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.

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.

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.

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.

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 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 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.

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.

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.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

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.

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.

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-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy

NASA Astrophysics Data System (ADS)

Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li

2018-03-01

In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.

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.

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.

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

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

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

Milledge, D.; Bellugi, D.; McKean, J. A.; Dietrich, W.

2012-12-01

The infinite slope model is the basis for almost all watershed scale slope stability models. However, it assumes that a potential landslide is infinitely long and wide. As a result, it cannot represent resistance at the margins of a potential landslide (e.g. from lateral roots), and is unable to predict the size of a potential landslide. Existing three-dimensional models generally require computationally expensive numerical solutions and have previously been applied only at the hillslope scale. Here we derive an alternative analytical treatment that accounts for lateral resistance by representing the forces acting on each margin of an unstable block. We apply 'at rest' earth pressure on the lateral sides, and 'active' and 'passive' pressure using a log-spiral method on the upslope and downslope margins. We represent root reinforcement on each margin assuming that root cohesion is an exponential function of soil depth. We benchmark this treatment against other more complete approaches (Finite Element (FE) and closed form solutions) and find that our model: 1) converges on the infinite slope predictions as length / depth and width / depth ratios become large; 2) agrees with the predictions from state-of-the-art FE models to within +/- 30% error, for the specific cases in which these can be applied. We then test our model's ability to predict failure of an actual (mapped) landslide where the relevant parameters are relatively well constrained. We find that our model predicts failure at the observed location with a nearly identical shape and predicts that larger or smaller shapes conformal to the observed shape are indeed more stable. Finally, we perform a sensitivity analysis using our model to show that lateral reinforcement sets a minimum landslide size, while the additional strength at the downslope boundary means that the optimum shape for a given size is longer in a downslope direction. However, reinforcement effects cannot fully explain the size or shape

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

Multi-Scale Modeling of an Integrated 3D Braided Composite with Applications to Helicopter Arm

NASA Astrophysics Data System (ADS)

Zhang, Diantang; Chen, Li; Sun, Ying; Zhang, Yifan; Qian, Kun

2017-10-01

A study is conducted with the aim of developing multi-scale analytical method for designing the composite helicopter arm with three-dimensional (3D) five-directional braided structure. Based on the analysis of 3D braided microstructure, the multi-scale finite element modeling is developed. Finite element analysis on the load capacity of 3D five-directional braided composites helicopter arm is carried out using the software ABAQUS/Standard. The influences of the braiding angle and loading condition on the stress and strain distribution of the helicopter arm are simulated. The results show that the proposed multi-scale method is capable of accurately predicting the mechanical properties of 3D braided composites, validated by the comparison the stress-strain curves of meso-scale RVCs. Furthermore, it is found that the braiding angle is an important factor affecting the mechanical properties of 3D five-directional braided composite helicopter arm. Based on the optimized structure parameters, the nearly net-shaped composite helicopter arm is fabricated using a novel resin transfer mould (RTM) process.

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

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.

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

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

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

Measuring the Perception of the Teachers' Autonomy-Supportive Behavior in Physical Education: Development and Initial Validation of a Multi-Dimensional Instrument

ERIC Educational Resources Information Center

Tilga, Henri; Hein, Vello; Koka, Andre

2017-01-01

This research aimed to develop and validate an instrument to assess the students' perceptions of the teachers' autonomy-supportive behavior by the multi-dimensional scale (Multi-Dimensional Perceived Autonomy Support Scale for Physical Education). The participants were 1,476 students aged 12- to 15-years-old. In Study 1, a pool of 37 items was…

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

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.

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.

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.

Application of Multi-Parameter Data Visualization by Means of Multidimensional Scaling to Evaluate Possibility of Coal Gasification

NASA Astrophysics Data System (ADS)

Jamróz, Dariusz; Niedoba, Tomasz; Surowiak, Agnieszka; Tumidajski, Tadeusz; Szostek, Roman; Gajer, Mirosław

2017-09-01

The application of methods drawing upon multi-parameter visualization of data by transformation of multidimensional space into two-dimensional one allow to show multi-parameter data on computer screen. Thanks to that, it is possible to conduct a qualitative analysis of this data in the most natural way for human being, i.e. by the sense of sight. An example of such method of multi-parameter visualization is multidimensional scaling. This method was used in this paper to present and analyze a set of seven-dimensional data obtained from Janina Mining Plant and Wieczorek Coal Mine. It was decided to examine whether the method of multi-parameter data visualization allows to divide the samples space into areas of various applicability to fluidal gasification process. The "Technological applicability card for coals" was used for this purpose [Sobolewski et al., 2012; 2017], in which the key parameters, important and additional ones affecting the gasification process were described.

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

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.

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.

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.

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.

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.

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.

Scaling and dimensional analysis of acoustic streaming jets

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

Moudjed, B.; Botton, V.; Henry, D.

2014-09-15

This paper focuses on acoustic streaming free jets. This is to say that progressive acoustic waves are used to generate a steady flow far from any wall. The derivation of the governing equations under the form of a nonlinear hydrodynamics problem coupled with an acoustic propagation problem is made on the basis of a time scale discrimination approach. This approach is preferred to the usually invoked amplitude perturbations expansion since it is consistent with experimental observations of acoustic streaming flows featuring hydrodynamic nonlinearities and turbulence. Experimental results obtained with a plane transducer in water are also presented together with amore » review of the former experimental investigations using similar configurations. A comparison of the shape of the acoustic field with the shape of the velocity field shows that diffraction is a key ingredient in the problem though it is rarely accounted for in the literature. A scaling analysis is made and leads to two scaling laws for the typical velocity level in acoustic streaming free jets; these are both observed in our setup and in former studies by other teams. We also perform a dimensional analysis of this problem: a set of seven dimensionless groups is required to describe a typical acoustic experiment. We find that a full similarity is usually not possible between two acoustic streaming experiments featuring different fluids. We then choose to relax the similarity with respect to sound attenuation and to focus on the case of a scaled water experiment representing an acoustic streaming application in liquid metals, in particular, in liquid silicon and in liquid sodium. We show that small acoustic powers can yield relatively high Reynolds numbers and velocity levels; this could be a virtue for heat and mass transfer applications, but a drawback for ultrasonic velocimetry.« less

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.

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

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.

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.

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…

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.

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.

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?

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.

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.

Multi-scale Modeling and Analysis of Nano-RFID Systems on HPC Setup

NASA Astrophysics Data System (ADS)

Pathak, Rohit; Joshi, Satyadhar

In this paper we have worked out on some the complex modeling aspects such as Multi Scale modeling, MATLAB Sugar based modeling and have shown the complexities involved in the analysis of Nano RFID (Radio Frequency Identification) systems. We have shown the modeling and simulation and demonstrated some novel ideas and library development for Nano RFID. Multi scale modeling plays a very important role in nanotech enabled devices properties of which cannot be explained sometimes by abstraction level theories. Reliability and packaging still remains one the major hindrances in practical implementation of Nano RFID based devices. And to work on them modeling and simulation will play a very important role. CNTs is the future low power material that will replace CMOS and its integration with CMOS, MEMS circuitry will play an important role in realizing the true power in Nano RFID systems. RFID based on innovations in nanotechnology has been shown. MEMS modeling of Antenna, sensors and its integration in the circuitry has been shown. Thus incorporating this we can design a Nano-RFID which can be used in areas like human implantation and complex banking applications. We have proposed modeling of RFID using the concept of multi scale modeling to accurately predict its properties. Also we give the modeling of MEMS devices that are proposed recently that can see possible application in RFID. We have also covered the applications and the advantages of Nano RFID in various areas. RF MEMS has been matured and its devices are being successfully commercialized but taking it to limits of nano domains and integration with singly chip RFID needs a novel approach which is being proposed. We have modeled MEMS based transponder and shown the distribution for multi scale modeling for Nano RFID.

Single Channel EEG Artifact Identification Using Two-Dimensional Multi-Resolution Analysis.

PubMed

Taherisadr, Mojtaba; Dehzangi, Omid; Parsaei, Hossein

2017-12-13

As a diagnostic monitoring approach, electroencephalogram (EEG) signals can be decoded by signal processing methodologies for various health monitoring purposes. However, EEG recordings are contaminated by other interferences, particularly facial and ocular artifacts generated by the user. This is specifically an issue during continuous EEG recording sessions, and is therefore a key step in using EEG signals for either physiological monitoring and diagnosis or brain-computer interface to identify such artifacts from useful EEG components. In this study, we aim to design a new generic framework in order to process and characterize EEG recording as a multi-component and non-stationary signal with the aim of localizing and identifying its component (e.g., artifact). In the proposed method, we gather three complementary algorithms together to enhance the efficiency of the system. Algorithms include time-frequency (TF) analysis and representation, two-dimensional multi-resolution analysis (2D MRA), and feature extraction and classification. Then, a combination of spectro-temporal and geometric features are extracted by combining key instantaneous TF space descriptors, which enables the system to characterize the non-stationarities in the EEG dynamics. We fit a curvelet transform (as a MRA method) to 2D TF representation of EEG segments to decompose the given space to various levels of resolution. Such a decomposition efficiently improves the analysis of the TF spaces with different characteristics (e.g., resolution). Our experimental results demonstrate that the combination of expansion to TF space, analysis using MRA, and extracting a set of suitable features and applying a proper predictive model is effective in enhancing the EEG artifact identification performance. We also compare the performance of the designed system with another common EEG signal processing technique-namely, 1D wavelet transform. Our experimental results reveal that the proposed method outperforms

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.

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.

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

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

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…

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).

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

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/ .

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

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.

On Multi-Dimensional Unstructured Mesh Adaption

NASA Technical Reports Server (NTRS)

Wood, William A.; Kleb, William L.

1999-01-01

Anisotropic unstructured mesh adaption is developed for a truly multi-dimensional upwind fluctuation splitting scheme, as applied to scalar advection-diffusion. The adaption is performed locally using edge swapping, point insertion/deletion, and nodal displacements. Comparisons are made versus the current state of the art for aggressive anisotropic unstructured adaption, which is based on a posteriori error estimates. Demonstration of both schemes to model problems, with features representative of compressible gas dynamics, show the present method to be superior to the a posteriori adaption for linear advection. The performance of the two methods is more similar when applied to nonlinear advection, with a difference in the treatment of shocks. The a posteriori adaption can excessively cluster points to a shock, while the present multi-dimensional scheme tends to merely align with a shock, using fewer nodes. As a consequence of this alignment tendency, an implementation of eigenvalue limiting for the suppression of expansion shocks is developed for the multi-dimensional distribution scheme. The differences in the treatment of shocks by the adaption schemes, along with the inherently low levels of artificial dissipation in the fluctuation splitting solver, suggest the present method is a strong candidate for applications to compressible gas dynamics.

Multi-scale signed envelope inversion

NASA Astrophysics Data System (ADS)

Chen, Guo-Xin; Wu, Ru-Shan; Wang, Yu-Qing; Chen, Sheng-Chang

2018-06-01

Envelope inversion based on modulation signal mode was proposed to reconstruct large-scale structures of underground media. In order to solve the shortcomings of conventional envelope inversion, multi-scale envelope inversion was proposed using new envelope Fréchet derivative and multi-scale inversion strategy to invert strong contrast models. In multi-scale envelope inversion, amplitude demodulation was used to extract the low frequency information from envelope data. However, only to use amplitude demodulation method will cause the loss of wavefield polarity information, thus increasing the possibility of inversion to obtain multiple solutions. In this paper we proposed a new demodulation method which can contain both the amplitude and polarity information of the envelope data. Then we introduced this demodulation method into multi-scale envelope inversion, and proposed a new misfit functional: multi-scale signed envelope inversion. In the numerical tests, we applied the new inversion method to the salt layer model and SEG/EAGE 2-D Salt model using low-cut source (frequency components below 4 Hz were truncated). The results of numerical test demonstrated the effectiveness of this method.

Scale-free crystallization of two-dimensional complex plasmas: Domain analysis using Minkowski tensors

NASA Astrophysics Data System (ADS)

Böbel, A.; Knapek, C. A.; Räth, C.

2018-05-01

Experiments of the recrystallization processes in two-dimensional complex plasmas are analyzed to rigorously test a recently developed scale-free phase transition theory. The "fractal-domain-structure" (FDS) theory is based on the kinetic theory of Frenkel. It assumes the formation of homogeneous domains, separated by defect lines, during crystallization and a fractal relationship between domain area and boundary length. For the defect number fraction and system energy a scale-free power-law relation is predicted. The long-range scaling behavior of the bond-order correlation function shows clearly that the complex plasma phase transitions are not of the Kosterlitz, Thouless, Halperin, Nelson, and Young type. Previous preliminary results obtained by counting the number of dislocations and applying a bond-order metric for structural analysis are reproduced. These findings are supplemented by extending the use of the bond-order metric to measure the defect number fraction and furthermore applying state-of-the-art analysis methods, allowing a systematic testing of the FDS theory with unprecedented scrutiny: A morphological analysis of lattice structure is performed via Minkowski tensor methods. Minkowski tensors form a complete family of additive, motion covariant and continuous morphological measures that are sensitive to nonlinear properties. The FDS theory is rigorously confirmed and predictions of the theory are reproduced extremely well. The predicted scale-free power-law relation between defect fraction number and system energy is verified for one more order of magnitude at high energies compared to the inherently discontinuous bond-order metric. It is found that the fractal relation between crystalline domain area and circumference is independent of the experiment, the particular Minkowski tensor method, and the particular choice of parameters. Thus, the fractal relationship seems to be inherent to two-dimensional phase transitions in complex plasmas. Minkowski

Percolation analysis of nonlinear structures in scale-free two-dimensional simulations

NASA Technical Reports Server (NTRS)

Dominik, Kurt G.; Shandarin, Sergei F.

1992-01-01

Results are presented of applying percolation analysis to several two-dimensional N-body models which simulate the formation of large-scale structure. Three parameters are estimated: total area (a(c)), total mass (M(C)), and percolation density (rho(c)) of the percolating structure at the percolation threshold for both unsmoothed and smoothed (with different scales L(s)) nonlinear with filamentary structures, confirming early speculations that this type of model has several features of filamentary-type distributions. Also, it is shown that, by properly applying smoothing techniques, many problems previously considered detrimental can be dealt with and overcome. Possible difficulties and prospects with the use of this method are discussed, specifically relating to techniques and methods already applied to CfA deep sky surveys. The success of this test in two dimensions and the potential for extrapolation to three dimensions is also discussed.

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

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.

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.

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

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.

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

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.

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.

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-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.

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.

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.

