstrated high internal consistency and had significant and expected correlations with other well-being measures. Results confirmed absence of DIF. The PMH instrument is a reliable and valid instrument that can be used to measure and compare level of mental health across different age, gender and ethnic groups in Singapore.

Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.

2005-01-01

This document is the final report for the project entitled, "Multi-Scale Sizing of Lightweight Multifunctional Spacecraft Structural Components," funded under the NRA entitled "Cross-Enterprise Technology Development Program" issued by the NASA Office of Space Science in 2000. The project was funded in 2001, and spanned a four year period from March, 2001 to February, 2005. Through enhancements to and synthesis of unique, state of the art structural mechanics and micromechanics analysis software, a new multi-scale tool has been developed that enables design, analysis, and sizing of advance lightweight composite and smart materials and structures from the full vehicle, to the stiffened structure, to the micro (fiber and matrix) scales. The new software tool has broad, cross-cutting value to current and future NASA missions that will rely on advanced composite and smart materials and structures.

COMPARISONS AND CONTRASTS AMONG DIFFERENT SCALED ASSESSMENTS

EPA Science Inventory

A comparison of a regional (multi-state) and local (multi-county) scale assessment was done to evaluate similarities and differences in the collection, analysis, and interpretation of landscape data. The study areas included EP A Region 3 a11d a sub-region spanning North and Sout...

Large-scale hydropower system optimization using dynamic programming and object-oriented programming: the case of the Northeast China Power Grid.

PubMed

Li, Ji-Qing; Zhang, Yu-Shan; Ji, Chang-Ming; Wang, Ai-Jing; Lund, Jay R

2013-01-01

This paper examines long-term optimal operation using dynamic programming for a large hydropower system of 10 reservoirs in Northeast China. Besides considering flow and hydraulic head, the optimization explicitly includes time-varying electricity market prices to maximize benefit. Two techniques are used to reduce the 'curse of dimensionality' of dynamic programming with many reservoirs. Discrete differential dynamic programming (DDDP) reduces the search space and computer memory needed. Object-oriented programming (OOP) and the ability to dynamically allocate and release memory with the C++ language greatly reduces the cumulative effect of computer memory for solving multi-dimensional dynamic programming models. The case study shows that the model can reduce the 'curse of dimensionality' and achieve satisfactory results.

Control electronics for a multi-laser/multi-detector scanning system

NASA Technical Reports Server (NTRS)

Kennedy, W.

1980-01-01

The Mars Rover Laser Scanning system uses a precision laser pointing mechanism, a photodetector array, and the concept of triangulation to perform three dimensional scene analysis. The system is used for real time terrain sensing and vision. The Multi-Laser/Multi-Detector laser scanning system is controlled by a digital device called the ML/MD controller. A next generation laser scanning system, based on the Level 2 controller, is microprocessor based. The new controller capabilities far exceed those of the ML/MD device. The first draft circuit details and general software structure are presented.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Flow and Temperature Distribution Evaluation on Sodium Heated Large-sized Straight Double-wall-tube Steam Generator

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

Kisohara, Naoyuki; Moribe, Takeshi; Sakai, Takaaki

2006-07-01

The sodium heated steam generator (SG) being designed in the feasibility study on commercialized fast reactor cycle systems is a straight double-wall-tube type. The SG is large sized to reduce its manufacturing cost by economics of scale. This paper addresses the temperature and flow multi-dimensional distributions at steady state to obtain the prospect of the SG. Large-sized heat exchanger components are prone to have non-uniform flow and temperature distributions. These phenomena might lead to tube buckling or tube to tube-sheet junction failure in straight tube type SGs, owing to tubes thermal expansion difference. The flow adjustment devices installed in themore » SG are optimized to prevent these issues, and the temperature distribution properties are uncovered by analysis methods. The analysis model of the SG consists of two parts, a sodium inlet distribution plenum (the plenum) and a heat transfer tubes bundle region (the bundle). The flow and temperature distributions in the plenum and the bundle are evaluated by the three-dimensional code 'FLUENT' and the two dimensional thermal-hydraulic code 'MSG', respectively. The MSG code is particularly developed for sodium heated SGs in JAEA. These codes have revealed that the sodium flow is distributed uniformly by the flow adjustment devices, and that the lateral tube temperature distributions remain within the allowable temperature range for the structural integrity of the tubes and the tube to tube-sheet junctions. (authors)« less

Origin of Permeability and Structure of Flows in Fractured Media

NASA Astrophysics Data System (ADS)

De Dreuzy, J.; Darcel, C.; Davy, P.; Erhel, J.; Le Goc, R.; Maillot, J.; Meheust, Y.; Pichot, G.; Poirriez, B.

2013-12-01

After more than three decades of research, flows in fractured media have been shown to result from multi-scale geological structures. Flows result non-exclusively from the damage zone of the large faults, from the percolation within denser networks of smaller fractures, from the aperture heterogeneity within the fracture planes and from some remaining permeability within the matrix. While the effect of each of these causes has been studied independently, global assessments of the main determinisms is still needed. We propose a general approach to determine the geological structures responsible for flows, their permeability and their organization based on field data and numerical modeling [de Dreuzy et al., 2012b]. Multi-scale synthetic networks are reconstructed from field data and simplified mechanical modeling [Davy et al., 2010]. High-performance numerical methods are developed to comply with the specificities of the geometry and physical properties of the fractured media [Pichot et al., 2010; Pichot et al., 2012]. And, based on a large Monte-Carlo sampling, we determine the key determinisms of fractured permeability and flows (Figure). We illustrate our approach on the respective influence of fracture apertures and fracture correlation patterns at large scale. We show the potential role of fracture intersections, so far overlooked between the fracture and the network scales. We also demonstrate how fracture correlations reduce the bulk fracture permeability. Using this analysis, we highlight the need for more specific in-situ characterization of fracture flow structures. Fracture modeling and characterization are necessary to meet the new requirements of a growing number of applications where fractures appear both as potential advantages to enhance permeability and drawbacks for safety, e.g. in energy storage, stimulated geothermal energy and non-conventional gas productions. References Davy, P., et al. (2010), A likely universal model of fracture scaling and its consequence for crustal hydromechanics, Journal of Geophysical Research-Solid Earth, 115, 13. de Dreuzy, J.-R., et al. (2012a), Influence of fracture scale heterogeneity on the flow properties of three-dimensional Discrete Fracture Networks (DFN), J. Geophys. Res.-Earth Surf., 117(B11207), 21 PP. de Dreuzy, J.-R., et al. (2012b), Synthetic benchmark for modeling flow in 3D fractured media, Computers and Geosciences(0). Pichot, G., et al. (2010), A Mixed Hybrid Mortar Method for solving flow in Discrete Fracture Networks, Applicable Analysis, 89(10), 1729-1643. Pichot, G., et al. (2012), Flow simulation in 3D multi-scale fractured networks using non-matching meshes, SIAM Journal on Scientific Computing (SISC), 34(1). Figure: (a) Fracture network with a broad-range of fracture lengths. (b) Flows (log-scale) with homogeneous fractures. (c) Flows (log-scale) with heterogeneous fractures [de Dreuzy et al., 2012a]. The impact of the fracture apertures (c) is illustrated on the organization of flows.

Theoretical study of the effect of an AlGaAs double heterostructure on metal-semiconductor-metal photodetector performance

NASA Technical Reports Server (NTRS)

Salem, Ali F.; Smith, Arlynn W.; Brennan, Kevin F.

1994-01-01

The sizing and efficiency of an aircraft is largely determined by the performance of its high-lift system. Subsonic civil transports most often use deployable multi-element airfoils to achieve the maximum-lift requirements for landing, as well as the high lift-to-drag ratios for take-off. However, these systems produce very complex flow fields which are not fully understood by the scientific community. In order to compete in today's market place, aircraft manufacturers will have to design better high-lift systems. Therefore, a more thorough understanding of the flows associated with these systems is desired. Flight and wind-tunnel experiments have been conducted on NASA Langley's B737-100 research aircraft to obtain detailed full-scale flow measurements on a multi-element high-lift system at various flight conditions. As part of this effort, computational aerodynamic tools are being used to provide preliminary flow-field information for instrumentation development, and to provide additional insight during the data analysis and interpretation process. The purpose of this paper is to demonstrate the ability and usefulness of a three-dimensional low-order potentialflow solver, PMARC, by comparing computational results with data obtained from 1/8 scale wind-tunnel tests. Overall, correlation of experimental and computational data reveals that the panel method is able to predict reasonably well the pressures of the aircraft's multi-element wing at several spanwise stations. PMARC's versatility and usefulness is also demonstrated by accurately predicting inviscid threedimensional flow features for several intricate geometrical regions.

Facile multi-dimensional profiling of chemical gradients at the millimetre scale.

PubMed

Chen, Chih-Lin; Hsieh, Kai-Ta; Hsu, Ching-Fong; Urban, Pawel L

2016-01-07

A vast number of conventional physicochemical methods are suitable for the analysis of homogeneous samples. However, in various cases, the samples exhibit intrinsic heterogeneity. Tomography allows one to record approximate distributions of chemical species in the three-dimensional space. Here we develop a simple optical tomography system which enables performing scans of non-homogeneous samples at different wavelengths. It takes advantage of inexpensive open-source electronics and simple algorithms. The analysed samples are illuminated by a miniature LCD/LED screen which emits light at three wavelengths (598, 547 and 455 nm, corresponding to the R, G, and B channels, respectively). On presentation of every wavelength, the sample vial is rotated by ∼180°, and videoed at 30 frames per s. The RGB values of pixels in the obtained digital snapshots are subsequently collated, and processed to produce sinograms. Following the inverse Radon transform, approximate quasi-three-dimensional images are reconstructed for each wavelength. Sample components with distinct visible light absorption spectra (myoglobin, methylene blue) can be resolved. The system was used to follow dynamic changes in non-homogeneous samples in real time, to visualize binary mixtures, to reconstruct reaction-diffusion fronts formed during the reduction of 2,6-dichlorophenolindophenol by ascorbic acid, and to visualize the distribution of fungal mycelium grown in a semi-solid medium.

Euclidean chemical spaces from molecular fingerprints: Hamming distance and Hempel's ravens.

PubMed

Martin, Eric; Cao, Eddie

2015-05-01

Molecules are often characterized by sparse binary fingerprints, where 1s represent the presence of substructures and 0s represent their absence. Fingerprints are especially useful for similarity calculations, such as database searching or clustering, generally measuring similarity as the Tanimoto coefficient. In other cases, such as visualization, design of experiments, or latent variable regression, a low-dimensional Euclidian "chemical space" is more useful, where proximity between points reflects chemical similarity. A temptation is to apply principal components analysis (PCA) directly to these fingerprints to obtain a low dimensional continuous chemical space. However, Gower has shown that distances from PCA on bit vectors are proportional to the square root of Hamming distance. Unlike Tanimoto similarity, Hamming similarity (HS) gives equal weight to shared 0s as to shared 1s, that is, HS gives as much weight to substructures that neither molecule contains, as to substructures which both molecules contain. Illustrative examples show that proximity in the corresponding chemical space reflects mainly similar size and complexity rather than shared chemical substructures. These spaces are ill-suited for visualizing and optimizing coverage of chemical space, or as latent variables for regression. A more suitable alternative is shown to be Multi-dimensional scaling on the Tanimoto distance matrix, which produces a space where proximity does reflect structural similarity.

Pedagogical Factors Stimulating the Self-Development of Students' Multi-Dimensional Thinking in Terms of Subject-Oriented Teaching

ERIC Educational Resources Information Center

Andreev, Valentin I.

2014-01-01

The main aim of this research is to disclose the essence of students' multi-dimensional thinking, also to reveal the rating of factors which stimulate the raising of effectiveness of self-development of students' multi-dimensional thinking in terms of subject-oriented teaching. Subject-oriented learning is characterized as a type of learning where…

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Seismic signal time-frequency analysis based on multi-directional window using greedy strategy

NASA Astrophysics Data System (ADS)

Chen, Yingpin; Peng, Zhenming; Cheng, Zhuyuan; Tian, Lin

2017-08-01

Wigner-Ville distribution (WVD) is an important time-frequency analysis technology with a high energy distribution in seismic signal processing. However, it is interfered by many cross terms. To suppress the cross terms of the WVD and keep the concentration of its high energy distribution, an adaptive multi-directional filtering window in the ambiguity domain is proposed. This begins with the relationship of the Cohen distribution and the Gabor transform combining the greedy strategy and the rotational invariance property of the fractional Fourier transform in order to propose the multi-directional window, which extends the one-dimensional, one directional, optimal window function of the optimal fractional Gabor transform (OFrGT) to a two-dimensional, multi-directional window in the ambiguity domain. In this way, the multi-directional window matches the main auto terms of the WVD more precisely. Using the greedy strategy, the proposed window takes into account the optimal and other suboptimal directions, which also solves the problem of the OFrGT, called the local concentration phenomenon, when encountering a multi-component signal. Experiments on different types of both the signal models and the real seismic signals reveal that the proposed window can overcome the drawbacks of the WVD and the OFrGT mentioned above. Finally, the proposed method is applied to a seismic signal's spectral decomposition. The results show that the proposed method can explore the space distribution of a reservoir more precisely.

Telescopic multi-resolution augmented reality

NASA Astrophysics Data System (ADS)

Jenkins, Jeffrey; Frenchi, Christopher; Szu, Harold

2014-05-01

To ensure a self-consistent scaling approximation, the underlying microscopic fluctuation components can naturally influence macroscopic means, which may give rise to emergent observable phenomena. In this paper, we describe a consistent macroscopic (cm-scale), mesoscopic (micron-scale), and microscopic (nano-scale) approach to introduce Telescopic Multi-Resolution (TMR) into current Augmented Reality (AR) visualization technology. We propose to couple TMR-AR by introducing an energy-matter interaction engine framework that is based on known Physics, Biology, Chemistry principles. An immediate payoff of TMR-AR is a self-consistent approximation of the interaction between microscopic observables and their direct effect on the macroscopic system that is driven by real-world measurements. Such an interdisciplinary approach enables us to achieve more than multiple scale, telescopic visualization of real and virtual information but also conducting thought experiments through AR. As a result of the consistency, this framework allows us to explore a large dimensionality parameter space of measured and unmeasured regions. Towards this direction, we explore how to build learnable libraries of biological, physical, and chemical mechanisms. Fusing analytical sensors with TMR-AR libraries provides a robust framework to optimize testing and evaluation through data-driven or virtual synthetic simulations. Visualizing mechanisms of interactions requires identification of observable image features that can indicate the presence of information in multiple spatial and temporal scales of analog data. The AR methodology was originally developed to enhance pilot-training as well as `make believe' entertainment industries in a user-friendly digital environment We believe TMR-AR can someday help us conduct thought experiments scientifically, to be pedagogically visualized in a zoom-in-and-out, consistent, multi-scale approximations.

Changes after voice therapy in objective and subjective voice measurements of pediatric patients with vocal nodules.

PubMed

Tezcaner, Ciler Zahide; Karatayli Ozgursoy, Selmin; Ozgursoy, Selmin Karatayli; Sati, Isil; Dursun, Gursel

2009-12-01

The aim of this study was to analyze the efficiency of the voice therapy in children with vocal nodules by using the acoustic analysis and subjective assessment. Thirty-nine patients with vocal fold nodules, aged between 7 and 14, were included in the study. Each subject had voice therapy led by an experienced voice therapist once a week. All diagnostic and follow-up workouts were performed before the voice therapy and after the third or the sixth month. Transoral and/or transnasal videostroboscopic examination and acoustic analysis were achieved using multi-dimensional voice program (MDVP) and subjective analysis with GRBAS scale. As for the perceptual assessment, the difference was significant for four parameters out of five. A significant improvement was found in the acoustic analysis parameters of jitter, shimmer, and noise-to-harmonic ratio. The voice therapy which was planned according to patients' needs, age, compliance and response to therapy had positive effects on pediatric patients with vocal nodules. Acoustic analysis and GRBAS may be used successfully in the follow-up of pediatric vocal nodule treatment.

Surface quality of unsaturated polyester resin processed via continuous multi-shot rotational molding

NASA Astrophysics Data System (ADS)

Ogila, K. O.; Yang, W.; Shao, M.; Tan, J.

2017-05-01

Unsaturated Polyester Resin is a versatile and cost efficient thermosetting plastic whose application in rotational molding is currently limited by its relatively high initial viscosity and heat of reaction. These material characteristics result in uneven material distribution, poor surface finish and imperfections in the moldings especially when large wall thicknesses are required. The current work attempts to remedy these shortcomings through the development of a continuous multi-shot system which adds predetermined loads of unsaturated polyester resin into a rotating mold at various intervals. As part of this system, a laboratory-scale uniaxial rotational molding machine was used to produce Unsaturated Polyester Resin moldings in single and double shots. Optimal processing conditions were determined through visual studies, three dimensional microscopic studies, thickness distribution analysis and Fourier Transform Infrared spectroscopy. Volume filling fractions of 0.049-0.065, second shot volumes of 0.5-0.75 from the first shot, rotational speeds of 15-20 rpm and temperatures of 30-50 °C resulted in moldings of suitable quality on both the inner and outer surfaces.

Optimal control in microgrid using multi-agent reinforcement learning.

PubMed

Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

2012-11-01

This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Analysis of complex samples using a portable multi-wavelength light emitting diode (LED) fluorescence spectrometer

USDA-ARS?s Scientific Manuscript database

Spectroscopic analysis of chemically complex samples often requires an increase n the dimensionality of the measured response surface. This often involves the measurement of emitted light intensities as functions of both wavelengths of excitation and emission resulting in the generation of an excita...

Error control techniques for satellite and space communications

NASA Technical Reports Server (NTRS)

Costello, Daniel J., Jr.

1988-01-01

During the period December 1, 1987 through May 31, 1988, progress was made in the following areas: construction of Multi-Dimensional Bandwidth Efficient Trellis Codes with MPSK modulation; performance analysis of Bandwidth Efficient Trellis Coded Modulation schemes; and performance analysis of Bandwidth Efficient Trellis Codes on Fading Channels.

Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2014-12-01

Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images acquired in 2010. The comparison showed exceptional performance of our method. This method can be applied to emergency management and decision support systems with a need for real-time data, and it shows great potential for rapid data analysis in other areas, including volcano detection, flood boundaries, forest health, and wildfires.

Multi-Dimensional Voice Program (MDVP) vs Praat for Assessing Euphonic Subjects: A Preliminary Study on the Gender-discriminating Power of Acoustic Analysis Software.

PubMed

Lovato, Andrea; De Colle, Wladimiro; Giacomelli, Luciano; Piacente, Alessandro; Righetto, Lara; Marioni, Gino; de Filippis, Cosimo

2016-11-01

The aim of this study was to compare the discriminatory power of the Multi-Dimensional Voice Program (MDVP) and Praat in distinguishing the gender of euphonic adults. This is a cross-sectional study. The recordings of 100 euphonic volunteers (50 males and 50 females) producing a sustained vowel /a/ were analyzed with MDVP and Praat software. Both computer programs identified significant differences between male and female volunteers in absolute jitter (MDVP P < 0.00001 and Praat P < 0.00001) and in shimmer in decibel (dB) (MDVP P = 0.006 and Praat P = 0.001). Using the scale proposed by Hosmer and Lemeshow, we found no gender discrimination for shimmer in dB with either the MDVP (area under the receiver operating characteristics curve [AUC] = 0.658) or Praat (AUC = 0.682). In our series, on the other hand, MDVP absolute jitter achieved an acceptable discrimination between males and females (AUC = 0.752), and Praat absolute jitter achieved an outstanding discrimination (AUC = 0.901). The discriminatory power of Praat absolute jitter was significantly higher than that of the MDVP (P = 0.003). Absolute jitter sensitivity and specificity were also higher for Praat (83% and 80%) than for the MDVP (74% and 49%). Differences attributable to a subject's gender and to the software used to measure acoustic parameters should be carefully considered in both research and clinical settings. Further studies are needed to test the discriminatory power of different voice analysis programs when differentiating between normal and dysphonic voices. Copyright © 2016 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Reduced-Order Modeling: New Approaches for Computational Physics

NASA Technical Reports Server (NTRS)

Beran, Philip S.; Silva, Walter A.

2001-01-01

In this paper, we review the development of new reduced-order modeling techniques and discuss their applicability to various problems in computational physics. Emphasis is given to methods ba'sed on Volterra series representations and the proper orthogonal decomposition. Results are reported for different nonlinear systems to provide clear examples of the construction and use of reduced-order models, particularly in the multi-disciplinary field of computational aeroelasticity. Unsteady aerodynamic and aeroelastic behaviors of two- dimensional and three-dimensional geometries are described. Large increases in computational efficiency are obtained through the use of reduced-order models, thereby justifying the initial computational expense of constructing these models and inotivatim,- their use for multi-disciplinary design analysis.

How Much Do Adolescents Cybergossip? Scale Development and Validation in Spain and Colombia.

PubMed

Romera, Eva M; Herrera-López, Mauricio; Casas, José A; Ortega Ruiz, Rosario; Del Rey, Rosario

2018-01-01

Cybergossip is the act of two or more people making evaluative comments via digital devices about somebody who is not present. This cyberbehavior affects the social group in which it occurs and can either promote or hinder peer relationships. Scientific studies that assess the nature of this emerging and interactive behavior in the virtual world are limited. Some research on traditional gossip has identified it as an inherent and defining element of indirect relational aggression. This paper adopts and argues for a wider definition of gossip that includes positive comments and motivations. This work also suggests that cybergossip has to be measured independently from traditional gossip due to key differences when it occurs through ICT. This paper presents the Colombian and Spanish validation of the Cybergossip Questionnaire for Adolescents (CGQ-A), involving 3,747 high school students ( M = 13.98 years old, SD = 1.69; 48.5% male), of which 1,931 were Colombian and 1,816 were Spanish. Test models derived from item response theory, confirmatory factor analysis, content validation, and multi-group analysis were run on the full sample and subsamples for each country and both genders. The obtained optimal fit and psychometric properties confirm the robustness and suitability of a one-dimensional structure for the cybergossip instrument. The multi-group analysis shows that the cybergossip construct is understood similarly in both countries and between girls and boys. The composite reliability ratifies convergent and divergent validity of the scale. Descriptive results show that Colombian adolescents gossip less than their Spanish counterparts and that boys and girls use cybergossip to the same extent. As a conclusion, this study confirmes the relationship between cybergossip and cyberbullying, but it also supports a focus on positive cybergossip in psychoeducational interventions to build positive virtual relationships and prevent risky cyberbehaviors.

Quadrantal multi-scale distribution entropy analysis of heartbeat interval series based on a modified Poincaré plot

NASA Astrophysics Data System (ADS)

Huo, Chengyu; Huang, Xiaolin; Zhuang, Jianjun; Hou, Fengzhen; Ni, Huangjing; Ning, Xinbao

2013-09-01

The Poincaré plot is one of the most important approaches in human cardiac rhythm analysis. However, further investigations are still needed to concentrate on techniques that can characterize the dispersion of the points displayed by a Poincaré plot. Based on a modified Poincaré plot, we provide a novel measurement named distribution entropy (DE) and propose a quadrantal multi-scale distribution entropy analysis (QMDE) for the quantitative descriptions of the scatter distribution patterns in various regions and temporal scales. We apply this method to the heartbeat interval series derived from healthy subjects and congestive heart failure (CHF) sufferers, respectively, and find that the discriminations between them are most significant in the first quadrant, which implies significant impacts on vagal regulation brought about by CHF. We also investigate the day-night differences of young healthy people, and it is shown that the results present a clearly circadian rhythm, especially in the first quadrant. In addition, the multi-scale analysis indicates that the results of healthy subjects and CHF sufferers fluctuate in different trends with variation of the scale factor. The same phenomenon also appears in circadian rhythm investigations of young healthy subjects, which implies that the cardiac dynamic system is affected differently in various temporal scales by physiological or pathological factors.

Multi-mounted X-ray cone-beam computed tomography

NASA Astrophysics Data System (ADS)

Fu, Jian; Wang, Jingzheng; Guo, Wei; Peng, Peng

2018-04-01

As a powerful nondestructive inspection technique, X-ray computed tomography (X-CT) has been widely applied to clinical diagnosis, industrial production and cutting-edge research. Imaging efficiency is currently one of the major obstacles for the applications of X-CT. In this paper, a multi-mounted three dimensional cone-beam X-CT (MM-CBCT) method is reported. It consists of a novel multi-mounted cone-beam scanning geometry and the corresponding three dimensional statistical iterative reconstruction algorithm. The scanning geometry is the most iconic design and significantly different from the current CBCT systems. Permitting the cone-beam scanning of multiple objects simultaneously, the proposed approach has the potential to achieve an imaging efficiency orders of magnitude greater than the conventional methods. Although multiple objects can be also bundled together and scanned simultaneously by the conventional CBCT methods, it will lead to the increased penetration thickness and signal crosstalk. In contrast, MM-CBCT avoids substantially these problems. This work comprises a numerical study of the method and its experimental verification using a dataset measured with a developed MM-CBCT prototype system. This technique will provide a possible solution for the CT inspection in a large scale.

Multi-material 3D Models for Temporal Bone Surgical Simulation.

PubMed

Rose, Austin S; Kimbell, Julia S; Webster, Caroline E; Harrysson, Ola L A; Formeister, Eric J; Buchman, Craig A

2015-07-01

A simulated, multicolor, multi-material temporal bone model can be created using 3-dimensional (3D) printing that will prove both safe and beneficial in training for actual temporal bone surgical cases. As the process of additive manufacturing, or 3D printing, has become more practical and affordable, a number of applications for the technology in the field of Otolaryngology-Head and Neck Surgery have been considered. One area of promise is temporal bone surgical simulation. Three-dimensional representations of human temporal bones were created from temporal bone computed tomography (CT) scans using biomedical image processing software. Multi-material models were then printed and dissected in a temporal bone laboratory by attending and resident otolaryngologists. A 5-point Likert scale was used to grade the models for their anatomical accuracy and suitability as a simulation of cadaveric and operative temporal bone drilling. The models produced for this study demonstrate significant anatomic detail and a likeness to human cadaver specimens for drilling and dissection. Simulated temporal bones created by this process have potential benefit in surgical training, preoperative simulation for challenging otologic cases, and the standardized testing of temporal bone surgical skills. © The Author(s) 2015.

Turbulent scaling laws as solutions of the multi-point correlation equation using statistical symmetries

NASA Astrophysics Data System (ADS)

Oberlack, Martin; Rosteck, Andreas; Avsarkisov, Victor

2013-11-01

Text-book knowledge proclaims that Lie symmetries such as Galilean transformation lie at the heart of fluid dynamics. These important properties also carry over to the statistical description of turbulence, i.e. to the Reynolds stress transport equations and its generalization, the multi-point correlation equations (MPCE). Interesting enough, the MPCE admit a much larger set of symmetries, in fact infinite dimensional, subsequently named statistical symmetries. Most important, theses new symmetries have important consequences for our understanding of turbulent scaling laws. The symmetries form the essential foundation to construct exact solutions to the infinite set of MPCE, which in turn are identified as classical and new turbulent scaling laws. Examples on various classical and new shear flow scaling laws including higher order moments will be presented. Even new scaling have been forecasted from these symmetries and in turn validated by DNS. Turbulence modellers have implicitly recognized at least one of the statistical symmetries as this is the basis for the usual log-law which has been employed for calibrating essentially all engineering turbulence models. An obvious conclusion is to generally make turbulence models consistent with the new statistical symmetries.

Predictor Development and Pilot Testing of a Prototype Selection Instrument for Army Flight Training

DTIC Science & Technology

2007-02-01

called the Automated Pilot Examination System, or "APEX") during the preliminary validation reserach . The current version of the ASTB includes subtests...of objects in three-dimensional space . Aviation & Nautical Information: items assess an examinee’s familiarity with aviation history, nautical...proficiency. Aviation, Space and Environmental Medicine, 46, 309-311. Daryanian, B. (1980). Subjective scaling of mental workload in a multi-task environment

A Novel Multi-scale Simulation Strategy for Turbulent Reacting Flows

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

James, Sutherland C.

In this project, a new methodology was proposed to bridge the gap between Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES). This novel methodology, titled Lattice-Based Multiscale Simulation (LBMS), creates a lattice structure of One-Dimensional Turbulence (ODT) models. This model has been shown to capture turbulent combustion with high fidelity by fully resolving interactions between turbulence and diffusion. By creating a lattice of ODT models, which are then coupled, LBMS overcomes the shortcomings of ODT, which are its inability to capture large scale three dimensional flow structures. However, by spacing these lattices significantly apart, LBMS can avoid the cursemore » of dimensionality that creates untenable computational costs associated with DNS. This project has shown that LBMS is capable of reproducing statistics of isotropic turbulent flows while coarsening the spacing between lines significantly. It also investigates and resolves issues that arise when coupling ODT lines, such as flux reconstruction perpendicular to a given ODT line, preservation of conserved quantities when eddies cross a course cell volume and boundary condition application. Robust parallelization is also investigated.« less

Resonance phenomena in a time-dependent, three-dimensional model of an idealized eddy

NASA Astrophysics Data System (ADS)

Rypina, I. I.; Pratt, L. J.; Wang, P.; Äe; -zgökmen, T. M.; Mezic, I.

2015-08-01

We analyze the geometry of Lagrangian motion and material barriers in a time-dependent, three-dimensional, Ekman-driven, rotating cylinder flow, which serves as an idealization for an isolated oceanic eddy and other overturning cells with cylindrical geometry in the ocean and atmosphere. The flow is forced at the top through an oscillating upper lid, and the response depends on the frequency and amplitude of lid oscillations. In particular, the Lagrangian geometry changes near the resonant tori of the unforced flow, whose frequencies are rationally related to the forcing frequencies. Multi-scale analytical expansions are used to simplify the flow in the vicinity of resonant trajectories and to investigate the resonant flow geometries. The resonance condition and scaling can be motivated by simple physical argument. The theoretically predicted flow geometries near resonant trajectories have then been confirmed through numerical simulations in a phenomenological model and in a full solution of the Navier-Stokes equations.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

NASA Astrophysics Data System (ADS)

Tourret, D.; Karma, A.; Clarke, A. J.; Gibbs, P. J.; Imhoff, S. D.

2015-06-01

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulations and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.

Dissimilarity of yellow-blue surfaces under neutral light sources differing in intensity: separate contributions of light intensity and chroma.