Multi-Scale Models for the Scale Interaction of Organized Tropical Convection

NASA Astrophysics Data System (ADS)

Yang, Qiu

Assessing the upscale impact of organized tropical convection from small spatial and temporal scales is a research imperative, not only for having a better understanding of the multi-scale structures of dynamical and convective fields in the tropics, but also for eventually helping in the design of new parameterization strategies to improve the next-generation global climate models. Here self-consistent multi-scale models are derived systematically by following the multi-scale asymptotic methods and used to describe the hierarchical structures of tropical atmospheric flows. The advantages of using these multi-scale models lie in isolating the essential components of multi-scale interaction and providing assessment of the upscale impact of the small-scale fluctuations onto the large-scale mean flow through eddy flux divergences of momentum and temperature in a transparent fashion. Specifically, this thesis includes three research projects about multi-scale interaction of organized tropical convection, involving tropical flows at different scaling regimes and utilizing different multi-scale models correspondingly. Inspired by the observed variability of tropical convection on multiple temporal scales, including daily and intraseasonal time scales, the goal of the first project is to assess the intraseasonal impact of the diurnal cycle on the planetary-scale circulation such as the Hadley cell. As an extension of the first project, the goal of the second project is to assess the intraseasonal impact of the diurnal cycle over the Maritime Continent on the Madden-Julian Oscillation. In the third project, the goals are to simulate the baroclinic aspects of the ITCZ breakdown and assess its upscale impact on the planetary-scale circulation over the eastern Pacific. These simple multi-scale models should be useful to understand the scale interaction of organized tropical convection and help improve the parameterization of unresolved processes in global climate models.

Mechanics of low-dimensional carbon nanostructures: Atomistic, continuum, and multi-scale approaches

NASA Astrophysics Data System (ADS)

Mahdavi, Arash

A new multiscale modeling technique called the Consistent Atomic-scale Finite Element (CAFE) method is introduced. Unlike traditional approaches for linking the atomic structure to its equivalent continuum, this method directly connects the atomic degrees of freedom to a reduced set of finite element degrees of freedom without passing through an intermediate homogenized continuum. As a result, there is no need to introduce stress and strain measures at the atomic level. The Tersoff-Brenner interatomic potential is used to calculate the consistent tangent stiffness matrix of the structure. In this finite element formulation, all local and non-local interactions between carbon atoms are taken into account using overlapping finite elements. In addition, a consistent hierarchical finite element modeling technique is developed for adaptively coarsening and refining the mesh over different parts of the model. This process is consistent with the underlying atomic structure and, by refining the mesh to the scale of atomic spacing, molecular dynamic results can be recovered. This method is valid across the scales and can be used to concurrently model atomistic and continuum phenomena so, in contrast with most other multi-scale methods, there is no need to introduce artificial boundaries for coupling atomistic and continuum regions. Effect of the length scale of the nanostructure is also included in the model by building the hierarchy of elements from bottom up using a finite size atom cluster as the building block. To be consistent with the bravais multi-lattice structure of sp2-bonded carbon, two independent displacement fields are used for reducing the order of the model. Sparse structure of the stiffness matrix of these nanostructures is exploited to reduce the memory requirement and to speed up the formation of the system matrices and solution of the equilibrium equations. Applicability of the method is shown with several examples of the nonlinear mechanics of carbon

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.

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.

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.

Consumer preference of fertilizer in West Java using multi-dimensional scaling approach

NASA Astrophysics Data System (ADS)

Utami, Hesty Nurul; Sadeli, Agriani Hermita; Perdana, Tomy; Renaldy, Eddy; Mahra Arari, H.; Ajeng Sesy N., P.; Fernianda Rahayu, H.; Ginanjar, Tetep; Sanjaya, Sonny

2018-02-01

There are various fertilizer products in the markets for farmers to be used for farming activities. Fertilizers are a supplements supply to soil nutrients, build up soil fertility in order to support plant nutrients and increase plants productivity. Fertilizers consists of nitrogen, phosphorous, potassium, micro vitamins and other complex nutrient in farming systems that commonly used in agricultural activities to improve quantity and quality of harvest. Recently, market demand for fertilizer has been increased dramatically; furthermore, fertilizer companies are required to develop strategies to know about consumer preferences towards several issues. Consumer preference depends on consumer needs selected by subject (individual) that is measured by utilization from several things that market offered and as final decision on purchase process. West Java is one of province as the main producer of agricultural products and automatically is one of the potential consumer's fertilizers on farming activities. This research is a case study in nine districts in West Java province, i.e., Bandung, West Bandung, Bogor, Depok, Garut, Indramayu, Majalengka, Cirebon and Cianjur. The purpose of this research is to describe the attributes on consumer preference for fertilizers. The multi-dimensional scaling method is used as quantitative method to help visualize the level of similarity of individual cases on a dataset, to describe and mapping the information system and to accept the goal. The attributes in this research are availability, nutrients content, price, form of fertilizer, decomposition speed, easy to use, label, packaging type, color, design and size of packaging, hardening process and promotion. There are tendency towards two fertilizer brand have similarity on availability of products, price, speed of decomposition and hardening process.

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.

The Chinese version of the Myocardial Infarction Dimensional Assessment Scale (MIDAS): Mokken scaling

PubMed Central

2012-01-01

Background Hierarchical scales are very useful in clinical practice due to their ability to discriminate precisely between individuals, and the original English version of the Myocardial Infarction Dimensional Assessment Scale has been shown to contain a hierarchy of items. The purpose of this study was to analyse a Mandarin Chinese translation of the Myocardial Infarction Dimensional Assessment Scale for a hierarchy of items according to the criteria of Mokken scaling. Data from 180 Chinese participants who completed the Chinese translation of the Myocardial Infarction Dimensional Assessment Scale were analysed using the Mokken Scaling Procedure and the 'R' statistical programme using the diagnostics available in these programmes. Correlation between Mandarin Chinese items and a Chinese translation of the Short Form (36) Health Survey was also analysed. Findings Fifteen items from the Mandarin Chinese Myocardial Infarction Dimensional Assessment Scale were retained in a strong and reliable Mokken scale; invariant item ordering was not evident and the Mokken scaled items of the Chinese Myocardial Infarction Dimensional Assessment Scale correlated with the Short Form (36) Health Survey. Conclusions Items from the Mandarin Chinese Myocardial Infarction Dimensional Assessment Scale form a Mokken scale and this offers further insight into how the items of the Myocardial Infarction Dimensional Assessment Scale relate to the measurement of health-related quality of life people with a myocardial infarction. PMID:22221696

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.

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.

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.

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

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.

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.

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.

Towards large scale multi-target tracking

NASA Astrophysics Data System (ADS)

Vo, Ba-Ngu; Vo, Ba-Tuong; Reuter, Stephan; Lam, Quang; Dietmayer, Klaus

2014-06-01

Multi-target tracking is intrinsically an NP-hard problem and the complexity of multi-target tracking solutions usually do not scale gracefully with problem size. Multi-target tracking for on-line applications involving a large number of targets is extremely challenging. This article demonstrates the capability of the random finite set approach to provide large scale multi-target tracking algorithms. In particular it is shown that an approximate filter known as the labeled multi-Bernoulli filter can simultaneously track one thousand five hundred targets in clutter on a standard laptop computer.

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.

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.

Multi-Scale/Multi-Functional Probabilistic Composite Fatigue

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A multi-level (multi-scale/multi-functional) evaluation is demonstrated by applying it to three different sample problems. These problems include the probabilistic evaluation of a space shuttle main engine blade, an engine rotor and an aircraft wing. The results demonstrate that the blade will fail at the highest probability path, the engine two-stage rotor will fail by fracture at the rim and the aircraft wing will fail at 109 fatigue cycles with a probability of 0.9967.

Spectral Dimensionality and Scale of Urban Radiance

NASA Technical Reports Server (NTRS)

Small, Christopher

2001-01-01

Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

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.

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

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

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.

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.

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.

Vortex scaling ranges in two-dimensional turbulence

NASA Astrophysics Data System (ADS)

Burgess, B. H.; Dritschel, D. G.; Scott, R. K.

2017-11-01

We survey the role of coherent vortices in two-dimensional turbulence, including formation mechanisms, implications for classical similarity and inertial range theories, and characteristics of the vortex populations. We review early work on the spatial and temporal scaling properties of vortices in freely evolving turbulence and more recent developments, including a spatiotemporal scaling theory for vortices in the forced inverse energy cascade. We emphasize that Kraichnan-Batchelor similarity theories and vortex scaling theories are best viewed as complementary and together provide a more complete description of two-dimensional turbulence. In particular, similarity theory has a continued role in describing the weak filamentary sea between the vortices. Moreover, we locate both classical inertial and vortex scaling ranges within the broader framework of scaling in far-from-equilibrium systems, which generically exhibit multiple fixed point solutions with distinct scaling behaviour. We describe how stationary transport in a range of scales comoving with the dilatation of flow features, as measured by the growth in vortex area, constrains the vortex number density in both freely evolving and forced two-dimensional turbulence. The new theories for coherent vortices reveal previously hidden nontrivial scaling, point to new dynamical understanding, and provide a novel exciting window into two-dimensional turbulence.

Multi-dimensional simulations of core-collapse supernova explosions with CHIMERA

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

Messer, Bronson; Harris, James Austin; Hix, William Raphael

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,more » and the importance of multi-dimensional fluid flows in shaping the explosions. We also highlight the production of 48Ca in long-running Chimera simulations.« less

The Edinburgh Postnatal Depression Scale: Screening Tool for Postpartum Anxiety as Well? Findings from a Confirmatory Factor Analysis of the Hebrew Version.

PubMed

Bina, Rena; Harrington, Donna

2016-04-01

The Edinburgh Postnatal Depression Scale (EPDS) was originally created as a uni-dimensional scale to screen for postpartum depression (PPD); however, evidence from various studies suggests that it is a multi-dimensional scale measuring mainly anxiety in addition to depression. The factor structure of the EPDS seems to differ across various language translations, raising questions regarding its stability. This study examined the factor structure of the Hebrew version of the EPDS to assess whether it is uni- or multi-dimensional. Seven hundred and fifteen (n = 715) women were screened at 6 weeks postpartum using the Hebrew version of the EPDS. Confirmatory factor analysis (CFA) was used to test four models derived from the literature. Of the four CFA models tested, a 9-item two factor model fit the data best, with one factor representing an underlying depression construct and the other representing an underlying anxiety construct. for Practice The Hebrew version of the EPDS appears to consist of depression and anxiety sub-scales. Given the widespread PPD screening initiatives, anxiety symptoms should be addressed in addition to depressive symptoms, and a short scale, such as the EPDS, assessing both may be efficient.

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…

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis.

PubMed

Gorman, Bryan R; Lu, Junjie; Baccei, Anna; Lowry, Nathan C; Purvis, Jeremy E; Mangoubi, Rami S; Lerou, Paul H

2014-01-01

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

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-dimensional multi-species modeling of transient electrodeposition in LIGA microfabrication.

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

Evans, Gregory Herbert; Chen, Ken Shuang

2004-06-01

This report documents the efforts and accomplishments of the LIGA electrodeposition modeling project which was headed by the ASCI Materials and Physics Modeling Program. A multi-dimensional framework based on GOMA was developed for modeling time-dependent diffusion and migration of multiple charged species in a dilute electrolyte solution with reduction electro-chemical reactions on moving deposition surfaces. By combining the species mass conservation equations with the electroneutrality constraint, a Poisson equation that explicitly describes the electrolyte potential was derived. The set of coupled, nonlinear equations governing species transport, electric potential, velocity, hydrodynamic pressure, and mesh motion were solved in GOMA, using themore » finite-element method and a fully-coupled implicit solution scheme via Newton's method. By treating the finite-element mesh as a pseudo solid with an arbitrary Lagrangian-Eulerian formulation and by repeatedly performing re-meshing with CUBIT and re-mapping with MAPVAR, the moving deposition surfaces were tracked explicitly from start of deposition until the trenches were filled with metal, thus enabling the computation of local current densities that potentially influence the microstructure and frictional/mechanical properties of the deposit. The multi-dimensional, multi-species, transient computational framework was demonstrated in case studies of two-dimensional nickel electrodeposition in single and multiple trenches, without and with bath stirring or forced flow. Effects of buoyancy-induced convection on deposition were also investigated. To further illustrate its utility, the framework was employed to simulate deposition in microscreen-based LIGA molds. Lastly, future needs for modeling LIGA electrodeposition are discussed.« less

a Region-Based Multi-Scale Approach for Object-Based Image Analysis

NASA Astrophysics Data System (ADS)

Kavzoglu, T.; Yildiz Erdemir, M.; Tonbul, H.

2016-06-01

Within the last two decades, object-based image analysis (OBIA) considering objects (i.e. groups of pixels) instead of pixels has gained popularity and attracted increasing interest. The most important stage of the OBIA is image segmentation that groups spectrally similar adjacent pixels considering not only the spectral features but also spatial and textural features. Although there are several parameters (scale, shape, compactness and band weights) to be set by the analyst, scale parameter stands out the most important parameter in segmentation process. Estimating optimal scale parameter is crucially important to increase the classification accuracy that depends on image resolution, image object size and characteristics of the study area. In this study, two scale-selection strategies were implemented in the image segmentation process using pan-sharped Qickbird-2 image. The first strategy estimates optimal scale parameters for the eight sub-regions. For this purpose, the local variance/rate of change (LV-RoC) graphs produced by the ESP-2 tool were analysed to determine fine, moderate and coarse scales for each region. In the second strategy, the image was segmented using the three candidate scale values (fine, moderate, coarse) determined from the LV-RoC graph calculated for whole image. The nearest neighbour classifier was applied in all segmentation experiments and equal number of pixels was randomly selected to calculate accuracy metrics (overall accuracy and kappa coefficient). Comparison of region-based and image-based segmentation was carried out on the classified images and found that region-based multi-scale OBIA produced significantly more accurate results than image-based single-scale OBIA. The difference in classification accuracy reached to 10% in terms of overall accuracy.

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.

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.

A novel fruit shape classification method based on multi-scale analysis

NASA Astrophysics Data System (ADS)

Gui, Jiangsheng; Ying, Yibin; Rao, Xiuqin

2005-11-01

Shape is one of the major concerns and which is still a difficult problem in automated inspection and sorting of fruits. In this research, we proposed the multi-scale energy distribution (MSED) for object shape description, the relationship between objects shape and its boundary energy distribution at multi-scale was explored for shape extraction. MSED offers not only the mainly energy which represent primary shape information at the lower scales, but also subordinate energy which represent local shape information at higher differential scales. Thus, it provides a natural tool for multi resolution representation and can be used as a feature for shape classification. We addressed the three main processing steps in the MSED-based shape classification. They are namely, 1) image preprocessing and citrus shape extraction, 2) shape resample and shape feature normalization, 3) energy decomposition by wavelet and classification by BP neural network. Hereinto, shape resample is resample 256 boundary pixel from a curve which is approximated original boundary by using cubic spline in order to get uniform raw data. A probability function was defined and an effective method to select a start point was given through maximal expectation, which overcame the inconvenience of traditional methods in order to have a property of rotation invariants. The experiment result is relatively well normal citrus and serious abnormality, with a classification rate superior to 91.2%. The global correct classification rate is 89.77%, and our method is more effective than traditional method. The global result can meet the request of fruit grading.