PubMed

Tokunaga, Rumi; Logvinenko, Alexander D; Maloney, Laurence T

2008-01-01

Observers viewed two side-by-side arrays each of which contained three yellow Munsell papers, three blue, and one neutral Munsell. Each array was illuminated uniformly and independently of the other. The neutral light source intensities were 1380, 125, or 20 lux. All six possible combinations of light intensities were set as illumination conditions. On each trial, observers were asked to rate the dissimilarity between each chip in one array and each chip in the other by using a 30-point scale. Each pair of surfaces in each illumination condition was judged five times. We analyzed this data using non-metric multi-dimensional scaling to determine how light intensity and surface chroma contributed to dissimilarity and how they interacted. Dissimilarities were captured by a three-dimensional configuration in which one dimension corresponded to differences in light intensity.

Three-dimensional Dendritic Needle Network model with application to Al-Cu directional solidification experiments

DOE PAGES

Tourret, D.; Karma, A.; Clarke, A. J.; ...

2015-06-11

We present a three-dimensional (3D) extension of a previously proposed multi-scale Dendritic Needle Network (DNN) approach for the growth of complex dendritic microstructures. Using a new formulation of the DNN dynamics equations for dendritic paraboloid-branches of a given thickness, one can directly extend the DNN approach to 3D modeling. We validate this new formulation against known scaling laws and analytical solutions that describe the early transient and steady-state growth regimes, respectively. Finally, we compare the predictions of the model to in situ X-ray imaging of Al-Cu alloy solidification experiments. The comparison shows a very good quantitative agreement between 3D simulationsmore » and thin sample experiments. It also highlights the importance of full 3D modeling to accurately predict the primary dendrite arm spacing that is significantly over-estimated by 2D simulations.« less

SPHARA - A Generalized Spatial Fourier Analysis for Multi-Sensor Systems with Non-Uniformly Arranged Sensors: Application to EEG

PubMed Central

Graichen, Uwe; Eichardt, Roland; Fiedler, Patrique; Strohmeier, Daniel; Zanow, Frank; Haueisen, Jens

2015-01-01

Important requirements for the analysis of multichannel EEG data are efficient techniques for signal enhancement, signal decomposition, feature extraction, and dimensionality reduction. We propose a new approach for spatial harmonic analysis (SPHARA) that extends the classical spatial Fourier analysis to EEG sensors positioned non-uniformly on the surface of the head. The proposed method is based on the eigenanalysis of the discrete Laplace-Beltrami operator defined on a triangular mesh. We present several ways to discretize the continuous Laplace-Beltrami operator and compare the properties of the resulting basis functions computed using these discretization methods. We apply SPHARA to somatosensory evoked potential data from eleven volunteers and demonstrate the ability of the method for spatial data decomposition, dimensionality reduction and noise suppression. When employing SPHARA for dimensionality reduction, a significantly more compact representation can be achieved using the FEM approach, compared to the other discretization methods. Using FEM, to recover 95% and 99% of the total energy of the EEG data, on average only 35% and 58% of the coefficients are necessary. The capability of SPHARA for noise suppression is shown using artificial data. We conclude that SPHARA can be used for spatial harmonic analysis of multi-sensor data at arbitrary positions and can be utilized in a variety of other applications. PMID:25885290

Image matrix processor for fast multi-dimensional computations

DOEpatents

Roberson, G.P.; Skeate, M.F.

1996-10-15

An apparatus for multi-dimensional computation is disclosed which comprises a computation engine, including a plurality of processing modules. The processing modules are configured in parallel and compute respective contributions to a computed multi-dimensional image of respective two dimensional data sets. A high-speed, parallel access storage system is provided which stores the multi-dimensional data sets, and a switching circuit routes the data among the processing modules in the computation engine and the storage system. A data acquisition port receives the two dimensional data sets representing projections through an image, for reconstruction algorithms such as encountered in computerized tomography. The processing modules include a programmable local host, by which they may be configured to execute a plurality of different types of multi-dimensional algorithms. The processing modules thus include an image manipulation processor, which includes a source cache, a target cache, a coefficient table, and control software for executing image transformation routines using data in the source cache and the coefficient table and loading resulting data in the target cache. The local host processor operates to load the source cache with a two dimensional data set, loads the coefficient table, and transfers resulting data out of the target cache to the storage system, or to another destination. 10 figs.

SciSpark's SRDD : A Scientific Resilient Distributed Dataset for Multidimensional Data

NASA Astrophysics Data System (ADS)

Palamuttam, R. S.; Wilson, B. D.; Mogrovejo, R. M.; Whitehall, K. D.; Mattmann, C. A.; McGibbney, L. J.; Ramirez, P.

2015-12-01

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 have developed SciSpark, a robust Big Data framework, that extends ApacheTM Spark for scaling scientific computations. Apache Spark improves the map-reduce implementation in ApacheTM Hadoop for parallel computing on a cluster, by emphasizing in-memory computation, "spilling" to disk only as needed, and relying on lazy evaluation. Central to Spark is the Resilient Distributed Dataset (RDD), an in-memory distributed data structure that extends the functional paradigm provided by the Scala programming language. However, RDDs are ideal for tabular or unstructured data, and not for highly dimensional data. The SciSpark project introduces the Scientific Resilient Distributed Dataset (sRDD), a distributed-computing array structure which supports iterative scientific algorithms for multidimensional data. SciSpark processes data stored in NetCDF and HDF files by partitioning them across time or space and distributing the partitions among a cluster of compute nodes. We show usability and extensibility of SciSpark by implementing distributed algorithms for geospatial operations on large collections of multi-dimensional grids. In particular we address the problem of scaling an automated method for finding Mesoscale Convective Complexes. SciSpark provides a tensor interface to support the pluggability of different matrix libraries. We evaluate performance of the various matrix libraries in distributed pipelines, such as Nd4jTM and BreezeTM. We detail the architecture and design of SciSpark, our efforts to integrate climate science algorithms, parallel ingest and partitioning (sharding) of A-Train satellite observations from model grids. These solutions are encompassed in SciSpark, an open-source software framework for distributed computing on scientific data.

Maximizing the Biochemical Resolving Power of Fluorescence Microscopy

PubMed Central

Esposito, Alessandro; Popleteeva, Marina; Venkitaraman, Ashok R.

2013-01-01

Most recent advances in fluorescence microscopy have focused on achieving spatial resolutions below the diffraction limit. However, the inherent capability of fluorescence microscopy to non-invasively resolve different biochemical or physical environments in biological samples has not yet been formally described, because an adequate and general theoretical framework is lacking. Here, we develop a mathematical characterization of the biochemical resolution in fluorescence detection with Fisher information analysis. To improve the precision and the resolution of quantitative imaging methods, we demonstrate strategies for the optimization of fluorescence lifetime, fluorescence anisotropy and hyperspectral detection, as well as different multi-dimensional techniques. We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information in fluorescence detection. These strategies enable the optimal use of the information content available within the limited photon-budget typically available in fluorescence microscopy. This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can maximize the biochemical resolving power of fluorescence microscopy, an approach we term Hyper Dimensional Imaging Microscopy (HDIM). Our work provides a theoretical framework for the description of the biochemical resolution in fluorescence microscopy, irrespective of spatial resolution, and for the development of a new class of microscopes that exploit multi-parametric detection systems. PMID:24204821

Two-dimensional DFA scaling analysis applied to encrypted images

NASA Astrophysics Data System (ADS)

Vargas-Olmos, C.; Murguía, J. S.; Ramírez-Torres, M. T.; Mejía Carlos, M.; Rosu, H. C.; González-Aguilar, H.

2015-01-01

The technique of detrended fluctuation analysis (DFA) has been widely used to unveil scaling properties of many different signals. In this paper, we determine scaling properties in the encrypted images by means of a two-dimensional DFA approach. To carry out the image encryption, we use an enhanced cryptosystem based on a rule-90 cellular automaton and we compare the results obtained with its unmodified version and the encryption system AES. The numerical results show that the encrypted images present a persistent behavior which is close to that of the 1/f-noise. These results point to the possibility that the DFA scaling exponent can be used to measure the quality of the encrypted image content.

Three-dimensional multi-scale model of deformable platelets adhesion to vessel wall in blood flow

PubMed Central

Wu, Ziheng; Xu, Zhiliang; Kim, Oleg; Alber, Mark

2014-01-01

When a blood vessel ruptures or gets inflamed, the human body responds by rapidly forming a clot to restrict the loss of blood. Platelets aggregation at the injury site of the blood vessel occurring via platelet–platelet adhesion, tethering and rolling on the injured endothelium is a critical initial step in blood clot formation. A novel three-dimensional multi-scale model is introduced and used in this paper to simulate receptor-mediated adhesion of deformable platelets at the site of vascular injury under different shear rates of blood flow. The novelty of the model is based on a new approach of coupling submodels at three biological scales crucial for the early clot formation: novel hybrid cell membrane submodel to represent physiological elastic properties of a platelet, stochastic receptor–ligand binding submodel to describe cell adhesion kinetics and lattice Boltzmann submodel for simulating blood flow. The model implementation on the GPU cluster significantly improved simulation performance. Predictive model simulations revealed that platelet deformation, interactions between platelets in the vicinity of the vessel wall as well as the number of functional GPIbα platelet receptors played significant roles in platelet adhesion to the injury site. Variation of the number of functional GPIbα platelet receptors as well as changes of platelet stiffness can represent effects of specific drugs reducing or enhancing platelet activity. Therefore, predictive simulations can improve the search for new drug targets and help to make treatment of thrombosis patient-specific. PMID:24982253

Low-carbon building assessment and multi-scale input-output analysis

NASA Astrophysics Data System (ADS)

Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.

2011-01-01

Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.

Three-dimensional minority-carrier collection channels at shunt locations in silicon solar cells

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

Guthrey, Harvey; Johnston, Steve; Weiss, Dirk N.

2016-10-01

In this contribution, we demonstrate the value of using a multiscale multi-technique characterization approach to study the performance-limiting defects in multi-crystalline silicon (mc-Si) photovoltaic devices. The combination of dark lock-in thermography (DLIT) imaging, electron beam induced current imaging, and both transmission and scanning transmission electron microscopy (TEM/STEM) on the same location revealed the nanoscale origin of the optoelectronic properties of shunts visible at the device scale. Our site-specific correlative approach identified the shunt behavior to be a result of three-dimensional inversion channels around structural defects decorated with oxide precipitates. These inversion channels facilitate enhanced minority-carrier transport that results in themore » increased heating observed through DLIT imaging. The definitive connection between the nanoscale structure and chemistry of the type of shunt investigated here allows photovoltaic device manufacturers to immediately address the oxygen content of their mc-Si absorber material when such features are present, instead of engaging in costly characterization.« less

A synchrotron-based local computed tomography combined with data-constrained modelling approach for quantitative analysis of anthracite coal microstructure

PubMed Central

Chen, Wen Hao; Yang, Sam Y. S.; Xiao, Ti Qiao; Mayo, Sherry C.; Wang, Yu Dan; Wang, Hai Peng

2014-01-01

Quantifying three-dimensional spatial distributions of pores and material compositions in samples is a key materials characterization challenge, particularly in samples where compositions are distributed across a range of length scales, and where such compositions have similar X-ray absorption properties, such as in coal. Consequently, obtaining detailed information within sub-regions of a multi-length-scale sample by conventional approaches may not provide the resolution and level of detail one might desire. Herein, an approach for quantitative high-definition determination of material compositions from X-ray local computed tomography combined with a data-constrained modelling method is proposed. The approach is capable of dramatically improving the spatial resolution and enabling finer details within a region of interest of a sample larger than the field of view to be revealed than by using conventional techniques. A coal sample containing distributions of porosity and several mineral compositions is employed to demonstrate the approach. The optimal experimental parameters are pre-analyzed. The quantitative results demonstrated that the approach can reveal significantly finer details of compositional distributions in the sample region of interest. The elevated spatial resolution is crucial for coal-bed methane reservoir evaluation and understanding the transformation of the minerals during coal processing. The method is generic and can be applied for three-dimensional compositional characterization of other materials. PMID:24763649

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

Asymptotic modeling of transport phenomena at the interface between a fluid and a porous layer: Jump conditions

NASA Astrophysics Data System (ADS)

Angot, Philippe; Goyeau, Benoît; Ochoa-Tapia, J. Alberto

2017-06-01

We develop asymptotic modeling for two- or three-dimensional viscous fluid flow and convective transfer at the interface between a fluid and a porous layer. The asymptotic model is based on the fact that the thickness d of the interfacial transition region Ωfp of the one-domain representation is very small compared to the macroscopic length scale L . The analysis leads to an equivalent two-domain representation where transport phenomena in the transition layer of the one-domain approach are represented by algebraic jump boundary conditions at a fictive dividing interface Σ between the homogeneous fluid and porous regions. These jump conditions are thus stated up to first-order in O (d /L ) with d /L ≪1 . The originality and relevance of this asymptotic model lies in its general and multidimensional character. Indeed, it is shown that all the jump interface conditions derived for the commonly used 1D-shear flow are recovered by taking the tangential component of the asymptotic model. In that case, the comparison between the present model and the different models available in the literature gives explicit expressions of the effective jump coefficients and their associated scaling. In addition for multi-dimensional flows, the general asymptotic model yields the different components of the jump conditions including a new specific equation for the cross-flow pressure jump on Σ .

Asymptotic modeling of transport phenomena at the interface between a fluid and a porous layer: Jump conditions.

PubMed

Angot, Philippe; Goyeau, Benoît; Ochoa-Tapia, J Alberto

2017-06-01

We develop asymptotic modeling for two- or three-dimensional viscous fluid flow and convective transfer at the interface between a fluid and a porous layer. The asymptotic model is based on the fact that the thickness d of the interfacial transition region Ω_{fp} of the one-domain representation is very small compared to the macroscopic length scale L. The analysis leads to an equivalent two-domain representation where transport phenomena in the transition layer of the one-domain approach are represented by algebraic jump boundary conditions at a fictive dividing interface Σ between the homogeneous fluid and porous regions. These jump conditions are thus stated up to first-order in O(d/L) with d/L≪1. The originality and relevance of this asymptotic model lies in its general and multidimensional character. Indeed, it is shown that all the jump interface conditions derived for the commonly used 1D-shear flow are recovered by taking the tangential component of the asymptotic model. In that case, the comparison between the present model and the different models available in the literature gives explicit expressions of the effective jump coefficients and their associated scaling. In addition for multi-dimensional flows, the general asymptotic model yields the different components of the jump conditions including a new specific equation for the cross-flow pressure jump on Σ.

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara.

PubMed

Koo, Jawoo; Cox, Cindy M; Bacou, Melanie; Azzarri, Carlo; Guo, Zhe; Wood-Sichra, Ulrike; Gong, Queenie; You, Liangzhi

2016-01-01

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M-an open-access database of geospatial indicators at 5 arc-minute grid resolution-and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

A brain MRI bias field correction method created in the Gaussian multi-scale space

NASA Astrophysics Data System (ADS)

Chen, Mingsheng; Qin, Mingxin

2017-07-01

A pre-processing step is needed to correct for the bias field signal before submitting corrupted MR images to such image-processing algorithms. This study presents a new bias field correction method. The method creates a Gaussian multi-scale space by the convolution of the inhomogeneous MR image with a two-dimensional Gaussian function. In the multi-Gaussian space, the method retrieves the image details from the differentiation of the original image and convolution image. Then, it obtains an image whose inhomogeneity is eliminated by the weighted sum of image details in each layer in the space. Next, the bias field-corrected MR image is retrieved after the Υ correction, which enhances the contrast and brightness of the inhomogeneity-eliminated MR image. We have tested the approach on T1 MRI and T2 MRI with varying bias field levels and have achieved satisfactory results. Comparison experiments with popular software have demonstrated superior performance of the proposed method in terms of quantitative indices, especially an improvement in subsequent image segmentation.