Scalable Triadic Analysis of Large-Scale Graphs: Multi-Core vs. Multi-Processor vs. Multi-Threaded Shared Memory Architectures

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

Chin, George; Marquez, Andres; Choudhury, Sutanay

2012-09-01

Triadic analysis encompasses a useful set of graph mining methods that is centered on the concept of a triad, which is a subgraph of three nodes and the configuration of directed edges across the nodes. Such methods are often applied in the social sciences as well as many other diverse fields. Triadic methods commonly operate on a triad census that counts the number of triads of every possible edge configuration in a graph. Like other graph algorithms, triadic census algorithms do not scale well when graphs reach tens of millions to billions of nodes. To enable the triadic analysis ofmore » large-scale graphs, we developed and optimized a triad census algorithm to efficiently execute on shared memory architectures. We will retrace the development and evolution of a parallel triad census algorithm. Over the course of several versions, we continually adapted the code’s data structures and program logic to expose more opportunities to exploit parallelism on shared memory that would translate into improved computational performance. We will recall the critical steps and modifications that occurred during code development and optimization. Furthermore, we will compare the performances of triad census algorithm versions on three specific systems: Cray XMT, HP Superdome, and AMD multi-core NUMA machine. These three systems have shared memory architectures but with markedly different hardware capabilities to manage parallelism.« less

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.

Scaling analysis of field-tuned superconductor-insulator transition in two-dimensional tantalum thin films.

PubMed

Park, Sungyu; Shin, Junghyun; Kim, Eunseong

2017-02-20

The superconductor-insulator (SI) transition in two-dimensional Ta thin films is investigated by controlling both film thickness and magnetic field. An intriguing metallic phase appears between a superconducting and an insulating phase within a range of film thickness and magnetic field. The temperature and electric field scaling analyses are performed to investigate the nature of the SI transition in the thickness-tuned metallic and superconducting samples. The critical exponents product of νz obtained from the temperature scaling analysis is found to be approximately 0.67 in the entire range of film thickness. On the other hand, an apparent discrepancy is measured in the product of ν(z + 1) by the electric filed analysis. The product values are found to be about 1.37 for the superconducting films and about 1.86 for the metallic films respectively. We find that the discrepancy is the direct consequence of electron heating that introduces additional dissipation channels in the metallic Ta films.

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.

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

Automated image analysis reveals the dynamic 3-dimensional organization of multi-ciliary arrays

PubMed Central

Galati, Domenico F.; Abuin, David S.; Tauber, Gabriel A.; Pham, Andrew T.; Pearson, Chad G.

2016-01-01

ABSTRACT Multi-ciliated cells (MCCs) use polarized fields of undulating cilia (ciliary array) to produce fluid flow that is essential for many biological processes. Cilia are positioned by microtubule scaffolds called basal bodies (BBs) that are arranged within a spatially complex 3-dimensional geometry (3D). Here, we develop a robust and automated computational image analysis routine to quantify 3D BB organization in the ciliate, Tetrahymena thermophila. Using this routine, we generate the first morphologically constrained 3D reconstructions of Tetrahymena cells and elucidate rules that govern the kinetics of MCC organization. We demonstrate the interplay between BB duplication and cell size expansion through the cell cycle. In mutant cells, we identify a potential BB surveillance mechanism that balances large gaps in BB spacing by increasing the frequency of closely spaced BBs in other regions of the cell. Finally, by taking advantage of a mutant predisposed to BB disorganization, we locate the spatial domains that are most prone to disorganization by environmental stimuli. Collectively, our analyses reveal the importance of quantitative image analysis to understand the principles that guide the 3D organization of MCCs. PMID:26700722

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

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.

Confirmatory Factor Analysis of the Hewitt-Multidimensional Perfectionism Scale

ERIC Educational Resources Information Center

Barut, Yasar

2015-01-01

Various studies on the conceptual framework of perfectionism construct use Hewitt Multi-dimensional Perfectionism Scale (HMPS), as a basic approach. The measure has a prominent role with respect to the theoretical considerations of perfectionism dimensions. This study aimed to evaluate the psychometric properties of the Turkish version of the…

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.

Multi-scale Material Appearance

NASA Astrophysics Data System (ADS)

Wu, Hongzhi

Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.

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…

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 Ca

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.

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.

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

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

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.

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...

Fast multi-dimensional NMR by minimal sampling

NASA Astrophysics Data System (ADS)

Kupče, Ēriks; Freeman, Ray

2008-03-01

A new scheme is proposed for very fast acquisition of three-dimensional NMR spectra based on minimal sampling, instead of the customary step-wise exploration of all of evolution space. The method relies on prior experiments to determine accurate values for the evolving frequencies and intensities from the two-dimensional 'first planes' recorded by setting t1 = 0 or t2 = 0. With this prior knowledge, the entire three-dimensional spectrum can be reconstructed by an additional measurement of the response at a single location (t1∗,t2∗) where t1∗ and t2∗ are fixed values of the evolution times. A key feature is the ability to resolve problems of overlap in the acquisition dimension. Applied to a small protein, agitoxin, the three-dimensional HNCO spectrum is obtained 35 times faster than systematic Cartesian sampling of the evolution domain. The extension to multi-dimensional spectroscopy is outlined.

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.

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

Multi-scale modeling in cell biology

PubMed Central

Meier-Schellersheim, Martin; Fraser, Iain D. C.; Klauschen, Frederick

2009-01-01

Biomedical research frequently involves performing experiments and developing hypotheses that link different scales of biological systems such as, for instance, the scales of intracellular molecular interactions to the scale of cellular behavior and beyond to the behavior of cell populations. Computational modeling efforts that aim at exploring such multi-scale systems quantitatively with the help of simulations have to incorporate several different simulation techniques due to the different time and space scales involved. Here, we provide a non-technical overview of how different scales of experimental research can be combined with the appropriate computational modeling techniques. We also show that current modeling software permits building and simulating multi-scale models without having to become involved with the underlying technical details of computational modeling. PMID:20448808

Geomorphometric multi-scale analysis for the recognition of Moon surface features using multi-resolution DTMs

NASA Astrophysics Data System (ADS)

Li, Ke; Chen, Jianping; Sofia, Giulia; Tarolli, Paolo

2014-05-01

Moon surface features have great significance in understanding and reconstructing the lunar geological evolution. Linear structures like rilles and ridges are closely related to the internal forced tectonic movement. The craters widely distributed on the moon are also the key research targets for external forced geological evolution. The extremely rare availability of samples and the difficulty for field works make remote sensing the most important approach for planetary studies. New and advanced lunar probes launched by China, U.S., Japan and India provide nowadays a lot of high-quality data, especially in the form of high-resolution Digital Terrain Models (DTMs), bringing new opportunities and challenges for feature extraction on the moon. The aim of this study is to recognize and extract lunar features using geomorphometric analysis based on multi-scale parameters and multi-resolution DTMs. The considered digital datasets include CE1-LAM (Chang'E One, Laser AltiMeter) data with resolution of 500m/pix, LRO-WAC (Lunar Reconnaissance Orbiter, Wide Angle Camera) data with resolution of 100m/pix, LRO-LOLA (Lunar Reconnaissance Orbiter, Lunar Orbiter Laser Altimeter) data with resolution of 60m/pix, and LRO-NAC (Lunar Reconnaissance Orbiter, Narrow Angle Camera) data with resolution of 2-5m/pix. We considered surface derivatives to recognize the linear structures including Rilles and Ridges. Different window scales and thresholds for are considered for feature extraction. We also calculated the roughness index to identify the erosion/deposits area within craters. The results underline the suitability of the adopted methods for feature recognition on the moon surface. The roughness index is found to be a useful tool to distinguish new craters, with higher roughness, from the old craters, which present a smooth and less rough surface.

Correlations of stock price fluctuations under multi-scale and multi-threshold scenarios

NASA Astrophysics Data System (ADS)

Sui, Guo; Li, Huajiao; Feng, Sida; Liu, Xueyong; Jiang, Meihui

2018-01-01

The multi-scale method is widely used in analyzing time series of financial markets and it can provide market information for different economic entities who focus on different periods. Through constructing multi-scale networks of price fluctuation correlation in the stock market, we can detect the topological relationship between each time series. Previous research has not addressed the problem that the original fluctuation correlation networks are fully connected networks and more information exists within these networks that is currently being utilized. Here we use listed coal companies as a case study. First, we decompose the original stock price fluctuation series into different time scales. Second, we construct the stock price fluctuation correlation networks at different time scales. Third, we delete the edges of the network based on thresholds and analyze the network indicators. Through combining the multi-scale method with the multi-threshold method, we bring to light the implicit information of fully connected networks.

Differentially Private Synthesization of Multi-Dimensional Data using Copula Functions

PubMed Central

Li, Haoran; Xiong, Li; Jiang, Xiaoqian

2014-01-01

Differential privacy has recently emerged in private statistical data release as one of the strongest privacy guarantees. Most of the existing techniques that generate differentially private histograms or synthetic data only work well for single dimensional or low-dimensional histograms. They become problematic for high dimensional and large domain data due to increased perturbation error and computation complexity. In this paper, we propose DPCopula, a differentially private data synthesization technique using Copula functions for multi-dimensional data. The core of our method is to compute a differentially private copula function from which we can sample synthetic data. Copula functions are used to describe the dependence between multivariate random vectors and allow us to build the multivariate joint distribution using one-dimensional marginal distributions. We present two methods for estimating the parameters of the copula functions with differential privacy: maximum likelihood estimation and Kendall’s τ estimation. We present formal proofs for the privacy guarantee as well as the convergence property of our methods. Extensive experiments using both real datasets and synthetic datasets demonstrate that DPCopula generates highly accurate synthetic multi-dimensional data with significantly better utility than state-of-the-art techniques. PMID:25405241

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with

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.

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.

Multi-scale analysis and characterization of the ITER pre-compression rings

NASA Astrophysics Data System (ADS)

Foussat, A.; Park, B.; Rajainmaki, H.

2014-01-01

The toroidal field (TF) system of ITER Tokamak composed of 18 "D" shaped Toroidal Field (TF) coils during an operating scenario experiences out-of-plane forces caused by the interaction between the 68kA operating TF current and the poloidal magnetic fields. In order to keep the induced static and cyclic stress range in the intercoil shear keys between coils cases within the ITER allowable limits [1], centripetal preload is introduced by means of S2 fiber-glass/epoxy composite pre-compression rings (PCRs). Those PCRs consist in two sets of three rings, each 5 m in diameter and 337 × 288 mm in cross-section, and are installed at the top and bottom regions to apply a total resultant preload of 70 MN per TF coil equivalent to about 400 MPa hoop stress. Recent developments of composites in the aerospace industry have accelerated the use of advanced composites as primary structural materials. The PCRs represent one of the most challenging composite applications of large dimensions and highly stressed structures operating at 4 K over a long term life. Efficient design of those pre-compression composite structures requires a detailed understanding of both the failure behavior of the structure and the fracture behavior of the material. Due to the inherent difficulties to carry out real scale testing campaign, there is a need to develop simulation tools to predict the multiple complex failure mechanisms in pre-compression rings. A framework contract was placed by ITER Organization with SENER Ingenieria y Sistemas SA to develop multi-scale models representative of the composite structure of the Pre-compression rings based on experimental material data. The predictive modeling based on ABAQUS FEM provides the opportunity both to understand better how PCR composites behave in operating conditions and to support the development of materials by the supplier with enhanced performance to withstand the machine design lifetime of 30,000 cycles. The multi-scale stress analysis has

Multi-Scale Effects in the Strength of Ceramics

PubMed Central

Cook, Robert F.

2016-01-01

Multiple length-scale effects are demonstrated in indentation-strength measurements of a range of ceramic materials under inert and reactive conditions. Meso-scale effects associated with flaw disruption by lateral cracking at large indentation loads are shown to increase strengths above the ideal indentation response. Micro-scale effects associated with toughening by microstructural restraints at small indentation loads are shown to decrease strengths below the ideal response. A combined meso-micro-scale analysis is developed that describes ceramic inert strength behaviors over the complete indentation flaw size range. Nano-scale effects associated with chemical equilibria and crack velocity thresholds are shown to lead to invariant minimum strengths at slow applied stressing rates under reactive conditions. A combined meso-micro-nano-scale analysis is developed that describes the full range of reactive and inert strength behaviors as a function of indentation load and applied stressing rate. Applications of the multi-scale analysis are demonstrated for materials design, materials selection, toughness determination, crack velocity determination, bond-rupture parameter determination, and prediction of reactive strengths. The measurements and analysis provide strong support for the existence of sharp crack tips in ceramics such that the nano-scale mechanisms of discrete bond rupture are separate from the larger scale crack driving force mechanics characterized by continuum-based stress-intensity factors. PMID:27563150

Gradient design for liquid chromatography using multi-scale optimization.

PubMed

López-Ureña, S; Torres-Lapasió, J R; Donat, R; García-Alvarez-Coque, M C

2018-01-26

In reversed phase-liquid chromatography, the usual solution to the "general elution problem" is the application of gradient elution with programmed changes of organic solvent (or other properties). A correct quantification of chromatographic peaks in liquid chromatography requires well resolved signals in a proper analysis time. When the complexity of the sample is high, the gradient program should be accommodated to the local resolution needs of each analyte. This makes the optimization of such situations rather troublesome, since enhancing the resolution for a given analyte may imply a collateral worsening of the resolution of other analytes. The aim of this work is to design multi-linear gradients that maximize the resolution, while fulfilling some restrictions: all peaks should be eluted before a given maximal time, the gradient should be flat or increasing, and sudden changes close to eluting peaks are penalized. Consequently, an equilibrated baseline resolution for all compounds is sought. This goal is achieved by splitting the optimization problem in a multi-scale framework. In each scale κ, an optimization problem is solved with N κ  ≈ 2 κ variables that are used to build the gradients. The N κ variables define cubic splines written in terms of a B-spline basis. This allows expressing gradients as polygonals of M points approximating the splines. The cubic splines are built using subdivision schemes, a technique of fast generation of smooth curves, compatible with the multi-scale framework. Owing to the nature of the problem and the presence of multiple local maxima, the algorithm used in the optimization problem of each scale κ should be "global", such as the pattern-search algorithm. The multi-scale optimization approach is successfully applied to find the best multi-linear gradient for resolving a mixture of amino acid derivatives. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Application Perspective of 2D+SCALE Dimension

NASA Astrophysics Data System (ADS)

Karim, H.; Rahman, A. Abdul

2016-09-01

Different applications or users need different abstraction of spatial models, dimensionalities and specification of their datasets due to variations of required analysis and output. Various approaches, data models and data structures are now available to support most current application models in Geographic Information System (GIS). One of the focuses trend in GIS multi-dimensional research community is the implementation of scale dimension with spatial datasets to suit various scale application needs. In this paper, 2D spatial datasets that been scaled up as the third dimension are addressed as 2D+scale (or 3D-scale) dimension. Nowadays, various data structures, data models, approaches, schemas, and formats have been proposed as the best approaches to support variety of applications and dimensionality in 3D topology. However, only a few of them considers the element of scale as their targeted dimension. As the scale dimension is concerned, the implementation approach can be either multi-scale or vario-scale (with any available data structures and formats) depending on application requirements (topology, semantic and function). This paper attempts to discuss on the current and new potential applications which positively could be integrated upon 3D-scale dimension approach. The previous and current works on scale dimension as well as the requirements to be preserved for any given applications, implementation issues and future potential applications forms the major discussion of this paper.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

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 microphysics development and its performance for the multi-scale modeling system will be presented.