Medical image classification based on multi-scale non-negative sparse coding.

PubMed

Zhang, Ruijie; Shen, Jian; Wei, Fushan; Li, Xiong; Sangaiah, Arun Kumar

2017-11-01

With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the semantic gap problem between low-level features and high-level image semantic, which will largely degrade the classification performance. To solve this problem, we propose a multi-scale non-negative sparse coding based medical image classification algorithm. Firstly, Medical images are decomposed into multiple scale layers, thus diverse visual details can be extracted from different scale layers. Secondly, for each scale layer, the non-negative sparse coding model with fisher discriminative analysis is constructed to obtain the discriminative sparse representation of medical images. Then, the obtained multi-scale non-negative sparse coding features are combined to form a multi-scale feature histogram as the final representation for a medical image. Finally, SVM classifier is combined to conduct medical image classification. The experimental results demonstrate that our proposed algorithm can effectively utilize multi-scale and contextual spatial information of medical images, reduce the semantic gap in a large degree and improve medical image classification performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-dimensional quantum state sharing based on quantum Fourier transform

NASA Astrophysics Data System (ADS)

Qin, Huawang; Tso, Raylin; Dai, Yuewei

2018-03-01

A scheme of multi-dimensional quantum state sharing is proposed. The dealer performs the quantum SUM gate and the quantum Fourier transform to encode a multi-dimensional quantum state into an entanglement state. Then the dealer distributes each participant a particle of the entanglement state, to share the quantum state among n participants. In the recovery, n-1 participants measure their particles and supply their measurement results; the last participant performs the unitary operation on his particle according to these measurement results and can reconstruct the initial quantum state. The proposed scheme has two merits: It can share the multi-dimensional quantum state and it does not need the entanglement measurement.

Cross-scale analysis of cluster correspondence using different operational neighborhoods

NASA Astrophysics Data System (ADS)

Lu, Yongmei; Thill, Jean-Claude

2008-09-01

Cluster correspondence analysis examines the spatial autocorrelation of multi-location events at the local scale. This paper argues that patterns of cluster correspondence are highly sensitive to the definition of operational neighborhoods that form the spatial units of analysis. A subset of multi-location events is examined for cluster correspondence if they are associated with the same operational neighborhood. This paper discusses the construction of operational neighborhoods for cluster correspondence analysis based on the spatial properties of the underlying zoning system and the scales at which the zones are aggregated into neighborhoods. Impacts of this construction on the degree of cluster correspondence are also analyzed. Empirical analyses of cluster correspondence between paired vehicle theft and recovery locations are conducted on different zoning methods and across a series of geographic scales and the dynamics of cluster correspondence patterns are discussed.

The detailed 3D multi-loop aggregate/rosette chromatin architecture and functional dynamic organization of the human and mouse genomes.

PubMed

Knoch, Tobias A; Wachsmuth, Malte; Kepper, Nick; Lesnussa, Michael; Abuseiris, Anis; Ali Imam, A M; Kolovos, Petros; Zuin, Jessica; Kockx, Christel E M; Brouwer, Rutger W W; van de Werken, Harmen J G; van IJcken, Wilfred F J; Wendt, Kerstin S; Grosveld, Frank G

2016-01-01

The dynamic three-dimensional chromatin architecture of genomes and its co-evolutionary connection to its function-the storage, expression, and replication of genetic information-is still one of the central issues in biology. Here, we describe the much debated 3D architecture of the human and mouse genomes from the nucleosomal to the megabase pair level by a novel approach combining selective high-throughput high-resolution chromosomal interaction capture ( T2C ), polymer simulations, and scaling analysis of the 3D architecture and the DNA sequence. The genome is compacted into a chromatin quasi-fibre with ~5 ± 1 nucleosomes/11 nm, folded into stable ~30-100 kbp loops forming stable loop aggregates/rosettes connected by similar sized linkers. Minor but significant variations in the architecture are seen between cell types and functional states. The architecture and the DNA sequence show very similar fine-structured multi-scaling behaviour confirming their co-evolution and the above. This architecture, its dynamics, and accessibility, balance stability and flexibility ensuring genome integrity and variation enabling gene expression/regulation by self-organization of (in)active units already in proximity. Our results agree with the heuristics of the field and allow "architectural sequencing" at a genome mechanics level to understand the inseparable systems genomic properties.

Multi-fluid CFD analysis in Process Engineering

NASA Astrophysics Data System (ADS)

Hjertager, B. H.

2017-12-01

An overview of modelling and simulation of flow processes in gas/particle and gas/liquid systems are presented. Particular emphasis is given to computational fluid dynamics (CFD) models that use the multi-dimensional multi-fluid techniques. Turbulence modelling strategies for gas/particle flows based on the kinetic theory for granular flows are given. Sub models for the interfacial transfer processes and chemical kinetics modelling are presented. Examples are shown for some gas/particle systems including flow and chemical reaction in risers as well as gas/liquid systems including bubble columns and stirred tanks.

Neural Categorization of Vibrotactile Frequency in Flutter and Vibration Stimulations: An fMRI Study.

PubMed

Kim, Junsuk; Chung, Yoon Gi; Chung, Soon-Cheol; Bulthoff, Heinrich H; Kim, Sung-Phil

2016-01-01

As the use of wearable haptic devices with vibrating alert features is commonplace, an understanding of the perceptual categorization of vibrotactile frequencies has become important. This understanding can be substantially enhanced by unveiling how neural activity represents vibrotactile frequency information. Using functional magnetic resonance imaging (fMRI), this study investigated categorical clustering patterns of the frequency-dependent neural activity evoked by vibrotactile stimuli with gradually changing frequencies from 20 to 200 Hz. First, a searchlight multi-voxel pattern analysis (MVPA) was used to find brain regions exhibiting neural activities associated with frequency information. We found that the contralateral postcentral gyrus (S1) and the supramarginal gyrus (SMG) carried frequency-dependent information. Next, we applied multidimensional scaling (MDS) to find low-dimensional neural representations of different frequencies obtained from the multi-voxel activity patterns within these regions. The clustering analysis on the MDS results showed that neural activity patterns of 20-100 Hz and 120-200 Hz were divided into two distinct groups. Interestingly, this neural grouping conformed to the perceptual frequency categories found in the previous behavioral studies. Our findings therefore suggest that neural activity patterns in the somatosensory cortical regions may provide a neural basis for the perceptual categorization of vibrotactile frequency.

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

NASA Astrophysics Data System (ADS)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

Comparing AMSR-E soil moisture estimates to the extended record of the U.S. Climate Reference Network (USCRN)

USDA-ARS?s Scientific Manuscript database

Soil moisture plays an integral role in various aspects ranging from multi-scale hydrologic modeling to agricultural decision analysis to multi-scale hydrologic modeling, from climate change assessments to drought prediction and prevention. The broad availability of soil moisture estimates has only...

Advancing Ecological Models to Compare Scale in Multi-Level Educational Change

ERIC Educational Resources Information Center

Woo, David James

2016-01-01

Education systems as units of analysis have been metaphorically likened to ecologies to model change. However, ecological models to date have been ineffective in modelling educational change that is multi-scale and occurs across multiple levels of an education system. Thus, this paper advances two innovative, ecological frameworks that improve on…

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

Integrative Exploratory Analysis of Two or More Genomic Datasets.

PubMed

Meng, Chen; Culhane, Aedin

2016-01-01

Exploratory analysis is an essential step in the analysis of high throughput data. Multivariate approaches such as correspondence analysis (CA), principal component analysis, and multidimensional scaling are widely used in the exploratory analysis of single dataset. Modern biological studies often assay multiple types of biological molecules (e.g., mRNA, protein, phosphoproteins) on a same set of biological samples, thereby creating multiple different types of omics data or multiassay data. Integrative exploratory analysis of these multiple omics data is required to leverage the potential of multiple omics studies. In this chapter, we describe the application of co-inertia analysis (CIA; for analyzing two datasets) and multiple co-inertia analysis (MCIA; for three or more datasets) to address this problem. These methods are powerful yet simple multivariate approaches that represent samples using a lower number of variables, allowing a more easily identification of the correlated structure in and between multiple high dimensional datasets. Graphical representations can be employed to this purpose. In addition, the methods simultaneously project samples and variables (genes, proteins) onto the same lower dimensional space, so the most variant variables from each dataset can be selected and associated with samples, which can be further used to facilitate biological interpretation and pathway analysis. We applied CIA to explore the concordance between mRNA and protein expression in a panel of 60 tumor cell lines from the National Cancer Institute. In the same 60 cell lines, we used MCIA to perform a cross-platform comparison of mRNA gene expression profiles obtained on four different microarray platforms. Last, as an example of integrative analysis of multiassay or multi-omics data we analyzed transcriptomic, proteomic, and phosphoproteomic data from pluripotent (iPS) and embryonic stem (ES) cell lines.

Intermediate scale plasma density irregularities in the polar ionosphere inferred from radio occultation

NASA Astrophysics Data System (ADS)

Shume, E. B.; Komjathy, A.; Langley, R. B.; Verkhoglyadova, O. P.; Butala, M.; Mannucci, A. J.

2014-12-01

In this research, we report intermediate scale plasma density irregularities in the high-latitude ionosphere inferred from high-resolution radio occultation (RO) measurements in the CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) - GPS (Global Positioning System) satellites radio link. The high inclination of the CASSIOPE satellite and high rate of signal receptionby the occultation antenna of the GPS Attitude, Positioning and Profiling (GAP) instrument on the Enhanced Polar Outflow Probe platform on CASSIOPE enable a high temporal and spatial resolution investigation of the dynamics of the polar ionosphere, magnetosphere-ionospherecoupling, solar wind effects, etc. with unprecedented details compared to that possible in the past. We have carried out high spatial resolution analysis in altitude and geomagnetic latitude of scintillation-producing plasma density irregularities in the polar ionosphere. Intermediate scale, scintillation-producing plasma density irregularities, which corresponds to 2 to 40 km spatial scales were inferred by applying multi-scale spectral analysis on the RO phase delay measurements. Using our multi-scale spectral analysis approach and Polar Operational Environmental Satellites (POES) and Defense Meteorological Satellite Program (DMSP) observations, we infer that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap regions. In specific terms, we found that large length scales and and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap region. Hence, the irregularity scales and phase scintillation characteristics are a function of the solar wind and the magnetospheric forcing. Multi-scale analysis may become a powerful diagnostic tool for characterizing how the ionosphere is dynamically driven by these factors.

A Unified Multi-scale Model for Cross-Scale Evaluation and Integration of Hydrological and Biogeochemical Processes

NASA Astrophysics Data System (ADS)

Liu, C.; Yang, X.; Bailey, V. L.; Bond-Lamberty, B. P.; Hinkle, C.

2013-12-01

Mathematical representations of hydrological and biogeochemical processes in soil, plant, aquatic, and atmospheric systems vary with scale. Process-rich models are typically used to describe hydrological and biogeochemical processes at the pore and small scales, while empirical, correlation approaches are often used at the watershed and regional scales. A major challenge for multi-scale modeling is that water flow, biogeochemical processes, and reactive transport are described using different physical laws and/or expressions at the different scales. For example, the flow is governed by the Navier-Stokes equations at the pore-scale in soils, by the Darcy law in soil columns and aquifer, and by the Navier-Stokes equations again in open water bodies (ponds, lake, river) and atmosphere surface layer. This research explores whether the physical laws at the different scales and in different physical domains can be unified to form a unified multi-scale model (UMSM) to systematically investigate the cross-scale, cross-domain behavior of fundamental processes at different scales. This presentation will discuss our research on the concept, mathematical equations, and numerical execution of the UMSM. Three-dimensional, multi-scale hydrological processes at the Disney Wilderness Preservation (DWP) site, Florida will be used as an example for demonstrating the application of the UMSM. In this research, the UMSM was used to simulate hydrological processes in rooting zones at the pore and small scales including water migration in soils under saturated and unsaturated conditions, root-induced hydrological redistribution, and role of rooting zone biogeochemical properties (e.g., root exudates and microbial mucilage) on water storage and wetting/draining. The small scale simulation results were used to estimate effective water retention properties in soil columns that were superimposed on the bulk soil water retention properties at the DWP site. The UMSM parameterized from smaller scale simulations were then used to simulate coupled flow and moisture migration in soils in saturated and unsaturated zones, surface and groundwater exchange, and surface water flow in streams and lakes at the DWP site under dynamic precipitation conditions. Laboratory measurements of soil hydrological and biogeochemical properties are used to parameterize the UMSM at the small scales, and field measurements are used to evaluate the UMSM.

Scales of variability of black carbon plumes and their dependence on resolution of ECHAM6-HAM

NASA Astrophysics Data System (ADS)

Weigum, Natalie; Stier, Philip; Schutgens, Nick; Kipling, Zak

2015-04-01

Prediction of the aerosol effect on climate depends on the ability of three-dimensional numerical models to accurately estimate aerosol properties. However, a limitation of traditional grid-based models is their inability to resolve variability on scales smaller than a grid box. Past research has shown that significant aerosol variability exists on scales smaller than these grid-boxes, which can lead to discrepancies between observations and aerosol models. The aim of this study is to understand how a global climate model's (GCM) inability to resolve sub-grid scale variability affects simulations of important aerosol features. This problem is addressed by comparing observed black carbon (BC) plume scales from the HIPPO aircraft campaign to those simulated by ECHAM-HAM GCM, and testing how model resolution affects these scales. This study additionally investigates how model resolution affects BC variability in remote and near-source regions. These issues are examined using three different approaches: comparison of observed and simulated along-flight-track plume scales, two-dimensional autocorrelation analysis, and 3-dimensional plume analysis. We find that the degree to which GCMs resolve variability can have a significant impact on the scales of BC plumes, and it is important for models to capture the scales of aerosol plume structures, which account for a large degree of aerosol variability. In this presentation, we will provide further results from the three analysis techniques along with a summary of the implication of these results on future aerosol model development.

A scale-based approach to interdisciplinary research and expertise in sports.

PubMed

Ibáñez-Gijón, Jorge; Buekers, Martinus; Morice, Antoine; Rao, Guillaume; Mascret, Nicolas; Laurin, Jérome; Montagne, Gilles

2017-02-01

After more than 20 years since the introduction of ecological and dynamical approaches in sports research, their promising opportunity for interdisciplinary research has not been fulfilled yet. The complexity of the research process and the theoretical and empirical difficulties associated with an integrated ecological-dynamical approach have been the major factors hindering the generalisation of interdisciplinary projects in sports sciences. To facilitate this generalisation, we integrate the major concepts from the ecological and dynamical approaches to study behaviour as a multi-scale process. Our integration gravitates around the distinction between functional (ecological) and execution (organic) scales, and their reciprocal intra- and inter-scale constraints. We propose an (epistemological) scale-based definition of constraints that accounts for the concept of synergies as emergent coordinative structures. To illustrate how we can operationalise the notion of multi-scale synergies we use an interdisciplinary model of locomotor pointing. To conclude, we show the value of this approach for interdisciplinary research in sport sciences, as we discuss two examples of task-specific dimensionality reduction techniques in the context of an ongoing project that aims to unveil the determinants of expertise in basketball free throw shooting. These techniques provide relevant empirical evidence to help bootstrap the challenging modelling efforts required in sport sciences.