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 and Object-Oriented Analysis for Mountain Terrain Segmentation and Geomorphological Assessment

NASA Astrophysics Data System (ADS)

Marston, B. K.; Bishop, M. P.; Shroder, J. F.

2009-12-01

Digital terrain analysis of mountain topography is widely utilized for mapping landforms, assessing the role of surface processes in landscape evolution, and estimating the spatial variation of erosion. Numerous geomorphometry techniques exist to characterize terrain surface parameters, although their utility to characterize the spatial hierarchical structure of the topography and permit an assessment of the erosion/tectonic impact on the landscape is very limited due to scale and data integration issues. To address this problem, we apply scale-dependent geomorphometric and object-oriented analyses to characterize the hierarchical spatial structure of mountain topography. Specifically, we utilized a high resolution digital elevation model to characterize complex topography in the Shimshal Valley in the Western Himalaya of Pakistan. To accomplish this, we generate terrain objects (geomorphological features and landform) including valley floors and walls, drainage basins, drainage network, ridge network, slope facets, and elemental forms based upon curvature. Object-oriented analysis was used to characterize object properties accounting for object size, shape, and morphometry. The spatial overlay and integration of terrain objects at various scales defines the nature of the hierarchical organization. Our results indicate that variations in the spatial complexity of the terrain hierarchical organization is related to the spatio-temporal influence of surface processes and landscape evolution dynamics. Terrain segmentation and the integration of multi-scale terrain information permits further assessment of process domains and erosion, tectonic impact potential, and natural hazard potential. We demonstrate this with landform mapping and geomorphological assessment examples.

Multi-scale lung modeling.

PubMed

Tawhai, Merryn H; Bates, Jason H T

2011-05-01

Multi-scale modeling of biological systems has recently become fashionable due to the growing power of digital computers as well as to the growing realization that integrative systems behavior is as important to life as is the genome. While it is true that the behavior of a living organism must ultimately be traceable to all its components and their myriad interactions, attempting to codify this in its entirety in a model misses the insights gained from understanding how collections of system components at one level of scale conspire to produce qualitatively different behavior at higher levels. The essence of multi-scale modeling thus lies not in the inclusion of every conceivable biological detail, but rather in the judicious selection of emergent phenomena appropriate to the level of scale being modeled. These principles are exemplified in recent computational models of the lung. Airways responsiveness, for example, is an organ-level manifestation of events that begin at the molecular level within airway smooth muscle cells, yet it is not necessary to invoke all these molecular events to accurately describe the contraction dynamics of a cell, nor is it necessary to invoke all phenomena observable at the level of the cell to account for the changes in overall lung function that occur following methacholine challenge. Similarly, the regulation of pulmonary vascular tone has complex origins within the individual smooth muscle cells that line the blood vessels but, again, many of the fine details of cell behavior average out at the level of the organ to produce an effect on pulmonary vascular pressure that can be described in much simpler terms. The art of multi-scale lung modeling thus reduces not to being limitlessly inclusive, but rather to knowing what biological details to leave out.

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…

Scale Interactions in the Tropics from a Simple Multi-Cloud Model

NASA Astrophysics Data System (ADS)

Niu, X.; Biello, J. A.

2017-12-01

Our lack of a complete understanding of the interaction between the moisture convection and equatorial waves remains an impediment in the numerical simulation of large-scale organization, such as the Madden-Julian Oscillation (MJO). The aim of this project is to understand interactions across spatial scales in the tropics from a simplified framework for scale interactions while a using a simplified framework to describe the basic features of moist convection. Using multiple asymptotic scales, Biello and Majda[1] derived a multi-scale model of moist tropical dynamics (IMMD[1]), which separates three regimes: the planetary scale climatology, the synoptic scale waves, and the planetary scale anomalies regime. The scales and strength of the observed MJO would categorize it in the regime of planetary scale anomalies - which themselves are forced from non-linear upscale fluxes from the synoptic scales waves. In order to close this model and determine whether it provides a self-consistent theory of the MJO. A model for diabatic heating due to moist convection must be implemented along with the IMMD. The multi-cloud parameterization is a model proposed by Khouider and Majda[2] to describe the three basic cloud types (congestus, deep and stratiform) that are most responsible for tropical diabatic heating. We implement a simplified version of the multi-cloud model that is based on results derived from large eddy simulations of convection [3]. We present this simplified multi-cloud model and show results of numerical experiments beginning with a variety of convective forcing states. Preliminary results on upscale fluxes, from synoptic scales to planetary scale anomalies, will be presented. [1] Biello J A, Majda A J. Intraseasonal multi-scale moist dynamics of the tropical atmosphere[J]. Communications in Mathematical Sciences, 2010, 8(2): 519-540. [2] Khouider B, Majda A J. A simple multicloud parameterization for convectively coupled tropical waves. Part I: Linear analysis

Low Dimensional Study of a Supersonic Multi-Stream Jet Flow

NASA Astrophysics Data System (ADS)

Tenney, Andrew; Berry, Matthew; Aycock-Rizzo, Halley; Glauser, Mark; Lewalle, Jacques

2017-11-01

In this study, the near field of a two stream supersonic jet flow is examined using low dimensional tools. The flow issues from a multi-stream nozzle as described in A near-field investigation of a supersonic, multi-stream jet: locating turbulence mechanisms through velocity and density measurements by Magstadt et al., with the bulk flow Mach number, M1, being 1.6, and the second stream Mach number, M2, reaching the sonic condition. The flow field is visualized using Particle Image Velocimetry (PIV), with frames captured at a rate of 4Hz. Time-resolved pressure measurements are made just aft of the nozzle exit, as well as in the far-field, 86.6 nozzle hydraulic diameters away from the exit plane. The methodologies used in the analysis of this flow include Proper Orthogonal Decomposition (POD), and the continuous wavelet transform. The results from this ``no deck'' case are then compared to those found in the study conducted by Berry et al. From this comparison, we draw conclusions about the effects of the presence of an aft deck on the low dimensional flow description, and near field spectral content. Supported by AFOSR Grant FA9550-15-1-0435, and AFRL, through an SBIR Grant with Spectral Energies, LLC.

Pedagogic discourse in introductory classes: Multi-dimensional analysis of textbooks and lectures in biology and macroeconomics

NASA Astrophysics Data System (ADS)

Carkin, Susan

The broad goal of this study is to represent the linguistic variation of textbooks and lectures, the primary input for student learning---and sometimes the sole input in the large introductory classes which characterize General Education at many state universities. Computer techniques are used to analyze a corpus of textbooks and lectures from first-year university classes in macroeconomics and biology. These spoken and written variants are compared to each other as well as to benchmark texts from other multi-dimensional studies in order to examine their patterns, relations, and functions. A corpus consisting of 147,000 words was created from macroeconomics and biology lectures at a medium-large state university and from a set of nationally "best-selling" textbooks used in these same introductory survey courses. The corpus was analyzed using multi-dimensional methodology (Biber, 1988). The analysis consists of both empirical and qualitative phases. Quantitative analyses are undertaken on the linguistic features, their patterns of co-occurrence, and on the contextual elements of classrooms and textbooks. The contextual analysis is used to functionally interpret the statistical patterns of co-occurrence along five dimensions of textual variation, demonstrating patterns of difference and similarity with reference to text excerpts. Results of the analysis suggest that academic discourse is far from monolithic. Pedagogic discourse in introductory classes varies by modality and discipline, but not always in the directions expected. In the present study the most abstract texts were biology lectures---more abstract than written genres of academic prose and more abstract than introductory textbooks. Academic lectures in both disciplines, monologues which carry a heavy informational load, were extremely interactive, more like conversation than academic prose. A third finding suggests that introductory survey textbooks differ from those used in upper division classes by being

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.

Effective use of metadata in the integration and analysis of multi-dimensional optical data

NASA Astrophysics Data System (ADS)

Pastorello, G. Z.; Gamon, J. A.

2012-12-01

Data discovery and integration relies on adequate metadata. However, creating and maintaining metadata is time consuming and often poorly addressed or avoided altogether, leading to problems in later data analysis and exchange. This is particularly true for research fields in which metadata standards do not yet exist or are under development, or within smaller research groups without enough resources. Vegetation monitoring using in-situ and remote optical sensing is an example of such a domain. In this area, data are inherently multi-dimensional, with spatial, temporal and spectral dimensions usually being well characterized. Other equally important aspects, however, might be inadequately translated into metadata. Examples include equipment specifications and calibrations, field/lab notes and field/lab protocols (e.g., sampling regimen, spectral calibration, atmospheric correction, sensor view angle, illumination angle), data processing choices (e.g., methods for gap filling, filtering and aggregation of data), quality assurance, and documentation of data sources, ownership and licensing. Each of these aspects can be important as metadata for search and discovery, but they can also be used as key data fields in their own right. If each of these aspects is also understood as an "extra dimension," it is possible to take advantage of them to simplify the data acquisition, integration, analysis, visualization and exchange cycle. Simple examples include selecting data sets of interest early in the integration process (e.g., only data collected according to a specific field sampling protocol) or applying appropriate data processing operations to different parts of a data set (e.g., adaptive processing for data collected under different sky conditions). More interesting scenarios involve guided navigation and visualization of data sets based on these extra dimensions, as well as partitioning data sets to highlight relevant subsets to be made available for exchange. The

Detecting Multi-scale Structures in Chandra Images of Centaurus A

NASA Astrophysics Data System (ADS)

Karovska, M.; Fabbiano, G.; Elvis, M. S.; Evans, I. N.; Kim, D. W.; Prestwich, A. H.; Schwartz, D. A.; Murray, S. S.; Forman, W.; Jones, C.; Kraft, R. P.; Isobe, T.; Cui, W.; Schreier, E. J.

1999-12-01

Centaurus A (NGC 5128) is a giant early-type galaxy with a merger history, containing the nearest radio-bright AGN. Recent Chandra High Resolution Camera (HRC) observations of Cen A reveal X-ray multi-scale structures in this object with unprecedented detail and clarity. We show the results of an analysis of the Chandra data with smoothing and edge enhancement techniques that allow us to enhance and quantify the multi-scale structures present in the HRC images. These techniques include an adaptive smoothing algorithm (Ebeling et al 1999), and a multi-directional gradient detection algorithm (Karovska et al 1994). The Ebeling et al adaptive smoothing algorithm, which is incorporated in the CXC analysis s/w package, is a powerful tool for smoothing images containing complex structures at various spatial scales. The adaptively smoothed images of Centaurus A show simultaneously the high-angular resolution bright structures at scales as small as an arcsecond and the extended faint structures as large as several arc minutes. The large scale structures suggest complex symmetry, including a component possibly associated with the inner radio lobes (as suggested by the ROSAT HRI data, Dobereiner et al 1996), and a separate component with an orthogonal symmetry that may be associated with the galaxy as a whole. The dust lane and the x-ray ridges are very clearly visible. The adaptively smoothed images and the edge-enhanced images also suggest several filamentary features including a large filament-like structure extending as far as about 5 arcminutes to North-West.

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.

Multi-scale biomedical systems: measurement challenges

NASA Astrophysics Data System (ADS)

Summers, R.

2016-11-01

Multi-scale biomedical systems are those that represent interactions in materials, sensors, and systems from a holistic perspective. It is possible to view such multi-scale activity using measurement of spatial scale or time scale, though in this paper only the former is considered. The biomedical application paradigm comprises interactions that range from quantum biological phenomena at scales of 10-12 for one individual to epidemiological studies of disease spread in populations that in a pandemic lead to measurement at a scale of 10+7. It is clear that there are measurement challenges at either end of this spatial scale, but those challenges that relate to the use of new technologies that deal with big data and health service delivery at the point of care are also considered. The measurement challenges lead to the use, in many cases, of model-based measurement and the adoption of virtual engineering. It is these measurement challenges that will be uncovered in this paper.

Automatic analysis of diabetic peripheral neuropathy using multi-scale quantitative morphology of nerve fibres in corneal confocal microscopy imaging.

PubMed

Dabbah, M A; Graham, J; Petropoulos, I N; Tavakoli, M; Malik, R A

2011-10-01

Diabetic peripheral neuropathy (DPN) is one of the most common long term complications of diabetes. Corneal confocal microscopy (CCM) image analysis is a novel non-invasive technique which quantifies corneal nerve fibre damage and enables diagnosis of DPN. This paper presents an automatic analysis and classification system for detecting nerve fibres in CCM images based on a multi-scale adaptive dual-model detection algorithm. The algorithm exploits the curvilinear structure of the nerve fibres and adapts itself to the local image information. Detected nerve fibres are then quantified and used as feature vectors for classification using random forest (RF) and neural networks (NNT) classifiers. We show, in a comparative study with other well known curvilinear detectors, that the best performance is achieved by the multi-scale dual model in conjunction with the NNT classifier. An evaluation of clinical effectiveness shows that the performance of the automated system matches that of ground-truth defined by expert manual annotation. Copyright © 2011 Elsevier B.V. All rights reserved.

2D deblending using the multi-scale shaping scheme

NASA Astrophysics Data System (ADS)

Li, Qun; Ban, Xingan; Gong, Renbin; Li, Jinnuo; Ge, Qiang; Zu, Shaohuan

2018-01-01

Deblending can be posed as an inversion problem, which is ill-posed and requires constraint to obtain unique and stable solution. In blended record, signal is coherent, whereas interference is incoherent in some domains (e.g., common receiver domain and common offset domain). Due to the different sparsity, coefficients of signal and interference locate in different curvelet scale domains and have different amplitudes. Take into account the two differences, we propose a 2D multi-scale shaping scheme to constrain the sparsity to separate the blended record. In the domain where signal concentrates, the multi-scale scheme passes all the coefficients representing signal, while, in the domain where interference focuses, the multi-scale scheme suppresses the coefficients representing interference. Because the interference is suppressed evidently at each iteration, the constraint of multi-scale shaping operator in all scale domains are weak to guarantee the convergence of algorithm. We evaluate the performance of the multi-scale shaping scheme and the traditional global shaping scheme by using two synthetic and one field data examples.

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.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Multi-Scale Scattering Transform in Music Similarity Measuring

NASA Astrophysics Data System (ADS)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

Control of Thermo-Acoustics Instabilities: The Multi-Scale Extended Kalman Approach

NASA Technical Reports Server (NTRS)

Le, Dzu K.; DeLaat, John C.; Chang, Clarence T.

2003-01-01

"Multi-Scale Extended Kalman" (MSEK) is a novel model-based control approach recently found to be effective for suppressing combustion instabilities in gas turbines. A control law formulated in this approach for fuel modulation demonstrated steady suppression of a high-frequency combustion instability (less than 500Hz) in a liquid-fuel combustion test rig under engine-realistic conditions. To make-up for severe transport-delays on control effect, the MSEK controller combines a wavelet -like Multi-Scale analysis and an Extended Kalman Observer to predict the thermo-acoustic states of combustion pressure perturbations. The commanded fuel modulation is composed of a damper action based on the predicted states, and a tones suppression action based on the Multi-Scale estimation of thermal excitations and other transient disturbances. The controller performs automatic adjustments of the gain and phase of these actions to minimize the Time-Scale Averaged Variances of the pressures inside the combustion zone and upstream of the injector. The successful demonstration of Active Combustion Control with this MSEK controller completed an important NASA milestone for the current research in advanced combustion technologies.

Multi-Scale Infrastructure Assessment

EPA Science Inventory

The U.S. Environmental Protection Agency’s (EPA) multi-scale infrastructure assessment project supports both water resource adaptation to climate change and the rehabilitation of the nation’s aging water infrastructure by providing tools, scientific data and information to progra...

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.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition

Alternative transitions between existing representations in multi-scale maps

NASA Astrophysics Data System (ADS)

Dumont, Marion; Touya, Guillaume; Duchêne, Cécile

2018-05-01

Map users may have issues to achieve multi-scale navigation tasks, as cartographic objects may have various representations across scales. We assume that adding intermediate representations could be one way to reduce the differences between existing representations, and to ease the transitions across scales. We consider an existing multiscale map on the scale range from 1 : 25k to 1 : 100k scales. Based on hypotheses about intermediate representations design, we build custom multi-scale maps with alternative transitions. We will conduct in a next future a user evaluation to compare the efficiency of these alternative maps for multi-scale navigation. This paper discusses the hypotheses and production process of these alternative maps.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

A Multi-Scale, Multi-Physics Optimization Framework for Additively Manufactured Structural Components

NASA Astrophysics Data System (ADS)

El-Wardany, Tahany; Lynch, Mathew; Gu, Wenjiong; Hsu, Arthur; Klecka, Michael; Nardi, Aaron; Viens, Daniel

This paper proposes an optimization framework enabling the integration of multi-scale / multi-physics simulation codes to perform structural optimization design for additively manufactured components. Cold spray was selected as the additive manufacturing (AM) process and its constraints were identified and included in the optimization scheme. The developed framework first utilizes topology optimization to maximize stiffness for conceptual design. The subsequent step applies shape optimization to refine the design for stress-life fatigue. The component weight was reduced by 20% while stresses were reduced by 75% and the rigidity was improved by 37%. The framework and analysis codes were implemented using Altair software as well as an in-house loading code. The optimized design was subsequently produced by the cold spray process.

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

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.

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.

Diagnosing Disaster Resilience of Communities as Multi-scale Complex Socio-ecological Systems

NASA Astrophysics Data System (ADS)

Liu, Wei; Mochizuki, Junko; Keating, Adriana; Mechler, Reinhard; Williges, Keith; Hochrainer, Stefan

2014-05-01

Global environmental change, growing anthropogenic influence, and increasing globalisation of society have made it clear that disaster vulnerability and resilience of communities cannot be understood without knowledge on the broader social-ecological system in which they are embedded. We propose a framework for diagnosing community resilience to disasters, as a form of disturbance to social-ecological systems, with feedbacks from the local to the global scale. Inspired by iterative multi-scale analysis employed by Resilience Alliance, the related socio-ecological systems framework of Ostrom, and the sustainable livelihood framework, we developed a multi-tier framework for thinking of communities as multi-scale social-ecological systems and analyzing communities' disaster resilience and also general resilience. We highlight the cross-scale influences and feedbacks on communities that exist from lower (e.g., household) to higher (e.g., regional, national) scales. The conceptual framework is then applied to a real-world resilience assessment situation, to illustrate how key components of socio-ecological systems, including natural hazards, natural and man-made environment, and community capacities can be delineated and analyzed.

Development and validation of the Work Conflict Appraisal Scale (WCAS).

PubMed

González-Navarro, Pilar; Llinares-Insa, Lucía; Zurriaga-Llorens, Rosario; Lloret-Segura, Susana

2017-05-01

In the context of cognitive appraisal, the Work Conflict Appraisal Scale (WCAS) was developed to assess work conflict in terms of threat and challenge. In the first study, the factorial structure of the scale was tested using confirmatory factor analysis with a Spanish multi-occupational employee sample (N= 296). In the sec-ond study, we used multi-sampling confirmatory factor analysis (N= 815) to cross-validate the results. The analyses confirm the validity of the scale and are con-sistent with the tri-dimensional conflict classification. The findings support the distinc-tion between the challenge and threat appraisals of work conflict, highlighting the im-portance of measuring these two types of appraisal separately. This scale is a valid and reliable instrument to measure conflict appraisal in organizations.

A Multi-Resolution Data Structure for Two-Dimensional Morse Functions

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

Bremer, P-T; Edelsbrunner, H; Hamann, B

2003-07-30

The efficient construction of simplified models is a central problem in the field of visualization. We combine topological and geometric methods to construct a multi-resolution data structure for functions over two-dimensional domains. Starting with the Morse-Smale complex we build a hierarchy by progressively canceling critical points in pairs. The data structure supports mesh traversal operations similar to traditional multi-resolution representations.

A multi-scale model for geared transmission aero-thermodynamics

NASA Astrophysics Data System (ADS)

McIntyre, Sean M.

A multi-scale, multi-physics computational tool for the simulation of high-per- formance gearbox aero-thermodynamics was developed and applied to equilibrium and pathological loss-of-lubrication performance simulation. The physical processes at play in these systems include multiphase compressible ow of the air and lubricant within the gearbox, meshing kinematics and tribology, as well as heat transfer by conduction, and free and forced convection. These physics are coupled across their representative space and time scales in the computational framework developed in this dissertation. These scales span eight orders of magnitude, from the thermal response of the full gearbox O(100 m; 10 2 s), through effects at the tooth passage time scale O(10-2 m; 10-4 s), down to tribological effects on the meshing gear teeth O(10-6 m; 10-6 s). Direct numerical simulation of these coupled physics and scales is intractable. Accordingly, a scale-segregated simulation strategy was developed by partitioning and treating the contributing physical mechanisms as sub-problems, each with associated space and time scales, and appropriate coupling mechanisms. These are: (1) the long time scale thermal response of the system, (2) the multiphase (air, droplets, and film) aerodynamic flow and convective heat transfer within the gearbox, (3) the high-frequency, time-periodic thermal effects of gear tooth heating while in mesh and its subsequent cooling through the rest of rotation, (4) meshing effects including tribology and contact mechanics. The overarching goal of this dissertation was to develop software and analysis procedures for gearbox loss-of-lubrication performance. To accommodate these four physical effects and their coupling, each is treated in the CFD code as a sub problem. These physics modules are coupled algorithmically. Specifically, the high- frequency conduction analysis derives its local heat transfer coefficient and near-wall air temperature boundary conditions from a quasi

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

Cross-scale interactions: Quantifying multi-scaled cause–effect relationships in macrosystems

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra S.; Bissell, Edward G.; Bremigan, Mary T.; Downing, John A.; Fergus, Carol E.; Filstrup, Christopher T.; Henry, Emily N.; Lottig, Noah R.; Stanley, Emily H.; Stow, Craig A.; Tan, Pang-Ning; Wagner, Tyler; Webster, Katherine E.

2014-01-01

Ecologists are increasingly discovering that ecological processes are made up of components that are multi-scaled in space and time. Some of the most complex of these processes are cross-scale interactions (CSIs), which occur when components interact across scales. When undetected, such interactions may cause errors in extrapolation from one region to another. CSIs, particularly those that include a regional scaled component, have not been systematically investigated or even reported because of the challenges of acquiring data at sufficiently broad spatial extents. We present an approach for quantifying CSIs and apply it to a case study investigating one such interaction, between local and regional scaled land-use drivers of lake phosphorus. Ultimately, our approach for investigating CSIs can serve as a basis for efforts to understand a wide variety of multi-scaled problems such as climate change, land-use/land-cover change, and invasive species.

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.

Three dimensional fabrication at small size scales

PubMed Central

Leong, Timothy G.; Zarafshar, Aasiyeh M.; Gracias, David H.

2010-01-01

Despite the fact that we live in a three-dimensional (3D) world and macroscale engineering is 3D, conventional sub-mm scale engineering is inherently two-dimensional (2D). New fabrication and patterning strategies are needed to enable truly three-dimensionally-engineered structures at small size scales. Here, we review strategies that have been developed over the last two decades that seek to enable such millimeter to nanoscale 3D fabrication and patterning. A focus of this review is the strategy of self-assembly, specifically in a biologically inspired, more deterministic form known as self-folding. Self-folding methods can leverage the strengths of lithography to enable the construction of precisely patterned 3D structures and “smart” components. This self-assembling approach is compared with other 3D fabrication paradigms, and its advantages and disadvantages are discussed. PMID:20349446

Multi-Scale Computational Modeling of Two-Phased Metal Using GMC Method

NASA Technical Reports Server (NTRS)

Moghaddam, Masoud Ghorbani; Achuthan, A.; Bednacyk, B. A.; Arnold, S. M.; Pineda, E. J.

2014-01-01

A multi-scale computational model for determining plastic behavior in two-phased CMSX-4 Ni-based superalloys is developed on a finite element analysis (FEA) framework employing crystal plasticity constitutive model that can capture the microstructural scale stress field. The generalized method of cells (GMC) micromechanics model is used for homogenizing the local field quantities. At first, GMC as stand-alone is validated by analyzing a repeating unit cell (RUC) as a two-phased sample with 72.9% volume fraction of gamma'-precipitate in the gamma-matrix phase and comparing the results with those predicted by finite element analysis (FEA) models incorporating the same crystal plasticity constitutive model. The global stress-strain behavior and the local field quantity distributions predicted by GMC demonstrated good agreement with FEA. High computational saving, at the expense of some accuracy in the components of local tensor field quantities, was obtained with GMC. Finally, the capability of the developed multi-scale model linking FEA and GMC to solve real life sized structures is demonstrated by analyzing an engine disc component and determining the microstructural scale details of the field quantities.

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.

Perceptions of Learning Effectiveness in M-Learning: Scale Development and Student Awareness

ERIC Educational Resources Information Center

Chang, Wen-Hui; Liu, Yuan-Chen; Huang, Tzu-Hua

2017-01-01

The purpose of this study is to develop a multi-dimensional scale to measure students' awareness of key competencies for M-learning and to test its reliability and validity. The Key Competencies of Mobile Learning Scale (KCMLS) was determined via confirmatory factor analysis to have four dimensions: team collaboration, creative thinking, critical…

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.

A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

PubMed Central

2011-01-01

Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191

Perceptual suppression revealed by adaptive multi-scale entropy analysis of local field potential in monkey visual cortex.

PubMed

Hu, Meng; Liang, Hualou

2013-04-01

Generalized flash suppression (GFS), in which a salient visual stimulus can be rendered invisible despite continuous retinal input, provides a rare opportunity to directly study the neural mechanism of visual perception. Previous work based on linear methods, such as spectral analysis, on local field potential (LFP) during GFS has shown that the LFP power at distinctive frequency bands are differentially modulated by perceptual suppression. Yet, the linear method alone may be insufficient for the full assessment of neural dynamic due to the fundamentally nonlinear nature of neural signals. In this study, we set forth to analyze the LFP data collected from multiple visual areas in V1, V2 and V4 of macaque monkeys while performing the GFS task using a nonlinear method - adaptive multi-scale entropy (AME) - to reveal the neural dynamic of perceptual suppression. In addition, we propose a new cross-entropy measure at multiple scales, namely adaptive multi-scale cross-entropy (AMCE), to assess the nonlinear functional connectivity between two cortical areas. We show that: (1) multi-scale entropy exhibits percept-related changes in all three areas, with higher entropy observed during perceptual suppression; (2) the magnitude of the perception-related entropy changes increases systematically over successive hierarchical stages (i.e. from lower areas V1 to V2, up to higher area V4); and (3) cross-entropy between any two cortical areas reveals higher degree of asynchrony or dissimilarity during perceptual suppression, indicating a decreased functional connectivity between cortical areas. These results, taken together, suggest that perceptual suppression is related to a reduced functional connectivity and increased uncertainty of neural responses, and the modulation of perceptual suppression is more effective at higher visual cortical areas. AME is demonstrated to be a useful technique in revealing the underlying dynamic of nonlinear/nonstationary neural signal.

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)

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.

Three-dimensional Aerodynamic Instability in Multi-stage Axial Compressors

NASA Technical Reports Server (NTRS)

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

2003-01-01

Four separate tasks are reported. The first task: A Computational Model for Short Wavelength Stall Inception and Development In Multi-Stage Compressors; the second task: Three-dimensional Rotating Stall Inception and Effects of Rotating Tip Clearance Asymmetry in Axial Compressors; the third task:Development of an Effective Computational Methodology for Body Force Representation of High-speed Rotor 37; and the fourth task:Development of Circumferential Inlet Distortion through a Representative Eleven Stage High-speed axial compressor. The common theme that threaded throughout these four tasks is the conceptual framework that consists of quantifying flow processes at the fadcompressor blade passage level to define the compressor performance characteristics needed for addressing physical phenomena such compressor aerodynamic instability and compressor response to flow distoriton with length scales larger than compressor blade-to-blade spacing at the system level. The results from these two levels can be synthesized to: (1) simulate compressor aerodynamic instability inception local to a blade rotor tip and its development from a local flow event into the nonlinear limit cycle instability that involves the entire compressor as was demonstrated in the first task; (2) determine the conditions under which compressor stability assessment based on two-dimensional model may not be adequate and the effects of self-induced flow distortion on compressor stability limit as in the second task; (3) quantify multistage compressor response to inlet distortion in stagnation pressure as illustrated in the fourth task; and (4) elucidate its potential applicability for compressor map generation under uniform as well as non-uniform inlet flow given three-dimensional Navier-Stokes solution for each individual blade row as was demonstrated in the third task.

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.

Multi-perspective views of students’ difficulties with one-dimensional vector and two-dimensional vector

NASA Astrophysics Data System (ADS)

Fauzi, Ahmad; Ratna Kawuri, Kunthi; Pratiwi, Retno

2017-01-01

Researchers of students’ conceptual change usually collects data from written tests and interviews. Moreover, reports of conceptual change often simply refer to changes in concepts, such as on a test, without any identification of the learning processes that have taken place. Research has shown that students have difficulties with vectors in university introductory physics courses and high school physics courses. In this study, we intended to explore students’ understanding of one-dimensional and two-dimensional vector in multi perspective views. In this research, we explore students’ understanding through test perspective and interviews perspective. Our research study adopted the mixed-methodology design. The participants of this research were sixty students of third semester of physics education department. The data of this research were collected by testand interviews. In this study, we divided the students’ understanding of one-dimensional vector and two-dimensional vector in two categories, namely vector skills of the addition of one-dimensionaland two-dimensional vector and the relation between vector skills and conceptual understanding. From the investigation, only 44% of students provided correct answer for vector skills of the addition of one-dimensional and two-dimensional vector and only 27% students provided correct answer for the relation between vector skills and conceptual understanding.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Gu, Guojun; Nelkin, Eric J.; Bowman, Kenneth P.; Stocker, Erich; Wolff, David B.

2006-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

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.