Grid-Enabled Quantitative Analysis of Breast Cancer

DTIC Science & Technology

2009-10-01

large-scale, multi-modality computerized image analysis . The central hypothesis of this research is that large-scale image analysis for breast cancer...pilot study to utilize large scale parallel Grid computing to harness the nationwide cluster infrastructure for optimization of medical image ... analysis parameters. Additionally, we investigated the use of cutting edge dataanalysis/ mining techniques as applied to Ultrasound, FFDM, and DCE-MRI Breast

Based on a multi-agent system for multi-scale simulation and application of household's LUCC: a case study for Mengcha village, Mizhi county, Shaanxi province.

PubMed

Chen, Hai; Liang, Xiaoying; Li, Rui

2013-01-01

Multi-Agent Systems (MAS) offer a conceptual approach to include multi-actor decision making into models of land use change. Through the simulation based on the MAS, this paper tries to show the application of MAS in the micro scale LUCC, and reveal the transformation mechanism of difference scale. This paper starts with a description of the context of MAS research. Then, it adopts the Nested Spatial Choice (NSC) method to construct the multi-scale LUCC decision-making model. And a case study for Mengcha village, Mizhi County, Shaanxi Province is reported. Finally, the potentials and drawbacks of the following approach is discussed and concluded. From our design and implementation of the MAS in multi-scale model, a number of observations and conclusions can be drawn on the implementation and future research directions. (1) The use of the LUCC decision-making and multi-scale transformation framework provides, according to us, a more realistic modeling of multi-scale decision making process. (2) By using continuous function, rather than discrete function, to construct the decision-making of the households is more realistic to reflect the effect. (3) In this paper, attempts have been made to give a quantitative analysis to research the household interaction. And it provides the premise and foundation for researching the communication and learning among the households. (4) The scale transformation architecture constructed in this paper helps to accumulate theory and experience for the interaction research between the micro land use decision-making and the macro land use landscape pattern. Our future research work will focus on: (1) how to rational use risk aversion principle, and put the rule on rotation between household parcels into model. (2) Exploring the methods aiming at researching the household decision-making over a long period, it allows us to find the bridge between the long-term LUCC data and the short-term household decision-making. (3) Researching the quantitative method and model, especially the scenario analysis model which may reflect the interaction among different household types.

Developing an African youth psychosocial assessment: an application of item response theory.

PubMed

Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

2014-06-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

Developing an African youth psychosocial assessment: an application of item response theory

PubMed Central

BETANCOURT, THERESA S.; YANG, FRANCES; BOLTON, PAUL; NORMAND, SHARON-LISE

2014-01-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. PMID:24478113

Synthesis of Joint Volumes, Visualization of Paths, and Revision of Viewing Sequences in a Multi-dimensional Seismic Data Viewer

NASA Astrophysics Data System (ADS)

Chen, D. M.; Clapp, R. G.; Biondi, B.

2006-12-01

Ricksep is a freely-available interactive viewer for multi-dimensional data sets. The viewer is very useful for simultaneous display of multiple data sets from different viewing angles, animation of movement along a path through the data space, and selection of local regions for data processing and information extraction. Several new viewing features are added to enhance the program's functionality in the following three aspects. First, two new data synthesis algorithms are created to adaptively combine information from a data set with mostly high-frequency content, such as seismic data, and another data set with mainly low-frequency content, such as velocity data. Using the algorithms, these two data sets can be synthesized into a single data set which resembles the high-frequency data set on a local scale and at the same time resembles the low- frequency data set on a larger scale. As a result, the originally separated high and low-frequency details can now be more accurately and conveniently studied together. Second, a projection algorithm is developed to display paths through the data space. Paths are geophysically important because they represent wells into the ground. Two difficulties often associated with tracking paths are that they normally cannot be seen clearly inside multi-dimensional spaces and depth information is lost along the direction of projection when ordinary projection techniques are used. The new algorithm projects samples along the path in three orthogonal directions and effectively restores important depth information by using variable projection parameters which are functions of the distance away from the path. Multiple paths in the data space can be generated using different character symbols as positional markers, and users can easily create, modify, and view paths in real time. Third, a viewing history list is implemented which enables Ricksep's users to create, edit and save a recipe for the sequence of viewing states. Then, the recipe can be loaded into an active Ricksep session, after which the user can navigate to any state in the sequence and modify the sequence from that state. Typical uses of this feature are undoing and redoing viewing commands and animating a sequence of viewing states. The theoretical discussion are carried out and several examples using real seismic data are provided to show how these new Ricksep features provide more convenient, accurate ways to manipulate multi-dimensional data sets.

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

Rabiti, Cristian; Alfonsi, Andrea; Huang, Dongli

This report collect the effort performed to improve the reliability analysis capabilities of the RAVEN code and explore new opportunity in the usage of surrogate model by extending the current RAVEN capabilities to multi physics surrogate models and construction of surrogate models for high dimensionality fields.

Dimensionality of the Rosenberg Self-Esteem Scale and its relationships with the Three-and the Five-factor personality models.

PubMed

Aluja, Anton; Rolland, Jean-Pierre; García, Luis F; Rossier, Jérôme

2007-04-01

We investigated the dimensionality of the French version of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1965) using confirmatory factor analysis. We tested models of 1 or 2 factors. Results suggest the RSES is a 1-dimensional scale with 3 highly correlated items. Comparison with the Revised NEO-Personality Inventory (NEO-PI-R; Costa, McCrae, & Rolland, 1998) demonstrated that Neuroticism correlated strongly and Extraversion and Conscientiousness moderately with the RSES. Depression accounted for 47% of the variance of the RSES. Other NEO-PI-R facets were also moderately related with self-esteem.

Robust scalable stabilisability conditions for large-scale heterogeneous multi-agent systems with uncertain nonlinear interactions: towards a distributed computing architecture

NASA Astrophysics Data System (ADS)

Manfredi, Sabato

2016-06-01

Large-scale dynamic systems are becoming highly pervasive in their occurrence with applications ranging from system biology, environment monitoring, sensor networks, and power systems. They are characterised by high dimensionality, complexity, and uncertainty in the node dynamic/interactions that require more and more computational demanding methods for their analysis and control design, as well as the network size and node system/interaction complexity increase. Therefore, it is a challenging problem to find scalable computational method for distributed control design of large-scale networks. In this paper, we investigate the robust distributed stabilisation problem of large-scale nonlinear multi-agent systems (briefly MASs) composed of non-identical (heterogeneous) linear dynamical systems coupled by uncertain nonlinear time-varying interconnections. By employing Lyapunov stability theory and linear matrix inequality (LMI) technique, new conditions are given for the distributed control design of large-scale MASs that can be easily solved by the toolbox of MATLAB. The stabilisability of each node dynamic is a sufficient assumption to design a global stabilising distributed control. The proposed approach improves some of the existing LMI-based results on MAS by both overcoming their computational limits and extending the applicative scenario to large-scale nonlinear heterogeneous MASs. Additionally, the proposed LMI conditions are further reduced in terms of computational requirement in the case of weakly heterogeneous MASs, which is a common scenario in real application where the network nodes and links are affected by parameter uncertainties. One of the main advantages of the proposed approach is to allow to move from a centralised towards a distributed computing architecture so that the expensive computation workload spent to solve LMIs may be shared among processors located at the networked nodes, thus increasing the scalability of the approach than the network size. Finally, a numerical example shows the applicability of the proposed method and its advantage in terms of computational complexity when compared with the existing approaches.

[Dimensional structure of the Brazilian version of the Scale of Satisfaction with Interpersonal Processes of General Medical Care].

PubMed

Nascimento, Maria Isabel do; Reichenheim, Michael Eduardo; Monteiro, Gina Torres Rego

2011-12-01

The objective of this study was to reassess the dimensional structure of a Brazilian version of the Scale of Satisfaction with Interpersonal Processes of General Medical Care, proposed originally as a one-dimensional instrument. Strict confirmatory factor analysis (CFA) and exploratory factor analysis modeled within a CFA framework (E/CFA) were used to identify the best model. An initial CFA rejected the one-dimensional structure, while an E/CFA suggested a two-dimensional structure. The latter structure was followed by a new CFA, which showed that the model without cross-loading was the most parsimonious, with adequate fit indices (CFI = 0.982 and TLI = 0.988), except for RMSEA (0.062). Although the model achieved convergent validity, discriminant validity was questionable, with the square-root of the mean variance extracted from dimension 1 estimates falling below the respective factor correlation. According to these results, there is not sufficient evidence to recommend the immediate use of the instrument, and further studies are needed for a more in-depth analysis of the postulated structures.

Nonlinear Conservation Laws and Finite Volume Methods

NASA Astrophysics Data System (ADS)

Leveque, Randall J.

Introduction Software Notation Classification of Differential Equations Derivation of Conservation Laws The Euler Equations of Gas Dynamics Dissipative Fluxes Source Terms Radiative Transfer and Isothermal Equations Multi-dimensional Conservation Laws The Shock Tube Problem Mathematical Theory of Hyperbolic Systems Scalar Equations Linear Hyperbolic Systems Nonlinear Systems The Riemann Problem for the Euler Equations Numerical Methods in One Dimension Finite Difference Theory Finite Volume Methods Importance of Conservation Form - Incorrect Shock Speeds Numerical Flux Functions Godunov's Method Approximate Riemann Solvers High-Resolution Methods Other Approaches Boundary Conditions Source Terms and Fractional Steps Unsplit Methods Fractional Step Methods General Formulation of Fractional Step Methods Stiff Source Terms Quasi-stationary Flow and Gravity Multi-dimensional Problems Dimensional Splitting Multi-dimensional Finite Volume Methods Grids and Adaptive Refinement Computational Difficulties Low-Density Flows Discrete Shocks and Viscous Profiles Start-Up Errors Wall Heating Slow-Moving Shocks Grid Orientation Effects Grid-Aligned Shocks Magnetohydrodynamics The MHD Equations One-Dimensional MHD Solving the Riemann Problem Nonstrict Hyperbolicity Stiffness The Divergence of B Riemann Problems in Multi-dimensional MHD Staggered Grids The 8-Wave Riemann Solver Relativistic Hydrodynamics Conservation Laws in Spacetime The Continuity Equation The 4-Momentum of a Particle The Stress-Energy Tensor Finite Volume Methods Multi-dimensional Relativistic Flow Gravitation and General Relativity References

3-D optical profilometry at micron scale with multi-frequency fringe projection using modified fibre optic Lloyd's mirror technique

NASA Astrophysics Data System (ADS)

Inanç, Arda; Kösoğlu, Gülşen; Yüksel, Heba; Naci Inci, Mehmet

2018-06-01

A new fibre optic Lloyd's mirror method is developed for extracting 3-D height distribution of various objects at the micron scale with a resolution of 4 μm. The fibre optic assembly is elegantly integrated to an optical microscope and a CCD camera. It is demonstrated that the proposed technique is quite suitable and practical to produce an interference pattern with an adjustable frequency. By increasing the distance between the fibre and the mirror with a micrometre stage in the Lloyd's mirror assembly, the separation between the two bright fringes is lowered down to the micron scale without using any additional elements as part of the optical projection unit. A fibre optic cable, whose polymer jacket is partially stripped, and a microfluidic channel are used as test objects to extract their surface topographies. Point by point sensitivity of the method is found to be around 8 μm, changing a couple of microns depending on the fringe frequency and the measured height. A straightforward calibration procedure for the phase to height conversion is also introduced by making use of the vertical moving stage of the optical microscope. The phase analysis of the acquired image is carried out by One Dimensional Continuous Wavelet Transform for which the chosen wavelet is the Morlet wavelet and the carrier removal of the projected fringe patterns is achieved by reference subtraction. Furthermore, flexible multi-frequency property of the proposed method allows measuring discontinuous heights where there are phase ambiguities like 2π by lowering the fringe frequency and eliminating the phase ambiguity.

Next-Generation MDAC Discrimination Procedure Using Multi-Dimensional Spectral Analyses

DTIC Science & Technology

2007-09-01

explosions near the Lop Nor, Novaya Zemlya, Semipalatinsk , Nevada, and Indian test sites . We have computed regional phase spectra and are correcting... test sites as mainly due to differences in explosion P and S corner frequencies. Fisk (2007) used source model fits to estimate Pn, Pg, and Lg corner...frequencies for Nevada Test Site (NTS) explosions and found that Lg corner frequencies exhibit similar scaling with source size as for Pn and Pg

3-Dimensional Nano-Scale Reinforcement Architecture for Advanced Composite Structures

DTIC Science & Technology

2008-10-01

textile structures on 3TEX equipment. Conduct experimental studies of the spinnability of Multi-Wall Carbon Nanotube ( MWCNT ) forests and...adjacent inner wall when MWNT length is one centimeter (Fig. 1.8). Complete stress transfer to all walls by going to longer nanotube lengths could...between regular IK T300 carbon yarn and 25-ply carbon nanotube yarn. Fig. 5.8 shows the nanotube yarns going through the heddles during weaving with

Predicting human immunodeficiency virus inhibitors using multi-dimensional Bayesian network classifiers.

PubMed

Borchani, Hanen; Bielza, Concha; Toro, Carlos; Larrañaga, Pedro

2013-03-01

Our aim is to use multi-dimensional Bayesian network classifiers in order to predict the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors given an input set of respective resistance mutations that an HIV patient carries. Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models especially designed to solve multi-dimensional classification problems, where each input instance in the data set has to be assigned simultaneously to multiple output class variables that are not necessarily binary. In this paper, we introduce a new method, named MB-MBC, for learning MBCs from data by determining the Markov blanket around each class variable using the HITON algorithm. Our method is applied to both reverse transcriptase and protease data sets obtained from the Stanford HIV-1 database. Regarding the prediction of antiretroviral combination therapies, the experimental study shows promising results in terms of classification accuracy compared with state-of-the-art MBC learning algorithms. For reverse transcriptase inhibitors, we get 71% and 11% in mean and global accuracy, respectively; while for protease inhibitors, we get more than 84% and 31% in mean and global accuracy, respectively. In addition, the analysis of MBC graphical structures lets us gain insight into both known and novel interactions between reverse transcriptase and protease inhibitors and their respective resistance mutations. MB-MBC algorithm is a valuable tool to analyze the HIV-1 reverse transcriptase and protease inhibitors prediction problem and to discover interactions within and between these two classes of inhibitors. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-dimensional PIC-simulations of parametric instabilities for shock-ignition conditions

NASA Astrophysics Data System (ADS)

Riconda, C.; Weber, S.; Klimo, O.; Héron, A.; Tikhonchuk, V. T.

2013-11-01

Laser-plasma interaction is investigated for conditions relevant for the shock-ignition (SI) scheme of inertial confinement fusion using two-dimensional particle-in-cell (PIC) simulations of an intense laser beam propagating in a hot, large-scale, non-uniform plasma. The temporal evolution and interdependence of Raman- (SRS), and Brillouin- (SBS), side/backscattering as well as Two-Plasmon-Decay (TPD) are studied. TPD is developing in concomitance with SRS creating a broad spectrum of plasma waves near the quarter-critical density. They are rapidly saturated due to plasma cavitation within a few picoseconds. The hot electron spectrum created by SRS and TPD is relatively soft, limited to energies below one hundred keV.

Model Reduction of Computational Aerothermodynamics for Multi-Discipline Analysis in High Speed Flows

NASA Astrophysics Data System (ADS)

Crowell, Andrew Rippetoe

This dissertation describes model reduction techniques for the computation of aerodynamic heat flux and pressure loads for multi-disciplinary analysis of hypersonic vehicles. NASA and the Department of Defense have expressed renewed interest in the development of responsive, reusable hypersonic cruise vehicles capable of sustained high-speed flight and access to space. However, an extensive set of technical challenges have obstructed the development of such vehicles. These technical challenges are partially due to both the inability to accurately test scaled vehicles in wind tunnels and to the time intensive nature of high-fidelity computational modeling, particularly for the fluid using Computational Fluid Dynamics (CFD). The aim of this dissertation is to develop efficient and accurate models for the aerodynamic heat flux and pressure loads to replace the need for computationally expensive, high-fidelity CFD during coupled analysis. Furthermore, aerodynamic heating and pressure loads are systematically evaluated for a number of different operating conditions, including: simple two-dimensional flow over flat surfaces up to three-dimensional flows over deformed surfaces with shock-shock interaction and shock-boundary layer interaction. An additional focus of this dissertation is on the implementation and computation of results using the developed aerodynamic heating and pressure models in complex fluid-thermal-structural simulations. Model reduction is achieved using a two-pronged approach. One prong focuses on developing analytical corrections to isothermal, steady-state CFD flow solutions in order to capture flow effects associated with transient spatially-varying surface temperatures and surface pressures (e.g., surface deformation, surface vibration, shock impingements, etc.). The second prong is focused on minimizing the computational expense of computing the steady-state CFD solutions by developing an efficient surrogate CFD model. The developed two-pronged approach is found to exhibit balanced performance in terms of accuracy and computational expense, relative to several existing approaches. This approach enables CFD-based loads to be implemented into long duration fluid-thermal-structural simulations.

Development and validation of the Bullying and Cyberbullying Scale for Adolescents: A multi-dimensional measurement model.

PubMed

Thomas, Hannah J; Scott, James G; Coates, Jason M; Connor, Jason P

2018-05-03

Intervention on adolescent bullying is reliant on valid and reliable measurement of victimization and perpetration experiences across different behavioural expressions. This study developed and validated a survey tool that integrates measurement of both traditional and cyber bullying to test a theoretically driven multi-dimensional model. Adolescents from 10 mainstream secondary schools completed a baseline and follow-up survey (N = 1,217; M age  = 14 years; 66.2% male). The Bullying and cyberbullying Scale for Adolescents (BCS-A) developed for this study comprised parallel victimization and perpetration subscales, each with 20 items. Additional measures of bullying (Olweus Global Bullying and the Forms of Bullying Scale [FBS]), as well as measures of internalizing and externalizing problems, school connectedness, social support, and personality, were used to further assess validity. Factor structure was determined, and then, the suitability of items was assessed according to the following criteria: (1) factor interpretability, (2) item correlations, (3) model parsimony, and (4) measurement equivalence across victimization and perpetration experiences. The final models comprised four factors: physical, verbal, relational, and cyber. The final scale was revised to two 13-item subscales. The BCS-A demonstrated acceptable concurrent and convergent validity (internalizing and externalizing problems, school connectedness, social support, and personality), as well as predictive validity over 6 months. The BCS-A has sound psychometric properties. This tool establishes measurement equivalence across types of involvement and behavioural forms common among adolescents. An improved measurement method could add greater rigour to the evaluation of intervention programmes and also enable interventions to be tailored to subscale profiles. © 2018 The British Psychological Society.

Evaluation of Two Crew Module Boilerplate Tests Using Newly Developed Calibration Metrics

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.

2012-01-01

The paper discusses a application of multi-dimensional calibration metrics to evaluate pressure data from water drop tests of the Max Launch Abort System (MLAS) crew module boilerplate. Specifically, three metrics are discussed: 1) a metric to assess the probability of enveloping the measured data with the model, 2) a multi-dimensional orthogonality metric to assess model adequacy between test and analysis, and 3) a prediction error metric to conduct sensor placement to minimize pressure prediction errors. Data from similar (nearly repeated) capsule drop tests shows significant variability in the measured pressure responses. When compared to expected variability using model predictions, it is demonstrated that the measured variability cannot be explained by the model under the current uncertainty assumptions.

Rasch Analysis of the Geriatric Depression Scale--Short Form

ERIC Educational Resources Information Center

Chiang, Karl S.; Green, Kathy E.; Cox, Enid O.

2009-01-01

Purpose: The purpose of this study was to examine scale dimensionality, reliability, invariance, targeting, continuity, cutoff scores, and diagnostic use of the Geriatric Depression Scale-Short Form (GDS-SF) over time with a sample of 177 English-speaking U.S. elders. Design and Methods: An item response theory, Rasch analysis, was conducted with…

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109

Thermofluid Analysis of Magnetocaloric Refrigeration

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

Abdelaziz, Omar; Gluesenkamp, Kyle R; Vineyard, Edward Allan

While there have been extensive studies on thermofluid characteristics of different magnetocaloric refrigeration systems, a conclusive optimization study using non-dimensional parameters which can be applied to a generic system has not been reported yet. In this study, a numerical model has been developed for optimization of active magnetic refrigerator (AMR). This model is computationally efficient and robust, making it appropriate for running the thousands of simulations required for parametric study and optimization. The governing equations have been non-dimensionalized and numerically solved using finite difference method. A parametric study on a wide range of non-dimensional numbers has been performed. While themore » goal of AMR systems is to improve the performance of competitive parameters including COP, cooling capacity and temperature span, new parameters called AMR performance index-1 have been introduced in order to perform multi objective optimization and simultaneously exploit all these parameters. The multi-objective optimization is carried out for a wide range of the non-dimensional parameters. The results of this study will provide general guidelines for designing high performance AMR systems.« less

Performance analysis of three-dimensional-triple-level cell and two-dimensional-multi-level cell NAND flash hybrid solid-state drives

NASA Astrophysics Data System (ADS)

Sakaki, Yukiya; Yamada, Tomoaki; Matsui, Chihiro; Yamaga, Yusuke; Takeuchi, Ken

2018-04-01

In order to improve performance of solid-state drives (SSDs), hybrid SSDs have been proposed. Hybrid SSDs consist of more than two types of NAND flash memories or NAND flash memories and storage-class memories (SCMs). However, the cost of hybrid SSDs adopting SCMs is more expensive than that of NAND flash only SSDs because of the high bit cost of SCMs. This paper proposes unique hybrid SSDs with two-dimensional (2D) horizontal multi-level cell (MLC)/three-dimensional (3D) vertical triple-level cell (TLC) NAND flash memories to achieve higher cost-performance. The 2D-MLC/3D-TLC hybrid SSD achieves up to 31% higher performance than the conventional 2D-MLC/2D-TLC hybrid SSD. The factors of different performance between the proposed hybrid SSD and the conventional hybrid SSD are analyzed by changing its block size, read/write/erase latencies, and write unit of 3D-TLC NAND flash memory, by means of a transaction-level modeling simulator.

A Review of Structure Construction of Silk Fibroin Biomaterials from Single Structures to Multi-Level Structures.

PubMed

Qi, Yu; Wang, Hui; Wei, Kai; Yang, Ya; Zheng, Ru-Yue; Kim, Ick Soo; Zhang, Ke-Qin

2017-03-03

The biological performance of artificial biomaterials is closely related to their structure characteristics. Cell adhesion, migration, proliferation, and differentiation are all strongly affected by the different scale structures of biomaterials. Silk fibroin (SF), extracted mainly from silkworms, has become a popular biomaterial due to its excellent biocompatibility, exceptional mechanical properties, tunable degradation, ease of processing, and sufficient supply. As a material with excellent processability, SF can be processed into various forms with different structures, including particulate, fiber, film, and three-dimensional (3D) porous scaffolds. This review discusses and summarizes the various constructions of SF-based materials, from single structures to multi-level structures, and their applications. In combination with single structures, new techniques for creating special multi-level structures of SF-based materials, such as micropatterning and 3D-printing, are also briefly addressed.

A non-linear optimization programming model for air quality planning including co-benefits for GHG emissions.

PubMed

Turrini, Enrico; Carnevale, Claudio; Finzi, Giovanna; Volta, Marialuisa

2018-04-15

This paper introduces the MAQ (Multi-dimensional Air Quality) model aimed at defining cost-effective air quality plans at different scales (urban to national) and assessing the co-benefits for GHG emissions. The model implements and solves a non-linear multi-objective, multi-pollutant decision problem where the decision variables are the application levels of emission abatement measures allowing the reduction of energy consumption, end-of pipe technologies and fuel switch options. The objectives of the decision problem are the minimization of tropospheric secondary pollution exposure and of internal costs. The model assesses CO 2 equivalent emissions in order to support decision makers in the selection of win-win policies. The methodology is tested on Lombardy region, a heavily polluted area in northern Italy. Copyright © 2017 Elsevier B.V. All rights reserved.

Examining the relationships between resources and online health information seeking among patients with chronic diseases and healthy people.

PubMed

Oh, Young Sam; Cho, Youngmin

2015-01-01

The Internet is increasingly used as an important source of health and medical-related information for people with chronic diseases. It is recognized that online health information seeking (OHIS) is influenced by individuals' multi-dimensional factors, such as demographics, socio-economic factors, perceptions of the Internet, and health conditions. This study applies the conservation of resource theory to examine relationships between various multi-dimensional factors, daily challenges, and OHIS depending on individuals' health conditions. The data used in this study was taken from the U.S. Health Tracking Survey (2012). In this study, Internet users aged 18 and older were classified into patients (N = 518) and healthy people (N = 677) based on their health status related to chronic diseases. Multiple regression analysis was used to examine the relationships between multi-dimensional factors (resources), self-rated health, and OHIS. Patients' various resources (e.g., age, income, education, having a smartphone, and health tracking) significantly predicted their self-rated health and OHIS; in addition, self-rated health significantly mediated the relationships between focal resources and OHIS. However, the mediating effects of self-rated health were not found in healthy people.

Self-organizing neural networks--an alternative way of cluster analysis in clinical chemistry.

PubMed

Reibnegger, G; Wachter, H

1996-04-15

Supervised learning schemes have been employed by several workers for training neural networks designed to solve clinical problems. We demonstrate that unsupervised techniques can also produce interesting and meaningful results. Using a data set on the chemical composition of milk from 22 different mammals, we demonstrate that self-organizing feature maps (Kohonen networks) as well as a modified version of error backpropagation technique yield results mimicking conventional cluster analysis. Both techniques are able to project a potentially multi-dimensional input vector onto a two-dimensional space whereby neighborhood relationships remain conserved. Thus, these techniques can be used for reducing dimensionality of complicated data sets and for enhancing comprehensibility of features hidden in the data matrix.

Maintaining Moore's law: enabling cost-friendly dimensional scaling

NASA Astrophysics Data System (ADS)

Mallik, Arindam; Ryckaert, Julien; Mercha, Abdelkarim; Verkest, Diederik; Ronse, Kurt; Thean, Aaron

2015-03-01

Moore's Law (Moore's Observation) has been driving the progress in semiconductor technology for the past 50 years. The semiconductor industry is at a juncture where significant increase in manufacturing cost is foreseen to sustain the past trend of dimensional scaling. At N10 and N7 technology nodes, the industry is struggling to find a cost-friendly solution. At a device level, technologists have come up with novel devices (finFET, Gate-All-Around), material innovations (SiGe, Ge) to boost performance and reduce power consumption. On the other hand, from the patterning side, the relative slow ramp-up of alternative lithography technologies like EUVL and DSA pushes the industry to adopt a severely multi-patterning-based solution. Both of these technological transformations have a big impact on die yield and eventually die cost. This paper is aimed to analyze the impact on manufacturing cost to keep the Moore's law alive. We have proposed and analyzed various patterning schemes that can enable cost-friendly scaling. We evaluated the impact of EUVL introduction on tackling the high cost of manufacturing. The primary objective of this paper is to maintain Moore's scaling from a patterning perspective and analyzing EUV lithography introduction at a die level.

Massively Scalable Near Duplicate Detection in Streams of Documents using MDSH

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

Bogen, Paul Logasa; Symons, Christopher T; McKenzie, Amber T

2013-01-01

In a world where large-scale text collections are not only becoming ubiquitous but also are growing at increasing rates, near duplicate documents are becoming a growing concern that has the potential to hinder many different information filtering tasks. While others have tried to address this problem, prior techniques have only been used on limited collection sizes and static cases. We will briefly describe the problem in the context of Open Source Intelligence (OSINT) along with our additional constraints for performance. In this work we propose two variations on Multi-dimensional Spectral Hash (MDSH) tailored for working on extremely large, growing setsmore » of text documents. We analyze the memory and runtime characteristics of our techniques and provide an informal analysis of the quality of the near-duplicate clusters produced by our techniques.« less

Impact of scale on morphological spatial pattern of forest

Treesearch

Katarzyna Ostapowicz; Peter Vogt; Kurt H. Riitters; Jacek Kozak; Christine Estreguil

2008-01-01

Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns...

Validity and reliability of Turkish Caregiver Burden Scale among family caregivers of haemodialysis patients.

PubMed

Cil Akinci, Ayse; Pinar, Rukiye

2014-02-01

To investigate the validity and reliability of the Caregiver Burden Scale in family members who provide primary care for haemodialysis patients. In Turkey, there is a need for a multi-dimensional instrument to evaluate the caregiver burden in people who provide care for patients with chronic diseases. A methodological study. The study sample consisted of 161 family members who provide primary care for haemodialysis patients. The forward-backward translation method was used to develop the Turkish Caregiver Burden Scale. The reliability was based on internal consistency investigated by Cronbach's alpha and item-total correlation. The factorial construct validity of the scale was tested with confirmatory factor analysis. By means of convergent and divergent validity, correlation between Caregiver Burden Scale and 36-Item Short Form Health Survey (SF-36) and correlation between Caregiver Burden Scale and the Maslach Burnout Scale were investigated. Cronbach's alpha and item-total correlations results suggested that there was good internal reliability. We found five underlying factors similar to original Scale's five-factor solution. The confirmatory factor analysis five-factor model represented an acceptable fit. Factor loadings were significant, with standardised loadings ranging from 0·43-0·81. By means of divergent validity, all sub-dimension scores and the total score of the Caregiver Burden Scale were negatively correlated with the SF-36, whereas there was a positive correlation with the emotional exhaustion and depersonalisation subscales of the Maslach Burnout Scale as expected. These results suggest that the Caregiver Burden Scale is a reliable and valid instrument which can be used with confidence in Turkish caregivers for haemodialysis patients to screen caregiver burden. The burden experienced by people who provide care for patients with chronic diseases can be evaluated with the Caregiver Burden Scale. Additionally, the Caregiver Burden Scale can be used in the evaluation of the effectiveness of attempts to decrease caregiver burden. © 2012 Blackwell Publishing Ltd.

Multi-petascale highly efficient parallel supercomputer

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

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Using Synchrotron Radiation Microtomography to Investigate Multi-scale Three-dimensional Microelectronic Packages.