High-frequency stock linkage and multi-dimensional stationary processes

NASA Astrophysics Data System (ADS)

Wang, Xi; Bao, Si; Chen, Jingchao

2017-02-01

In recent years, China's stock market has experienced dramatic fluctuations; in particular, in the second half of 2014 and 2015, the market rose sharply and fell quickly. Many classical financial phenomena, such as stock plate linkage, appeared repeatedly during this period. In general, these phenomena have usually been studied using daily-level data or minute-level data. Our paper focuses on the linkage phenomenon in Chinese stock 5-second-level data during this extremely volatile period. The method used to select the linkage points and the arbitrage strategy are both based on multi-dimensional stationary processes. A new program method for testing the multi-dimensional stationary process is proposed in our paper, and the detailed program is presented in the paper's appendix. Because of the existence of the stationary process, the strategy's logarithmic cumulative average return will converge under the condition of the strong ergodic theorem, and this ensures the effectiveness of the stocks' linkage points and the more stable statistical arbitrage strategy.

The forced vibration of one-dimensional multi-coupled periodic structures: An application to finite element analysis

NASA Astrophysics Data System (ADS)

Mead, Denys J.

2009-01-01

A general theory for the forced vibration of multi-coupled one-dimensional periodic structures is presented as a sequel to a much earlier general theory for free vibration. Starting from the dynamic stiffness matrix of a single multi-coupled periodic element, it derives matrix equations for the magnitudes of the characteristic free waves excited in the whole structure by prescribed harmonic forces and/or displacements acting at a single periodic junction. The semi-infinite periodic system excited at its end is first analysed to provide the basis for analysing doubly infinite and finite periodic systems. In each case, total responses are found by considering just one periodic element. An already-known method of reducing the size of the computational problem is reexamined, expanded and extended in detail, involving reduction of the dynamic stiffness matrix of the periodic element through a wave-coordinate transformation. Use of the theory is illustrated in a combined periodic structure+finite element analysis of the forced harmonic in-plane motion of a uniform flat plate. Excellent agreement between the computed low-frequency responses and those predicted by simple engineering theories validates the detailed formulations of the paper. The primary purpose of the paper is not towards a specific application but to present a systematic and coherent forced vibration theory, carefully linked with the existing free-wave theory.

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 multi-machine scaling of halo current rotation

NASA Astrophysics Data System (ADS)

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; Gerhardt, S. P.; Granetz, R. S.; Hender, T. C.; Pautasso, G.; Contributors, JET

2018-01-01

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: (1) the machine-specific minimum current quench time, \

A multi-machine scaling of halo current rotation

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

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

A multi-machine scaling of halo current rotation

DOE PAGES

Myers, C. E.; Eidietis, N. W.; Gerasimov, S. N.; ...

2017-12-12

Halo currents generated during unmitigated tokamak disruptions are known to develop rotating asymmetric features that are of great concern to ITER because they can dynamically amplify the mechanical stresses on the machine. This paper presents a multi-machine analysis of these phenomena. More specifically, data from C-Mod, NSTX, ASDEX Upgrade, DIII-D, and JET are used to develop empirical scalings of three key quantities: the machine-specific minimum current quench time,more » $$ \

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-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.

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study

PubMed Central

Vickers, T. Winston; Ernest, Holly B.; Boyce, Walter M.

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in

Multi-level, multi-scale resource selection functions and resistance surfaces for conservation planning: Pumas as a case study.

PubMed

Zeller, Katherine A; Vickers, T Winston; Ernest, Holly B; Boyce, Walter M

2017-01-01

The importance of examining multiple hierarchical levels when modeling resource use for wildlife has been acknowledged for decades. Multi-level resource selection functions have recently been promoted as a method to synthesize resource use across nested organizational levels into a single predictive surface. Analyzing multiple scales of selection within each hierarchical level further strengthens multi-level resource selection functions. We extend this multi-level, multi-scale framework to modeling resistance for wildlife by combining multi-scale resistance surfaces from two data types, genetic and movement. Resistance estimation has typically been conducted with one of these data types, or compared between the two. However, we contend it is not an either/or issue and that resistance may be better-modeled using a combination of resistance surfaces that represent processes at different hierarchical levels. Resistance surfaces estimated from genetic data characterize temporally broad-scale dispersal and successful breeding over generations, whereas resistance surfaces estimated from movement data represent fine-scale travel and contextualized movement decisions. We used telemetry and genetic data from a long-term study on pumas (Puma concolor) in a highly developed landscape in southern California to develop a multi-level, multi-scale resource selection function and a multi-level, multi-scale resistance surface. We used these multi-level, multi-scale surfaces to identify resource use patches and resistant kernel corridors. Across levels, we found puma avoided urban, agricultural areas, and roads and preferred riparian areas and more rugged terrain. For other landscape features, selection differed among levels, as did the scales of selection for each feature. With these results, we developed a conservation plan for one of the most isolated puma populations in the U.S. Our approach captured a wide spectrum of ecological relationships for a population, resulted in

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.

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.

Wearable Wireless Sensor for Multi-Scale Physiological Monitoring

DTIC Science & Technology

2013-10-01

AD_________________ Award Number: W81XWH-12-1-0541 TITLE: Wearable Wireless Sensor for Multi-Scale...TYPE Annual 3. DATES COVERED 25 12- 13 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Wearable Wireless Sensor for Multi-Scale Physiological...peripheral management • Procedures for low power mode activation and wake - up • Routines for start- up state detection • Flash memory management

n-SIFT: n-dimensional scale invariant feature transform.

PubMed

Cheung, Warren; Hamarneh, Ghassan

2009-09-01

We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for extracting and matching distinctive scale invariant features. We apply the features to images of arbitrary dimensionality through the use of hyperspherical coordinates for gradients and multidimensional histograms to create the feature vectors. We analyze the performance of a fully automated multimodal medical image matching technique based on these features, and successfully apply the technique to determine accurate feature point correspondence between pairs of 3-D MRI images and dynamic 3D + time CT data.

The Multi-dimensional Character of Core-collapse Supernovae

DOE PAGES

Hix, W. R.; Lentz, E. J.; Bruenn, S. W.; ...

2016-03-01

Core-collapse supernovae, the culmination of massive stellar evolution, are spectacular astronomical events and the principle actors in the story of our elemental origins. Our understanding of these events, while still incomplete, centers around a neutrino-driven central engine that is highly hydrodynamically unstable. Increasingly sophisticated simulations reveal a shock that stalls for hundreds of milliseconds before reviving. Though brought back to life by neutrino heating, the development of the supernova explosion is inextricably linked to multi-dimensional fluid flows. In this paper, the outcomes of three-dimensional simulations that include sophisticated nuclear physics and spectral neutrino transport are juxtaposed to learn about themore » nature of the three-dimensional fluid flow that shapes the explosion. Comparison is also made between the results of simulations in spherical symmetry from several groups, to give ourselves confidence in the understanding derived from this juxtaposition.« less

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.

Reliability of Multi-Category Rating Scales

ERIC Educational Resources Information Center

Parker, Richard I.; Vannest, Kimberly J.; Davis, John L.

2013-01-01

The use of multi-category scales is increasing for the monitoring of IEP goals, classroom and school rules, and Behavior Improvement Plans (BIPs). Although they require greater inference than traditional data counting, little is known about the inter-rater reliability of these scales. This simulation study examined the performance of nine…

Multi-scale pixel-based image fusion using multivariate empirical mode decomposition.

PubMed

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P; McDonald-Maier, Klaus D

2015-05-08

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences.

Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition

PubMed Central

Rehman, Naveed ur; Ehsan, Shoaib; Abdullah, Syed Muhammad Umer; Akhtar, Muhammad Jehanzaib; Mandic, Danilo P.; McDonald-Maier, Klaus D.

2015-01-01

A novel scheme to perform the fusion of multiple images using the multivariate empirical mode decomposition (MEMD) algorithm is proposed. Standard multi-scale fusion techniques make a priori assumptions regarding input data, whereas standard univariate empirical mode decomposition (EMD)-based fusion techniques suffer from inherent mode mixing and mode misalignment issues, characterized respectively by either a single intrinsic mode function (IMF) containing multiple scales or the same indexed IMFs corresponding to multiple input images carrying different frequency information. We show that MEMD overcomes these problems by being fully data adaptive and by aligning common frequency scales from multiple channels, thus enabling their comparison at a pixel level and subsequent fusion at multiple data scales. We then demonstrate the potential of the proposed scheme on a large dataset of real-world multi-exposure and multi-focus images and compare the results against those obtained from standard fusion algorithms, including the principal component analysis (PCA), discrete wavelet transform (DWT) and non-subsampled contourlet transform (NCT). A variety of image fusion quality measures are employed for the objective evaluation of the proposed method. We also report the results of a hypothesis testing approach on our large image dataset to identify statistically-significant performance differences. PMID:26007714

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

The three-dimensional Multi-Block Advanced Grid Generation System (3DMAGGS)

NASA Technical Reports Server (NTRS)

Alter, Stephen J.; Weilmuenster, Kenneth J.

1993-01-01

As the size and complexity of three dimensional volume grids increases, there is a growing need for fast and efficient 3D volumetric elliptic grid solvers. Present day solvers are limited by computational speed and do not have all the capabilities such as interior volume grid clustering control, viscous grid clustering at the wall of a configuration, truncation error limiters, and convergence optimization residing in one code. A new volume grid generator, 3DMAGGS (Three-Dimensional Multi-Block Advanced Grid Generation System), which is based on the 3DGRAPE code, has evolved to meet these needs. This is a manual for the usage of 3DMAGGS and contains five sections, including the motivations and usage, a GRIDGEN interface, a grid quality analysis tool, a sample case for verifying correct operation of the code, and a comparison to both 3DGRAPE and GRIDGEN3D. Since it was derived from 3DGRAPE, this technical memorandum should be used in conjunction with the 3DGRAPE manual (NASA TM-102224).

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

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

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.

A multi-resolution analysis of lidar-DTMs to identify geomorphic processes from characteristic topographic length scales

NASA Astrophysics Data System (ADS)

Sangireddy, H.; Passalacqua, P.; Stark, C. P.

2013-12-01

Characteristic length scales are often present in topography, and they reflect the driving geomorphic processes. The wide availability of high resolution lidar Digital Terrain Models (DTMs) allows us to measure such characteristic scales, but new methods of topographic analysis are needed in order to do so. Here, we explore how transitions in probability distributions (pdfs) of topographic variables such as (log(area/slope)), defined as topoindex by Beven and Kirkby[1979], can be measured by Multi-Resolution Analysis (MRA) of lidar DTMs [Stark and Stark, 2001; Sangireddy et al.,2012] and used to infer dominant geomorphic processes such as non-linear diffusion and critical shear. We show this correlation between dominant geomorphic processes to characteristic length scales by comparing results from a landscape evolution model to natural landscapes. The landscape evolution model MARSSIM Howard[1994] includes components for modeling rock weathering, mass wasting by non-linear creep, detachment-limited channel erosion, and bedload sediment transport. We use MARSSIM to simulate steady state landscapes for a range of hillslope diffusivity and critical shear stresses. Using the MRA approach, we estimate modal values and inter-quartile ranges of slope, curvature, and topoindex as a function of resolution. We also construct pdfs at each resolution and identify and extract characteristic scale breaks. Following the approach of Tucker et al.,[2001], we measure the average length to channel from ridges, within the GeoNet framework developed by Passalacqua et al.,[2010] and compute pdfs for hillslope lengths at each scale defined in the MRA. We compare the hillslope diffusivity used in MARSSIM against inter-quartile ranges of topoindex and hillslope length scales, and observe power law relationships between the compared variables for simulated landscapes at steady state. We plot similar measures for natural landscapes and are able to qualitatively infer the dominant geomorphic

Multi-Dimensional Calibration of Impact Dynamic Models

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Annett, Martin S.; Jackson, Karen E.

2011-01-01

NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.

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

Blood Flow: Multi-scale Modeling and Visualization (July 2011)

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

None

2011-01-01

Multi-scale modeling of arterial blood flow can shed light on the interaction between events happening at micro- and meso-scales (i.e., adhesion of red blood cells to the arterial wall, clot formation) and at macro-scales (i.e., change in flow patterns due to the clot). Coupled numerical simulations of such multi-scale flow require state-of-the-art computers and algorithms, along with techniques for multi-scale visualizations. This animation presents early results of two studies used in the development of a multi-scale visualization methodology. The fisrt illustrates a flow of healthy (red) and diseased (blue) blood cells with a Dissipative Particle Dynamics (DPD) method. Each bloodmore » cell is represented by a mesh, small spheres show a sub-set of particles representing the blood plasma, while instantaneous streamlines and slices represent the ensemble average velocity. In the second we investigate the process of thrombus (blood clot) formation, which may be responsible for the rupture of aneurysms, by concentrating on the platelet blood cells, observing as they aggregate on the wall of an aneruysm. Simulation was performed on Kraken at the National Institute for Computational Sciences. Visualization was produced using resources of the Argonne Leadership Computing Facility at Argonne National Laboratory.« less

Single-scale renormalisation group improvement of multi-scale effective potentials

NASA Astrophysics Data System (ADS)

Chataignier, Leonardo; Prokopec, Tomislav; Schmidt, Michael G.; Świeżewska, Bogumiła

2018-03-01

We present a new method for renormalisation group improvement of the effective potential of a quantum field theory with an arbitrary number of scalar fields. The method amounts to solving the renormalisation group equation for the effective potential with the boundary conditions chosen on the hypersurface where quantum corrections vanish. This hypersurface is defined through a suitable choice of a field-dependent value for the renormalisation scale. The method can be applied to any order in perturbation theory and it is a generalisation of the standard procedure valid for the one-field case. In our method, however, the choice of the renormalisation scale does not eliminate individual logarithmic terms but rather the entire loop corrections to the effective potential. It allows us to evaluate the improved effective potential for arbitrary values of the scalar fields using the tree-level potential with running coupling constants as long as they remain perturbative. This opens the possibility of studying various applications which require an analysis of multi-field effective potentials across different energy scales. In particular, the issue of stability of the scalar potential can be easily studied beyond tree level.

Multi-Scale Computational Models for Electrical Brain Stimulation

PubMed Central

Seo, Hyeon; Jun, Sung C.

2017-01-01

Electrical brain stimulation (EBS) is an appealing method to treat neurological disorders. To achieve optimal stimulation effects and a better understanding of the underlying brain mechanisms, neuroscientists have proposed computational modeling studies for a decade. Recently, multi-scale models that combine a volume conductor head model and multi-compartmental models of cortical neurons have been developed to predict stimulation effects on the macroscopic and microscopic levels more precisely. As the need for better computational models continues to increase, we overview here recent multi-scale modeling studies; we focused on approaches that coupled a simplified or high-resolution volume conductor head model and multi-compartmental models of cortical neurons, and constructed realistic fiber models using diffusion tensor imaging (DTI). Further implications for achieving better precision in estimating cellular responses are discussed. PMID:29123476

Multi-scale Modeling of Plasticity in Tantalum.