PubMed

Carlton, Holly D; Elmer, John W; Li, Yan; Pacheco, Mario; Goyal, Deepak; Parkinson, Dilworth Y; MacDowell, Alastair A

2016-04-13

Synchrotron radiation micro-tomography (SRµT) is a non-destructive three-dimensional (3D) imaging technique that offers high flux for fast data acquisition times with high spatial resolution. In the electronics industry there is serious interest in performing failure analysis on 3D microelectronic packages, many which contain multiple levels of high-density interconnections. Often in tomography there is a trade-off between image resolution and the volume of a sample that can be imaged. This inverse relationship limits the usefulness of conventional computed tomography (CT) systems since a microelectronic package is often large in cross sectional area 100-3,600 mm(2), but has important features on the micron scale. The micro-tomography beamline at the Advanced Light Source (ALS), in Berkeley, CA USA, has a setup which is adaptable and can be tailored to a sample's properties, i.e., density, thickness, etc., with a maximum allowable cross-section of 36 x 36 mm. This setup also has the option of being either monochromatic in the energy range ~7-43 keV or operating with maximum flux in white light mode using a polychromatic beam. Presented here are details of the experimental steps taken to image an entire 16 x 16 mm system within a package, in order to obtain 3D images of the system with a spatial resolution of 8.7 µm all within a scan time of less than 3 min. Also shown are results from packages scanned in different orientations and a sectioned package for higher resolution imaging. In contrast a conventional CT system would take hours to record data with potentially poorer resolution. Indeed, the ratio of field-of-view to throughput time is much higher when using the synchrotron radiation tomography setup. The description below of the experimental setup can be implemented and adapted for use with many other multi-materials.

An adaptive least-squares global sensitivity method and application to a plasma-coupled combustion prediction with parametric correlation

NASA Astrophysics Data System (ADS)

Tang, Kunkun; Massa, Luca; Wang, Jonathan; Freund, Jonathan B.

2018-05-01

We introduce an efficient non-intrusive surrogate-based methodology for global sensitivity analysis and uncertainty quantification. Modified covariance-based sensitivity indices (mCov-SI) are defined for outputs that reflect correlated effects. The overall approach is applied to simulations of a complex plasma-coupled combustion system with disparate uncertain parameters in sub-models for chemical kinetics and a laser-induced breakdown ignition seed. The surrogate is based on an Analysis of Variance (ANOVA) expansion, such as widely used in statistics, with orthogonal polynomials representing the ANOVA subspaces and a polynomial dimensional decomposition (PDD) representing its multi-dimensional components. The coefficients of the PDD expansion are obtained using a least-squares regression, which both avoids the direct computation of high-dimensional integrals and affords an attractive flexibility in choosing sampling points. This facilitates importance sampling using a Bayesian calibrated posterior distribution, which is fast and thus particularly advantageous in common practical cases, such as our large-scale demonstration, for which the asymptotic convergence properties of polynomial expansions cannot be realized due to computation expense. Effort, instead, is focused on efficient finite-resolution sampling. Standard covariance-based sensitivity indices (Cov-SI) are employed to account for correlation of the uncertain parameters. Magnitude of Cov-SI is unfortunately unbounded, which can produce extremely large indices that limit their utility. Alternatively, mCov-SI are then proposed in order to bound this magnitude ∈ [ 0 , 1 ]. The polynomial expansion is coupled with an adaptive ANOVA strategy to provide an accurate surrogate as the union of several low-dimensional spaces, avoiding the typical computational cost of a high-dimensional expansion. It is also adaptively simplified according to the relative contribution of the different polynomials to the total variance. The approach is demonstrated for a laser-induced turbulent combustion simulation model, which includes parameters with correlated effects.

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

DOE PAGES

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

2018-01-01

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Multi-Dimensional Signal Processing Research Program

DTIC Science & Technology

1981-09-30

applications to real-time image processing and analysis. A specific long-range application is the automated processing of aerial reconnaissance imagery...Non-supervised image segmentation is a potentially im- portant operation in the automated processing of aerial reconnaissance pho- tographs since it

Rapid acquisition of data dense solid-state CPMG NMR spectral sets using multi-dimensional statistical analysis

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

Mason, H. E.; Uribe, E. C.; Shusterman, J. A.

Tensor-rank decomposition methods have been applied to variable contact time 29 Si{ 1 H} CP/CPMG NMR data sets to extract NMR dynamics information and dramatically decrease conventional NMR acquisition times.

Meta-modelling, visualization and emulation of multi-dimensional data for virtual production intelligence

NASA Astrophysics Data System (ADS)

Schulz, Wolfgang; Hermanns, Torsten; Al Khawli, Toufik

2017-07-01

Decision making for competitive production in high-wage countries is a daily challenge where rational and irrational methods are used. The design of decision making processes is an intriguing, discipline spanning science. However, there are gaps in understanding the impact of the known mathematical and procedural methods on the usage of rational choice theory. Following Benjamin Franklin's rule for decision making formulated in London 1772, he called "Prudential Algebra" with the meaning of prudential reasons, one of the major ingredients of Meta-Modelling can be identified finally leading to one algebraic value labelling the results (criteria settings) of alternative decisions (parameter settings). This work describes the advances in Meta-Modelling techniques applied to multi-dimensional and multi-criterial optimization by identifying the persistence level of the corresponding Morse-Smale Complex. Implementations for laser cutting and laser drilling are presented, including the generation of fast and frugal Meta-Models with controlled error based on mathematical model reduction Reduced Models are derived to avoid any unnecessary complexity. Both, model reduction and analysis of multi-dimensional parameter space are used to enable interactive communication between Discovery Finders and Invention Makers. Emulators and visualizations of a metamodel are introduced as components of Virtual Production Intelligence making applicable the methods of Scientific Design Thinking and getting the developer as well as the operator more skilled.

Advances and Challenges In Uncertainty Quantification with Application to Climate Prediction, ICF design and Science Stockpile Stewardship

NASA Astrophysics Data System (ADS)

Klein, R.; Woodward, C. S.; Johannesson, G.; Domyancic, D.; Covey, C. C.; Lucas, D. D.

2012-12-01

Uncertainty Quantification (UQ) is a critical field within 21st century simulation science that resides at the very center of the web of emerging predictive capabilities. The science of UQ holds the promise of giving much greater meaning to the results of complex large-scale simulations, allowing for quantifying and bounding uncertainties. This powerful capability will yield new insights into scientific predictions (e.g. Climate) of great impact on both national and international arenas, allow informed decisions on the design of critical experiments (e.g. ICF capsule design, MFE, NE) in many scientific fields, and assign confidence bounds to scientifically predictable outcomes (e.g. nuclear weapons design). In this talk I will discuss a major new strategic initiative (SI) we have developed at Lawrence Livermore National Laboratory to advance the science of Uncertainty Quantification at LLNL focusing in particular on (a) the research and development of new algorithms and methodologies of UQ as applied to multi-physics multi-scale codes, (b) incorporation of these advancements into a global UQ Pipeline (i.e. a computational superstructure) that will simplify user access to sophisticated tools for UQ studies as well as act as a self-guided, self-adapting UQ engine for UQ studies on extreme computing platforms and (c) use laboratory applications as a test bed for new algorithms and methodologies. The initial SI focus has been on applications for the quantification of uncertainty associated with Climate prediction, but the validated UQ methodologies we have developed are now being fed back into Science Based Stockpile Stewardship (SSS) and ICF UQ efforts. To make advancements in several of these UQ grand challenges, I will focus in talk on the following three research areas in our Strategic Initiative: Error Estimation in multi-physics and multi-scale codes ; Tackling the "Curse of High Dimensionality"; and development of an advanced UQ Computational Pipeline to enable complete UQ workflow and analysis for ensemble runs at the extreme scale (e.g. exascale) with self-guiding adaptation in the UQ Pipeline engine. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

Understanding Prairie Fen Hydrology - a Hierarchical Multi-Scale Groundwater Modeling Approach

NASA Astrophysics Data System (ADS)

Sampath, P.; Liao, H.; Abbas, H.; Ma, L.; Li, S.

2012-12-01

Prairie fens provide critical habitat to more than 50 rare species and significantly contribute to the biodiversity of the upper Great Lakes region. The sustainability of these globally unique ecosystems, however, requires that they be fed by a steady supply of pristine, calcareous groundwater. Understanding the hydrology that supports the existence of such fens is essential in preserving these valuable habitats. This research uses process-based multi-scale groundwater modeling for this purpose. Two fen-sites, MacCready Fen and Ives Road Fen, in Southern Michigan were systematically studied. A hierarchy of nested steady-state models was built for each fen-site to capture the system's dynamics at spatial scales ranging from the regional groundwater-shed to the local fens. The models utilize high-resolution Digital Elevation Models (DEM), National Hydrologic Datasets (NHD), a recently-assembled water-well database, and results from a state-wide groundwater mapping project to represent the complex hydro-geological and stress framework. The modeling system simulates both shallow glacial and deep bedrock aquifers as well as the interaction between surface water and groundwater. Aquifer heterogeneities were explicitly simulated with multi-scale transition probability geo-statistics. A two-way hydraulic head feedback mechanism was set up between the nested models, such that the parent models provided boundary conditions to the child models, and in turn the child models provided local information to the parent models. A hierarchical mass budget analysis was performed to estimate the seepage fluxes at the surface water/groundwater interfaces and to assess the relative importance of the processes at multiple scales that contribute water to the fens. The models were calibrated using observed base-flows at stream gauging stations and/or static water levels at wells. Three-dimensional particle tracking was used to predict the sources of water to the fens. We observed from the multi-scale simulations that the water system that supports the fens is a much larger, more connected, and more complex one than expected. The water in the fen can be traced back to a network of sources, including lakes and wetlands at different elevations, which are connected to a regional mound through a "cascade delivery mechanism". This "master recharge area" is the ultimate source of water not only to the fens in its vicinity, but also for many major rivers and aquifers. The implication of this finding is that prairie fens must be managed as part of a much larger, multi-scale groundwater system and we must consider protection of the shorter and long-term water sources. This will require a fundamental reassessment of our current approach to fen conservation, which is primarily based on protection of individual fens and their immediate surroundings. Clearly, in the future we must plan for conservation of the broad recharge areas and the multiple fen complexes they support.

Streamflow hindcasting in European river basins via multi-parametric ensemble of the mesoscale hydrologic model (mHM)

NASA Astrophysics Data System (ADS)

Noh, Seong Jin; Rakovec, Oldrich; Kumar, Rohini; Samaniego, Luis

2016-04-01

There have been tremendous improvements in distributed hydrologic modeling (DHM) which made a process-based simulation with a high spatiotemporal resolution applicable on a large spatial scale. Despite of increasing information on heterogeneous property of a catchment, DHM is still subject to uncertainties inherently coming from model structure, parameters and input forcing. Sequential data assimilation (DA) may facilitate improved streamflow prediction via DHM using real-time observations to correct internal model states. In conventional DA methods such as state updating, parametric uncertainty is, however, often ignored mainly due to practical limitations of methodology to specify modeling uncertainty with limited ensemble members. If parametric uncertainty related with routing and runoff components is not incorporated properly, predictive uncertainty by DHM may be insufficient to capture dynamics of observations, which may deteriorate predictability. Recently, a multi-scale parameter regionalization (MPR) method was proposed to make hydrologic predictions at different scales using a same set of model parameters without losing much of the model performance. The MPR method incorporated within the mesoscale hydrologic model (mHM, http://www.ufz.de/mhm) could effectively represent and control uncertainty of high-dimensional parameters in a distributed model using global parameters. In this study, we present a global multi-parametric ensemble approach to incorporate parametric uncertainty of DHM in DA to improve streamflow predictions. To effectively represent and control uncertainty of high-dimensional parameters with limited number of ensemble, MPR method is incorporated with DA. Lagged particle filtering is utilized to consider the response times and non-Gaussian characteristics of internal hydrologic processes. The hindcasting experiments are implemented to evaluate impacts of the proposed DA method on streamflow predictions in multiple European river basins having different climate and catchment characteristics. Because augmentation of parameters is not required within an assimilation window, the approach could be stable with limited ensemble members and viable for practical uses.

Implementation of a Multi-Robot Coverage Algorithm on a Two-Dimensional, Grid-Based Environment

DTIC Science & Technology

2017-06-01

two planar laser range finders with a 180-degree field of view , color camera, vision beacons, and wireless communicator. In their system, the robots...Master’s thesis 4. TITLE AND SUBTITLE IMPLEMENTATION OF A MULTI -ROBOT COVERAGE ALGORITHM ON A TWO -DIMENSIONAL, GRID-BASED ENVIRONMENT 5. FUNDING NUMBERS...path planning coverage algorithm for a multi -robot system in a two -dimensional, grid-based environment. We assess the applicability of a topology

Multi-Subband Ensemble Monte Carlo simulations of scaled GAA MOSFETs

NASA Astrophysics Data System (ADS)

Donetti, L.; Sampedro, C.; Ruiz, F. G.; Godoy, A.; Gamiz, F.

2018-05-01

We developed a Multi-Subband Ensemble Monte Carlo simulator for non-planar devices, taking into account two-dimensional quantum confinement. It couples self-consistently the solution of the 3D Poisson equation, the 2D Schrödinger equation, and the 1D Boltzmann transport equation with the Ensemble Monte Carlo method. This simulator was employed to study MOS devices based on ultra-scaled Gate-All-Around Si nanowires with diameters in the range from 4 nm to 8 nm with gate length from 8 nm to 14 nm. We studied the output and transfer characteristics, interpreting the behavior in the sub-threshold region and in the ON state in terms of the spatial charge distribution and the mobility computed with the same simulator. We analyzed the results, highlighting the contribution of different valleys and subbands and the effect of the gate bias on the energy and velocity profiles. Finally the scaling behavior was studied, showing that only the devices with D = 4nm maintain a good control of the short channel effects down to the gate length of 8nm .

Laser Scanning Holographic Lithography for Flexible 3D Fabrication of Multi-Scale Integrated Nano-structures and Optical Biosensors

PubMed Central

Yuan, Liang (Leon); Herman, Peter R.

2016-01-01

Three-dimensional (3D) periodic nanostructures underpin a promising research direction on the frontiers of nanoscience and technology to generate advanced materials for exploiting novel photonic crystal (PC) and nanofluidic functionalities. However, formation of uniform and defect-free 3D periodic structures over large areas that can further integrate into multifunctional devices has remained a major challenge. Here, we introduce a laser scanning holographic method for 3D exposure in thick photoresist that combines the unique advantages of large area 3D holographic interference lithography (HIL) with the flexible patterning of laser direct writing to form both micro- and nano-structures in a single exposure step. Phase mask interference patterns accumulated over multiple overlapping scans are shown to stitch seamlessly and form uniform 3D nanostructure with beam size scaled to small 200 μm diameter. In this way, laser scanning is presented as a facile means to embed 3D PC structure within microfluidic channels for integration into an optofluidic lab-on-chip, demonstrating a new laser HIL writing approach for creating multi-scale integrated microsystems. PMID:26922872

Mode-based equivalent multi-degree-of-freedom system for one-dimensional viscoelastic response analysis of layered soil deposit

NASA Astrophysics Data System (ADS)

Li, Chong; Yuan, Juyun; Yu, Haitao; Yuan, Yong

2018-01-01

Discrete models such as the lumped parameter model and the finite element model are widely used in the solution of soil amplification of earthquakes. However, neither of the models will accurately estimate the natural frequencies of soil deposit, nor simulate a damping of frequency independence. This research develops a new discrete model for one-dimensional viscoelastic response analysis of layered soil deposit based on the mode equivalence method. The new discrete model is a one-dimensional equivalent multi-degree-of-freedom (MDOF) system characterized by a series of concentrated masses, springs and dashpots with a special configuration. The dynamic response of the equivalent MDOF system is analytically derived and the physical parameters are formulated in terms of modal properties. The equivalent MDOF system is verified through a comparison of amplification functions with the available theoretical solutions. The appropriate number of degrees of freedom (DOFs) in the equivalent MDOF system is estimated. A comparative study of the equivalent MDOF system with the existing discrete models is performed. It is shown that the proposed equivalent MDOF system can exactly present the natural frequencies and the hysteretic damping of soil deposits and provide more accurate results with fewer DOFs.

Scaling analysis for the direct reactor auxiliary cooling system for FHRs

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

Lv, Q.; Kim, I. H.; Sun, X.

2015-04-01

The Direct Reactor Auxiliary Cooling System (DRACS) is a passive residual heat removal system proposed for the Fluoride-salt-cooled High-temperature Reactor (FHR) that combines the coated particle fuel and graphite moderator with a liquid fluoride salt as the coolant. The DRACS features three natural circulation/convection loops that rely on buoyancy as the driving force and are coupled via two heat exchangers, namely, the DRACS heat exchanger and the natural draft heat exchanger. A fluidic diode is employed to minimize the parasitic flow into the DRACS primary loop and correspondingly the heat loss to the DRACS during reactor normal operation, and tomore » activate the DRACS in accidents when the reactor is shut down. While the DRACS concept has been proposed, there are no actual prototypic DRACS systems for FHRs built or tested in the literature. In this paper, a detailed scaling analysis for the DRACS is performed, which will provide guidance for the design of scaled-down DRACS test facilities. Based on the Boussinesq assumption and one-dimensional flow formulation, the governing equations are non-dimensionalized by introducing appropriate dimensionless parameters. The key dimensionless numbers that characterize the DRACS system are obtained from the non-dimensional governing equations. Based on the dimensionless numbers and non-dimensional governing equations, similarity laws are proposed. In addition, a scaling methodology has been developed, which consists of a core scaling and a loop scaling. The consistency between the core and loop scaling is examined via the reference volume ratio, which can be obtained from both the core and loop scaling processes. The scaling methodology and similarity laws have been applied to obtain a scientific design of a scaled-down high-temperature DRACS test facility.« less

Morphological Properties of Siloxane-Hydrogel Contact Lens Surfaces.

PubMed

Stach, Sebastian; Ţălu, Ştefan; Trabattoni, Silvia; Tavazzi, Silvia; Głuchaczka, Alicja; Siek, Patrycja; Zając, Joanna; Giovanzana, Stefano

2017-04-01

The aim of this study was to quantitatively characterize the micromorphology of contact lens (CL) surfaces using atomic force microscopy (AFM) and multifractal analysis. AFM and multifractal analysis were used to characterize the topography of new and worn siloxane-hydrogel CLs made of Filcon V (I FDA group). CL surface roughness was studied by AFM in intermittent-contact mode, in air, on square areas of 25 and 100 μm 2 , by using a Nanoscope V MultiMode (Bruker). Detailed surface characterization of the surface topography was obtained using statistical parameters of 3-D (three-dimensional) surface roughness, in accordance with ISO 25178-2: 2012. Before wear, the surface was found to be characterized by out-of-plane and sharp structures, whilst after a wear of 8 h, two typical morphologies were observed. One morphology (sharp type) has a similar aspect as the unworn CLs and the other morphology (smooth type) is characterized by troughs and bumpy structures. The analysis of the AFM images revealed a multifractal geometry. The generalized dimension D q and the singularity spectrum f(α) provided quantitative values that characterize the local scale properties of CL surface geometry at nanometer scale. Surface statistical parameters deduced by multifractal analysis can be used to assess the CL micromorphology and can be used by manufacturers in developing CLs with improved surface characteristics. These parameters can also be used in understanding the tribological interactions of the back surface of the CL with the corneal surface and the front surface of the CL with the under-surface of the eyelid (friction, wear, and micro-elastohydrodynamic lubrication at a nanometer scale).

A novel framework for change detection in bi-temporal polarimetric SAR images

NASA Astrophysics Data System (ADS)

Pirrone, Davide; Bovolo, Francesca; Bruzzone, Lorenzo

2016-10-01

Last years have seen relevant increase of polarimetric Synthetic Aperture Radar (SAR) data availability, thanks to satellite sensors like Sentinel-1 or ALOS-2 PALSAR-2. The augmented information lying in the additional polarimetric channels represents a possibility for better discriminate different classes of changes in change detection (CD) applications. This work aims at proposing a framework for CD in multi-temporal multi-polarization SAR data. The framework includes both a tool for an effective visual representation of the change information and a method for extracting the multiple-change information. Both components are designed to effectively handle the multi-dimensionality of polarimetric data. In the novel representation, multi-temporal intensity SAR data are employed to compute a polarimetric log-ratio. The multitemporal information of the polarimetric log-ratio image is represented in a multi-dimensional features space, where changes are highlighted in terms of magnitude and direction. This representation is employed to design a novel unsupervised multi-class CD approach. This approach considers a sequential two-step analysis of the magnitude and the direction information for separating non-changed and changed samples. The proposed approach has been validated on a pair of Sentinel-1 data acquired before and after the flood in Tamil-Nadu in 2015. Preliminary results demonstrate that the representation tool is effective and that the use of polarimetric SAR data is promising in multi-class change detection applications.

Numerical simulation of machining distortions on a forged aerospace component following a one and a multi-step approaches

NASA Astrophysics Data System (ADS)

Prete, Antonio Del; Franchi, Rodolfo; Antermite, Fabrizio; Donatiello, Iolanda

2018-05-01

Residual stresses appear in a component as a consequence of thermo-mechanical processes (e.g. ring rolling process) casting and heat treatments. When machining these kinds of components, distortions arise due to the redistribution of residual stresses due to the foregoing process history inside the material. If distortions are excessive, they can lead to a large number of scrap parts. Since dimensional accuracy can affect directly the engines efficiency, the dimensional control for aerospace components is a non-trivial issue. In this paper, the problem related to the distortions of large thin walled aeroengines components in nickel superalloys has been addressed. In order to estimate distortions on inner diameters after internal turning operations, a 3D Finite Element Method (FEM) analysis has been developed on a real industrial test case. All the process history, has been taken into account by developing FEM models of ring rolling process and heat treatments. Three different strategies of ring rolling process have been studied and the combination of related parameters which allows to obtain the best dimensional accuracy has been found. Furthermore, grain size evolution and recrystallization phenomena during manufacturing process has been numerically investigated using a semi empirical Johnson-Mehl-Avrami-Kohnogorov (JMAK) model. The volume subtractions have been simulated by boolean trimming: a one step and a multi step analysis have been performed. The multi-step procedure has allowed to choose the best material removal sequence in order to reduce machining distortions.

Multi-scale characterization of the energy landscape of proteins with application to the C3D/Efb-C complex.

PubMed

Haspel, Nurit; Geisbrecht, Brian V; Lambris, John; Kavraki, Lydia

2010-03-01

We present a novel multi-level methodology to explore and characterize the low energy landscape and the thermodynamics of proteins. Traditional conformational search methods typically explore only a small portion of the conformational space of proteins and are hard to apply to large proteins due to the large amount of calculations required. In our multi-scale approach, we first provide an initial characterization of the equilibrium state ensemble of a protein using an efficient computational conformational sampling method. We then enrich the obtained ensemble by performing short Molecular Dynamics (MD) simulations on selected conformations from the ensembles as starting points. To facilitate the analysis of the results, we project the resulting conformations on a low-dimensional landscape to efficiently focus on important interactions and examine low energy regions. This methodology provides a more extensive sampling of the low energy landscape than an MD simulation starting from a single crystal structure as it explores multiple trajectories of the protein. This enables us to obtain a broader view of the dynamics of proteins and it can help in understanding complex binding, improving docking results and more. In this work, we apply the methodology to provide an extensive characterization of the bound complexes of the C3d fragment of human Complement component C3 and one of its powerful bacterial inhibitors, the inhibitory domain of Staphylococcus aureus extra-cellular fibrinogen-binding domain (Efb-C) and two of its mutants. We characterize several important interactions along the binding interface and define low free energy regions in the three complexes. Proteins 2010. (c) 2009 Wiley-Liss, Inc.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

Multi-Dimensional Simulation of LWR Fuel Behavior in the BISON Fuel Performance Code

NASA Astrophysics Data System (ADS)

Williamson, R. L.; Capps, N. A.; Liu, W.; Rashid, Y. R.; Wirth, B. D.

2016-11-01

Nuclear fuel operates in an extreme environment that induces complex multiphysics phenomena occurring over distances ranging from inter-atomic spacing to meters, and times scales ranging from microseconds to years. To simulate this behavior requires a wide variety of material models that are often complex and nonlinear. The recently developed BISON code represents a powerful fuel performance simulation tool based on its material and physical behavior capabilities, finite-element versatility of spatial representation, and use of parallel computing. The code can operate in full three dimensional (3D) mode, as well as in reduced two dimensional (2D) modes, e.g., axisymmetric radial-axial ( R- Z) or plane radial-circumferential ( R- θ), to suit the application and to allow treatment of global and local effects. A BISON case study was used to illustrate analysis of Pellet Clad Mechanical Interaction failures from manufacturing defects using combined 2D and 3D analyses. The analysis involved commercial fuel rods and demonstrated successful computation of metrics of interest to fuel failures, including cladding peak hoop stress and strain energy density. In comparison with a failure threshold derived from power ramp tests, results corroborate industry analyses of the root cause of the pellet-clad interaction failures and illustrate the importance of modeling 3D local effects around fuel pellet defects, which can produce complex effects including cold spots in the cladding, stress concentrations, and hot spots in the fuel that can lead to enhanced cladding degradation such as hydriding, oxidation, CRUD formation, and stress corrosion cracking.

Multi-Dimensional Simulation of LWR Fuel Behavior in the BISON Fuel Performance Code

DOE PAGES

Williamson, R. L.; Capps, N. A.; Liu, W.; ...

2016-09-27

Nuclear fuel operates in an extreme environment that induces complex multiphysics phenomena occurring over distances ranging from inter-atomic spacing to meters, and times scales ranging from microseconds to years. To simulate this behavior requires a wide variety of material models that are often complex and nonlinear. The recently developed BISON code represents a powerful fuel performance simulation tool based on its material and physical behavior capabilities, finite-element versatility of spatial representation, and use of parallel computing. The code can operate in full three dimensional (3D) mode, as well as in reduced two dimensional (2D) modes, e.g., axisymmetric radial-axial (R-Z) ormore » plane radial-circumferential (R-θ), to suit the application and to allow treatment of global and local effects. A BISON case study was used in this paper to illustrate analysis of Pellet Clad Mechanical Interaction failures from manufacturing defects using combined 2D and 3D analyses. The analysis involved commercial fuel rods and demonstrated successful computation of metrics of interest to fuel failures, including cladding peak hoop stress and strain energy density. Finally, in comparison with a failure threshold derived from power ramp tests, results corroborate industry analyses of the root cause of the pellet-clad interaction failures and illustrate the importance of modeling 3D local effects around fuel pellet defects, which can produce complex effects including cold spots in the cladding, stress concentrations, and hot spots in the fuel that can lead to enhanced cladding degradation such as hydriding, oxidation, CRUD formation, and stress corrosion cracking.« less

Changes among Israeli Youth Movements: A Structural Analysis Based on Kahane's Code of Informality

ERIC Educational Resources Information Center

Cohen, Erik H.

2015-01-01

Multi-dimensional data analysis tools are applied to Reuven Kahane's data on the informality of youth organizations, yielding a graphic portrayal of Kahane's code of informality. This structure helps address questions of the whether the eight structural components exhaustively cover the field without redundancy. Further, the structure is used to…

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

NASA Astrophysics Data System (ADS)

Messer, O. E. B.; Harris, J. A.; Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; Mezzacappa, A.

2018-04-01

Unraveling the core-collapse supernova (CCSN) mechanism is a problem that remains essentially unsolved despite more than four decades of effort. Spherically symmetric models with otherwise high physical fidelity generally fail to produce explosions, and it is widely accepted that CCSNe are inherently multi-dimensional. Progress in realistic modeling has occurred recently through the availability of petascale platforms and the increasing sophistication of supernova codes. We will discuss our most recent work on understanding neutrino-driven CCSN explosions employing multi-dimensional neutrino-radiation hydrodynamics simulations with the Chimera code. We discuss the inputs and resulting outputs from these simulations, the role of neutrino radiation transport, and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.

Coupled Kardar-Parisi-Zhang Equations in One Dimension

NASA Astrophysics Data System (ADS)

Ferrari, Patrik L.; Sasamoto, Tomohiro; Spohn, Herbert

2013-11-01

Over the past years our understanding of the scaling properties of the solutions to the one-dimensional KPZ equation has advanced considerably, both theoretically and experimentally. In our contribution we export these insights to the case of coupled KPZ equations in one dimension. We establish equivalence with nonlinear fluctuating hydrodynamics for multi-component driven stochastic lattice gases. To check the predictions of the theory, we perform Monte Carlo simulations of the two-component AHR model. Its steady state is computed using the matrix product ansatz. Thereby all coefficients appearing in the coupled KPZ equations are deduced from the microscopic model. Time correlations in the steady state are simulated and we confirm not only the scaling exponent, but also the scaling function and the non-universal coefficients.

Finite Volume Numerical Methods for Aeroheating Rate Calculations from Infrared Thermographic Data

NASA Technical Reports Server (NTRS)

Daryabeigi, Kamran; Berry, Scott A.; Horvath, Thomas J.; Nowak, Robert J.

2003-01-01

The use of multi-dimensional finite volume numerical techniques with finite thickness models for calculating aeroheating rates from measured global surface temperatures on hypersonic wind tunnel models was investigated. Both direct and inverse finite volume techniques were investigated and compared with the one-dimensional semi -infinite technique. Global transient surface temperatures were measured using an infrared thermographic technique on a 0.333-scale model of the Hyper-X forebody in the Langley Research Center 20-Inch Mach 6 Air tunnel. In these tests the effectiveness of vortices generated via gas injection for initiating hypersonic transition on the Hyper-X forebody were investigated. An array of streamwise orientated heating striations were generated and visualized downstream of the gas injection sites. In regions without significant spatial temperature gradients, one-dimensional techniques provided accurate aeroheating rates. In regions with sharp temperature gradients due to the striation patterns two-dimensional heat transfer techniques were necessary to obtain accurate heating rates. The use of the one-dimensional technique resulted in differences of 20% in the calculated heating rates because it did not account for lateral heat conduction in the model.

Non-monetary valuation using Multi-Criteria Decision Analysis: Sensitivity of additive aggregation methods to scaling and compensation assumptions

EPA Science Inventory

Analytical methods for Multi-Criteria Decision Analysis (MCDA) support the non-monetary valuation of ecosystem services for environmental decision making. Many published case studies transform ecosystem service outcomes into a common metric and aggregate the outcomes to set land ...

A High-Order Transport Scheme for Collisional-Radiative and Nonequilibrium Plasma

DTIC Science & Technology

2009-02-06

of change of the temperature is obtained, ∂E ∂T ∂T ∂t = ∂ ∂x ( κs ∂T ∂x ) (7.6) Assuming a one- dimensional discretization on a uniformly- spaced ...oscillations nor a quantitative analysis of the multi- dimensional shock structure has been provided to date. This dissertation builds upon previous...high-enthalpy nonequilibrium plasmas and is the focus of much of this work. The plasma is described as