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

Lim, Hojun; Battaile, Corbett Chandler.; Carroll, Jay

In this report, we present a multi-scale computational model to simulate plastic deformation of tantalum and validating experiments. In atomistic/ dislocation level, dislocation kink- pair theory is used to formulate temperature and strain rate dependent constitutive equations. The kink-pair theory is calibrated to available data from single crystal experiments to produce accurate and convenient constitutive laws. The model is then implemented into a BCC crystal plasticity finite element method (CP-FEM) model to predict temperature and strain rate dependent yield stresses of single and polycrystalline tantalum and compared with existing experimental data from the literature. Furthermore, classical continuum constitutive models describingmore » temperature and strain rate dependent flow behaviors are fit to the yield stresses obtained from the CP-FEM polycrystal predictions. The model is then used to conduct hydro- dynamic simulations of Taylor cylinder impact test and compared with experiments. In order to validate the proposed tantalum CP-FEM model with experiments, we introduce a method for quantitative comparison of CP-FEM models with various experimental techniques. To mitigate the effects of unknown subsurface microstructure, tantalum tensile specimens with a pseudo-two-dimensional grain structure and grain sizes on the order of millimeters are used. A technique combining an electron back scatter diffraction (EBSD) and high resolution digital image correlation (HR-DIC) is used to measure the texture and sub-grain strain fields upon uniaxial tensile loading at various applied strains. Deformed specimens are also analyzed with optical profilometry measurements to obtain out-of- plane strain fields. These high resolution measurements are directly compared with large-scale CP-FEM predictions. This computational method directly links fundamental dislocation physics to plastic deformations in the grain-scale and to the engineering-scale applications. Furthermore

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 .

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

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.

Generalizing DTW to the multi-dimensional case requires an adaptive approach

PubMed Central

Hu, Bing; Jin, Hongxia; Wang, Jun; Keogh, Eamonn

2017-01-01

In recent years Dynamic Time Warping (DTW) has emerged as the distance measure of choice for virtually all time series data mining applications. For example, virtually all applications that process data from wearable devices use DTW as a core sub-routine. This is the result of significant progress in improving DTW’s efficiency, together with multiple empirical studies showing that DTW-based classifiers at least equal (and generally surpass) the accuracy of all their rivals across dozens of datasets. Thus far, most of the research has considered only the one-dimensional case, with practitioners generalizing to the multi-dimensional case in one of two ways, dependent or independent warping. In general, it appears the community believes either that the two ways are equivalent, or that the choice is irrelevant. In this work, we show that this is not the case. The two most commonly used multi-dimensional DTW methods can produce different classifications, and neither one dominates over the other. This seems to suggest that one should learn the best method for a particular application. However, we will show that this is not necessary; a simple, principled rule can be used on a case-by-case basis to predict which of the two methods we should trust at the time of classification. Our method allows us to ensure that classification results are at least as accurate as the better of the two rival methods, and, in many cases, our method is significantly more accurate. We demonstrate our ideas with the most extensive set of multi-dimensional time series classification experiments ever attempted. PMID:29104448

Rasch analysis of the Italian Lower Extremity Functional Scale: insights on dimensionality and suggestions for an improved 15-item version.

PubMed

Bravini, Elisabetta; Giordano, Andrea; Sartorio, Francesco; Ferriero, Giorgio; Vercelli, Stefano

2017-04-01

To investigate dimensionality and the measurement properties of the Italian Lower Extremity Functional Scale using both classical test theory and Rasch analysis methods, and to provide insights for an improved version of the questionnaire. Rasch analysis of individual patient data. Rehabilitation centre. A total of 135 patients with musculoskeletal diseases of the lower limb. Patients were assessed with the Lower Extremity Functional Scale before and after the rehabilitation. Rasch analysis showed some problems related to rating scale category functioning, items fit, and items redundancy. After an iterative process, which resulted in the reduction of rating scale categories from 5 to 4, and in the deletion of 5 items, the psychometric properties of the Italian Lower Extremity Functional Scale improved. The retained 15 items with a 4-level response format fitted the Rasch model (internal construct validity), and demonstrated unidimensionality and good reliability indices (person-separation reliability 0.92; Cronbach's alpha 0.94). Then, the analysis showed differential item functioning for six of the retained items. The sensitivity to change of the Italian 15-item Lower Extremity Functional Scale was nearly equal to the one of the original version (effect size: 0.93 and 0.98; standardized response mean: 1.20 and 1.28, respectively for the 15-item and 20-item versions). The Italian Lower Extremity Functional Scale had unsatisfactory measurement properties. However, removing five items and simplifying the scoring from 5 to 4 levels resulted in a more valid measure with good reliability and sensitivity to change.

The use of multi-dimensional flow and morphodynamic models for restoration design analysis

NASA Astrophysics Data System (ADS)

McDonald, R.; Nelson, J. M.

2013-12-01

River restoration projects with the goal of restoring a wide range of morphologic and ecologic channel processes and functions have become common. The complex interactions between flow and sediment-transport make it challenging to design river channels that are both self-sustaining and improve ecosystem function. The relative immaturity of the field of river restoration and shortcomings in existing methodologies for evaluating channel designs contribute to this problem, often leading to project failures. The call for increased monitoring of constructed channels to evaluate which restoration techniques do and do not work is ubiquitous and may lead to improved channel restoration projects. However, an alternative approach is to detect project flaws before the channels are built by using numerical models to simulate hydraulic and sediment-transport processes and habitat in the proposed channel (Restoration Design Analysis). Multi-dimensional models provide spatially distributed quantities throughout the project domain that may be used to quantitatively evaluate restoration designs for such important metrics as (1) the change in water-surface elevation which can affect the extent and duration of floodplain reconnection, (2) sediment-transport and morphologic change which can affect the channel stability and long-term maintenance of the design; and (3) habitat changes. These models also provide an efficient way to evaluate such quantities over a range of appropriate discharges including low-probability events which often prove the greatest risk to the long-term stability of restored channels. Currently there are many free and open-source modeling frameworks available for such analysis including iRIC, Delft3D, and TELEMAC. In this presentation we give examples of Restoration Design Analysis for each of the metrics above from projects on the Russian River, CA and the Kootenai River, ID. These examples demonstrate how detailed Restoration Design Analysis can be used to

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…

Coupled numerical approach combining finite volume and lattice Boltzmann methods for multi-scale multi-physicochemical processes

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

Chen, Li; He, Ya-Ling; Kang, Qinjun

2013-12-15

A coupled (hybrid) simulation strategy spatially combining the finite volume method (FVM) and the lattice Boltzmann method (LBM), called CFVLBM, is developed to simulate coupled multi-scale multi-physicochemical processes. In the CFVLBM, computational domain of multi-scale problems is divided into two sub-domains, i.e., an open, free fluid region and a region filled with porous materials. The FVM and LBM are used for these two regions, respectively, with information exchanged at the interface between the two sub-domains. A general reconstruction operator (RO) is proposed to derive the distribution functions in the LBM from the corresponding macro scalar, the governing equation of whichmore » obeys the convection–diffusion equation. The CFVLBM and the RO are validated in several typical physicochemical problems and then are applied to simulate complex multi-scale coupled fluid flow, heat transfer, mass transport, and chemical reaction in a wall-coated micro reactor. The maximum ratio of the grid size between the FVM and LBM regions is explored and discussed. -- Highlights: •A coupled simulation strategy for simulating multi-scale phenomena is developed. •Finite volume method and lattice Boltzmann method are coupled. •A reconstruction operator is derived to transfer information at the sub-domains interface. •Coupled multi-scale multiple physicochemical processes in micro reactor are simulated. •Techniques to save computational resources and improve the efficiency are discussed.« less

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network

PubMed Central

Qu, Xiaobo; He, Yifan

2018-01-01

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods. PMID:29509666

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

PubMed

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

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.

Multi-scale computational modeling of developmental biology.

PubMed

Setty, Yaki

2012-08-01

Normal development of multicellular organisms is regulated by a highly complex process in which a set of precursor cells proliferate, differentiate and move, forming over time a functioning tissue. To handle their complexity, developmental systems can be studied over distinct scales. The dynamics of each scale is determined by the collective activity of entities at the scale below it. I describe a multi-scale computational approach for modeling developmental systems and detail the methodology through a synthetic example of a developmental system that retains key features of real developmental systems. I discuss the simulation of the system as it emerges from cross-scale and intra-scale interactions and describe how an in silico study can be carried out by modifying these interactions in a way that mimics in vivo experiments. I highlight biological features of the results through a comparison with findings in Caenorhabditis elegans germline development and finally discuss about the applications of the approach in real developmental systems and propose future extensions. The source code of the model of the synthetic developmental system can be found in www.wisdom.weizmann.ac.il/~yaki/MultiScaleModel. yaki.setty@gmail.com Supplementary data are available at Bioinformatics online.

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.

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.

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.

Development of a Scale Measuring Trait Anxiety in Physical Education

ERIC Educational Resources Information Center

Barkoukis, Vassilis; Rodafinos, Angelos; Koidou, Eirini; Tsorbatzoudis, Haralambos

2012-01-01

The aim of the present study was to examine the validity and reliability of a multi-dimensional measure of trait anxiety specifically designed for the physical education lesson. The Physical Education Trait Anxiety Scale was initially completed by 774 high school students during regular school classes. A confirmatory factor analysis supported the…

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

NASA Astrophysics Data System (ADS)

Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

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

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…

An improved KCF tracking algorithm based on multi-feature and multi-scale

NASA Astrophysics Data System (ADS)

Wu, Wei; Wang, Ding; Luo, Xin; Su, Yang; Tian, Weiye

2018-02-01

The purpose of visual tracking is to associate the target object in a continuous video frame. In recent years, the method based on the kernel correlation filter has become the research hotspot. However, the algorithm still has some problems such as video capture equipment fast jitter, tracking scale transformation. In order to improve the ability of scale transformation and feature description, this paper has carried an innovative algorithm based on the multi feature fusion and multi-scale transform. The experimental results show that our method solves the problem that the target model update when is blocked or its scale transforms. The accuracy of the evaluation (OPE) is 77.0%, 75.4% and the success rate is 69.7%, 66.4% on the VOT and OTB datasets. Compared with the optimal one of the existing target-based tracking algorithms, the accuracy of the algorithm is improved by 6.7% and 6.3% respectively. The success rates are improved by 13.7% and 14.2% respectively.

A multi-scale Q1/P0 approach to langrangian shock hydrodynamics.

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

Shashkov, Mikhail; Love, Edward; Scovazzi, Guglielmo

A new multi-scale, stabilized method for Q1/P0 finite element computations of Lagrangian shock hydrodynamics is presented. Instabilities (of hourglass type) are controlled by a stabilizing operator derived using the variational multi-scale analysis paradigm. The resulting stabilizing term takes the form of a pressure correction. With respect to currently implemented hourglass control approaches, the novelty of the method resides in its residual-based character. The stabilizing residual has a definite physical meaning, since it embeds a discrete form of the Clausius-Duhem inequality. Effectively, the proposed stabilization samples and acts to counter the production of entropy due to numerical instabilities. The proposed techniquemore » is applicable to materials with no shear strength, for which there exists a caloric equation of state. The stabilization operator is incorporated into a mid-point, predictor/multi-corrector time integration algorithm, which conserves mass, momentum and total energy. Encouraging numerical results in the context of compressible gas dynamics confirm the potential of the method.« less

Multi-label classification of chronically ill patients with bag of words and supervised dimensionality reduction algorithms.

PubMed

Bromuri, Stefano; Zufferey, Damien; Hennebert, Jean; Schumacher, Michael

2014-10-01

This research is motivated by the issue of classifying illnesses of chronically ill patients for decision support in clinical settings. Our main objective is to propose multi-label classification of multivariate time series contained in medical records of chronically ill patients, by means of quantization methods, such as bag of words (BoW), and multi-label classification algorithms. Our second objective is to compare supervised dimensionality reduction techniques to state-of-the-art multi-label classification algorithms. The hypothesis is that kernel methods and locality preserving projections make such algorithms good candidates to study multi-label medical time series. We combine BoW and supervised dimensionality reduction algorithms to perform multi-label classification on health records of chronically ill patients. The considered algorithms are compared with state-of-the-art multi-label classifiers in two real world datasets. Portavita dataset contains 525 diabetes type 2 (DT2) patients, with co-morbidities of DT2 such as hypertension, dyslipidemia, and microvascular or macrovascular issues. MIMIC II dataset contains 2635 patients affected by thyroid disease, diabetes mellitus, lipoid metabolism disease, fluid electrolyte disease, hypertensive disease, thrombosis, hypotension, chronic obstructive pulmonary disease (COPD), liver disease and kidney disease. The algorithms are evaluated using multi-label evaluation metrics such as hamming loss, one error, coverage, ranking loss, and average precision. Non-linear dimensionality reduction approaches behave well on medical time series quantized using the BoW algorithm, with results comparable to state-of-the-art multi-label classification algorithms. Chaining the projected features has a positive impact on the performance of the algorithm with respect to pure binary relevance approaches. The evaluation highlights the feasibility of representing medical health records using the BoW for multi-label classification

Modeling small-scale dairy farms in central Mexico using multi-criteria programming.

PubMed

Val-Arreola, D; Kebreab, E; France, J

2006-05-01

Milk supply from Mexican dairy farms does not meet demand and small-scale farms can contribute toward closing the gap. Two multi-criteria programming techniques, goal programming and compromise programming, were used in a study of small-scale dairy farms in central Mexico. To build the goal and compromise programming models, 4 ordinary linear programming models were also developed, which had objective functions to maximize metabolizable energy for milk production, to maximize margin of income over feed costs, to maximize metabolizable protein for milk production, and to minimize purchased feedstuffs. Neither multi-criteria approach was significantly better than the other; however, by applying both models it was possible to perform a more comprehensive analysis of these small-scale dairy systems. The multi-criteria programming models affirm findings from previous work and suggest that a forage strategy based on alfalfa, ryegrass, and corn silage would meet nutrient requirements of the herd. Both models suggested that there is an economic advantage in rescheduling the calving season to the second and third calendar quarters to better synchronize higher demand for nutrients with the period of high forage availability.

Goal-oriented robot navigation learning using a multi-scale space representation.

PubMed

Llofriu, M; Tejera, G; Contreras, M; Pelc, T; Fellous, J M; Weitzenfeld, A

2015-12-01

There has been extensive research in recent years on the multi-scale nature of hippocampal place cells and entorhinal grid cells encoding which led to many speculations on their role in spatial cognition. In this paper we focus on the multi-scale nature of place cells and how they contribute to faster learning during goal-oriented navigation when compared to a spatial cognition system composed of single scale place cells. The task consists of a circular arena with a fixed goal location, in which a robot is trained to find the shortest path to the goal after a number of learning trials. Synaptic connections are modified using a reinforcement learning paradigm adapted to the place cells multi-scale architecture. The model is evaluated in both simulation and physical robots. We find that larger scale and combined multi-scale representations favor goal-oriented navigation task learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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

Comparison of three-dimensional multi-segmental foot models used in clinical gait laboratories.

PubMed

Nicholson, Kristen; Church, Chris; Takata, Colton; Niiler, Tim; Chen, Brian Po-Jung; Lennon, Nancy; Sees, Julie P; Henley, John; Miller, Freeman

2018-05-16

Many skin-mounted three-dimensional multi-segmented foot models are currently in use for gait analysis. Evidence regarding the repeatability of models, including between trial and between assessors, is mixed, and there are no between model comparisons of kinematic results. This study explores differences in kinematics and repeatability between five three-dimensional multi-segmented foot models. The five models include duPont, Heidelberg, Oxford Child, Leardini, and Utah. Hind foot, forefoot, and hallux angles were calculated with each model for ten individuals. Two physical therapists applied markers three times to each individual to assess within and between therapist variability. Standard deviations were used to evaluate marker placement variability. Locally weighted regression smoothing with alpha-adjusted serial T tests analysis was used to assess kinematic similarities. All five models had similar variability, however, the Leardini model showed high standard deviations in plantarflexion/dorsiflexion angles. P-value curves for the gait cycle were used to assess kinematic similarities. The duPont and Oxford models had the most similar kinematics. All models demonstrated similar marker placement variability. Lower variability was noted in the sagittal and coronal planes compared to rotation in the transverse plane, suggesting a higher minimal detectable change when clinically considering rotation and a need for additional research. Between the five models, the duPont and Oxford shared the most kinematic similarities. While patterns of movement were very similar between all models, offsets were often present and need to be considered when evaluating published data. Copyright © 2018 Elsevier B.V. All rights reserved.

Two-dimensional fracture analysis of piezoelectric material based on the scaled boundary node method

NASA Astrophysics Data System (ADS)

Shen-Shen, Chen; Juan, Wang; Qing-Hua, Li

2016-04-01

A scaled boundary node method (SBNM) is developed for two-dimensional fracture analysis of piezoelectric material, which allows the stress and electric displacement intensity factors to be calculated directly and accurately. As a boundary-type meshless method, the SBNM employs the moving Kriging (MK) interpolation technique to an approximate unknown field in the circumferential direction and therefore only a set of scattered nodes are required to discretize the boundary. As the shape functions satisfy Kronecker delta property, no special techniques are required to impose the essential boundary conditions. In the radial direction, the SBNM seeks analytical solutions by making use of analytical techniques available to solve ordinary differential equations. Numerical examples are investigated and satisfactory solutions are obtained, which validates the accuracy and simplicity of the proposed approach. Project supported by the National Natural Science Foundation of China (Grant Nos. 11462006 and 21466012), the Foundation of Jiangxi Provincial Educational Committee, China (Grant No. KJLD14041), and the Foundation of East China Jiaotong University, China (Grant No. 09130020).

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Validating Remotely Sensed Land Surface Evapotranspiration Based on Multi-scale Field Measurements

NASA Astrophysics Data System (ADS)

Jia, Z.; Liu, S.; Ziwei, X.; Liang, S.

2012-12-01

The land surface evapotranspiration plays an important role in the surface energy balance and the water cycle. There have been significant technical and theoretical advances in our knowledge of evapotranspiration over the past two decades. Acquisition of the temporally and spatially continuous distribution of evapotranspiration using remote sensing technology has attracted the widespread attention of researchers and managers. However, remote sensing technology still has many uncertainties coming from model mechanism, model inputs, parameterization schemes, and scaling issue in the regional estimation. Achieving remotely sensed evapotranspiration (RS_ET) with confident certainty is required but difficult. As a result, it is indispensable to develop the validation methods to quantitatively assess the accuracy and error sources of the regional RS_ET estimations. This study proposes an innovative validation method based on multi-scale evapotranspiration acquired from field measurements, with the validation results including the accuracy assessment, error source analysis, and uncertainty analysis of the validation process. It is a potentially useful approach to evaluate the accuracy and analyze the spatio-temporal properties of RS_ET at both the basin and local scales, and is appropriate to validate RS_ET in diverse resolutions at different time-scales. An independent RS_ET validation using this method was presented over the Hai River Basin, China in 2002-2009 as a case study. Validation at the basin scale showed good agreements between the 1 km annual RS_ET and the validation data such as the water balanced evapotranspiration, MODIS evapotranspiration products, precipitation, and landuse types. Validation at the local scale also had good results for monthly, daily RS_ET at 30 m and 1 km resolutions, comparing to the multi-scale evapotranspiration measurements from the EC and LAS, respectively, with the footprint model over three typical landscapes. Although some

Multi-scale functional mapping of tidal marsh vegetation for restoration monitoring

NASA Astrophysics Data System (ADS)

Tuxen Bettman, Karin

2007-12-01

Nearly half of the world's natural wetlands have been destroyed or degraded, and in recent years, there have been significant endeavors to restore wetland habitat throughout the world. Detailed mapping of restoring wetlands can offer valuable information about changes in vegetation and geomorphology, which can inform the restoration process and ultimately help to improve chances of restoration success. I studied six tidal marshes in the San Francisco Estuary, CA, US, between 2003 and 2004 in order to develop techniques for mapping tidal marshes at multiple scales by incorporating specific restoration objectives for improved longer term monitoring. I explored a "pixel-based" remote sensing image analysis method for mapping vegetation in restored and natural tidal marshes, describing the benefits and limitations of this type of approach (Chapter 2). I also performed a multi-scale analysis of vegetation pattern metrics for a recently restored tidal marsh in order to target the metrics that are consistent across scales and will be robust measures of marsh vegetation change (Chapter 3). Finally, I performed an "object-based" image analysis using the same remotely sensed imagery, which maps vegetation type and specific wetland functions at multiple scales (Chapter 4). The combined results of my work highlight important trends and management implications for monitoring wetland restoration using remote sensing, and will better enable restoration ecologists to use remote sensing for tidal marsh monitoring. Several findings important for tidal marsh restoration monitoring were made. Overall results showed that pixel-based methods are effective at quantifying landscape changes in composition and diversity in recently restored marshes, but are limited in their use for quantifying smaller, more fine-scale changes. While pattern metrics can highlight small but important changes in vegetation composition and configuration across years, scientists should exercise caution when

Multi-scale graph-cut algorithm for efficient water-fat separation.

PubMed

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

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.

MUSIC: MUlti-Scale Initial Conditions

NASA Astrophysics Data System (ADS)

Hahn, Oliver; Abel, Tom

2013-11-01

MUSIC generates multi-scale initial conditions with multiple levels of refinements for cosmological ‘zoom-in’ simulations. The code uses an adaptive convolution of Gaussian white noise with a real-space transfer function kernel together with an adaptive multi-grid Poisson solver to generate displacements and velocities following first- (1LPT) or second-order Lagrangian perturbation theory (2LPT). MUSIC achieves rms relative errors of the order of 10-4 for displacements and velocities in the refinement region and thus improves in terms of errors by about two orders of magnitude over previous approaches. In addition, errors are localized at coarse-fine boundaries and do not suffer from Fourier space-induced interference ringing.

Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface.

PubMed

Park, Ji-Won; Jeong, Hyobin; Kang, Byeongsoo; Kim, Su Jin; Park, Sang Yoon; Kang, Sokbom; Kim, Hark Kyun; Choi, Joon Sig; Hwang, Daehee; Lee, Tae Geol

2015-06-05

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states.

Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface

PubMed Central

Park, Ji-Won; Jeong, Hyobin; Kang, Byeongsoo; Kim, Su Jin; Park, Sang Yoon; Kang, Sokbom; Kim, Hark Kyun; Choi, Joon Sig; Hwang, Daehee; Lee, Tae Geol

2015-01-01

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) emerges as a promising tool to identify the ions (small molecules) indicative of disease states from the surface of patient tissues. In TOF-SIMS analysis, an enhanced ionization of surface molecules is critical to increase the number of detected ions. Several methods have been developed to enhance ionization capability. However, how these methods improve identification of disease-related ions has not been systematically explored. Here, we present a multi-dimensional SIMS (MD-SIMS) that combines conventional TOF-SIMS and metal-assisted SIMS (MetA-SIMS). Using this approach, we analyzed cancer and adjacent normal tissues first by TOF-SIMS and subsequently by MetA-SIMS. In total, TOF- and MetA-SIMS detected 632 and 959 ions, respectively. Among them, 426 were commonly detected by both methods, while 206 and 533 were detected uniquely by TOF- and MetA-SIMS, respectively. Of the 426 commonly detected ions, 250 increased in their intensities by MetA-SIMS, whereas 176 decreased. The integrated analysis of the ions detected by the two methods resulted in an increased number of discriminatory ions leading to an enhanced separation between cancer and normal tissues. Therefore, the results show that MD-SIMS can be a useful approach to provide a comprehensive list of discriminatory ions indicative of disease states. PMID:26046669

Bayesian Analysis of High Dimensional Classification

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Subhadeep; Liang, Faming

2009-12-01

Modern data mining and bioinformatics have presented an important playground for statistical learning techniques, where the number of input variables is possibly much larger than the sample size of the training data. In supervised learning, logistic regression or probit regression can be used to model a binary output and form perceptron classification rules based on Bayesian inference. In these cases , there is a lot of interest in searching for sparse model in High Dimensional regression(/classification) setup. we first discuss two common challenges for analyzing high dimensional data. The first one is the curse of dimensionality. The complexity of many existing algorithms scale exponentially with the dimensionality of the space and by virtue of that algorithms soon become computationally intractable and therefore inapplicable in many real applications. secondly, multicollinearities among the predictors which severely slowdown the algorithm. In order to make Bayesian analysis operational in high dimension we propose a novel 'Hierarchical stochastic approximation monte carlo algorithm' (HSAMC), which overcomes the curse of dimensionality, multicollinearity of predictors in high dimension and also it possesses the self-adjusting mechanism to avoid the local minima separated by high energy barriers. Models and methods are illustrated by simulation inspired from from the feild of genomics. Numerical results indicate that HSAMC can work as a general model selection sampler in high dimensional complex model space.

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.

QED multi-dimensional vacuum polarization finite-difference solver

NASA Astrophysics Data System (ADS)

Carneiro, Pedro; Grismayer, Thomas; Silva, Luís; Fonseca, Ricardo

2015-11-01

The Extreme Light Infrastructure (ELI) is expected to deliver peak intensities of 1023 - 1024 W/cm2 allowing to probe nonlinear Quantum Electrodynamics (QED) phenomena in an unprecedented regime. Within the framework of QED, the second order process of photon-photon scattering leads to a set of extended Maxwell's equations [W. Heisenberg and H. Euler, Z. Physik 98, 714] effectively creating nonlinear polarization and magnetization terms that account for the nonlinear response of the vacuum. To model this in a self-consistent way, we present a multi dimensional generalized Maxwell equation finite difference solver with significantly enhanced dispersive properties, which was implemented in the OSIRIS particle-in-cell code [R.A. Fonseca et al. LNCS 2331, pp. 342-351, 2002]. We present a detailed numerical analysis of this electromagnetic solver. As an illustration of the properties of the solver, we explore several examples in extreme conditions. We confirm the theoretical prediction of vacuum birefringence of a pulse propagating in the presence of an intense static background field [arXiv:1301.4918 [quant-ph

EXAMINING THE DIMENSIONALITY OF COLQUITT'S ORGANIZATIONAL JUSTICE SCALE IN A PUBLIC HEALTH SECTOR CONTEXT.

PubMed

Enoksen, Elisabeth

2015-06-01

In 2001, Colquitt developed an Organizational Justice Scale that intended to measure procedural, distributive, interpersonal, and informational justice. The dimensionality of the scale has been tested in subsequent studies with diverging results. Given the fact that contextual differences may account for more variation across research sites than individual differences, the deviating research findings may be due to context. This study examined the dimensionality of Colquitt's Organizational Justice Scale in a new context: the public health sector. The procedural and informational justice dimensions were highly correlated, but confirmatory factor analysis showed that a four-factor solution provided a better fit than a three-factor solution. All fit indices for the four-factor model were consistent with a good model. There was, however, evidence of a potential omitted factor, procedural-voice justice, which has also been found in a previous examination of the measure in the public sector.

Deep multi-scale convolutional neural network for hyperspectral image classification

NASA Astrophysics Data System (ADS)

Zhang, Feng-zhe; Yang, Xia

2018-04-01

In this paper, we proposed a multi-scale convolutional neural network for hyperspectral image classification task. Firstly, compared with conventional convolution, we utilize multi-scale convolutions, which possess larger respective fields, to extract spectral features of hyperspectral image. We design a deep neural network with a multi-scale convolution layer which contains 3 different convolution kernel sizes. Secondly, to avoid overfitting of deep neural network, dropout is utilized, which randomly sleeps neurons, contributing to improve the classification accuracy a bit. In addition, new skills like ReLU in deep learning is utilized in this paper. We conduct experiments on University of Pavia and Salinas datasets, and obtained better classification accuracy compared with other methods.

Scalable Methods for Uncertainty Quantification, Data Assimilation and Target Accuracy Assessment for Multi-Physics Advanced Simulation of Light Water Reactors

NASA Astrophysics Data System (ADS)

Khuwaileh, Bassam

High fidelity simulation of nuclear reactors entails large scale applications characterized with high dimensionality and tremendous complexity where various physics models are integrated in the form of coupled models (e.g. neutronic with thermal-hydraulic feedback). Each of the coupled modules represents a high fidelity formulation of the first principles governing the physics of interest. Therefore, new developments in high fidelity multi-physics simulation and the corresponding sensitivity/uncertainty quantification analysis are paramount to the development and competitiveness of reactors achieved through enhanced understanding of the design and safety margins. Accordingly, this dissertation introduces efficient and scalable algorithms for performing efficient Uncertainty Quantification (UQ), Data Assimilation (DA) and Target Accuracy Assessment (TAA) for large scale, multi-physics reactor design and safety problems. This dissertation builds upon previous efforts for adaptive core simulation and reduced order modeling algorithms and extends these efforts towards coupled multi-physics models with feedback. The core idea is to recast the reactor physics analysis in terms of reduced order models. This can be achieved via identifying the important/influential degrees of freedom (DoF) via the subspace analysis, such that the required analysis can be recast by considering the important DoF only. In this dissertation, efficient algorithms for lower dimensional subspace construction have been developed for single physics and multi-physics applications with feedback. Then the reduced subspace is used to solve realistic, large scale forward (UQ) and inverse problems (DA and TAA). Once the elite set of DoF is determined, the uncertainty/sensitivity/target accuracy assessment and data assimilation analysis can be performed accurately and efficiently for large scale, high dimensional multi-physics nuclear engineering applications. Hence, in this work a Karhunen-Loeve (KL

Multi-physics optimization of three-dimensional microvascular polymeric components

NASA Astrophysics Data System (ADS)

Aragón, Alejandro M.; Saksena, Rajat; Kozola, Brian D.; Geubelle, Philippe H.; Christensen, Kenneth T.; White, Scott R.

2013-01-01

This work discusses the computational design of microvascular polymeric materials, which aim at mimicking the behavior found in some living organisms that contain a vascular system. The optimization of the topology of the embedded three-dimensional microvascular network is carried out by coupling a multi-objective constrained genetic algorithm with a finite-element based physics solver, the latter validated through experiments. The optimization is carried out on multiple conflicting objective functions, namely the void volume fraction left by the network, the energy required to drive the fluid through the network and the maximum temperature when the material is subjected to thermal loads. The methodology presented in this work results in a viable alternative for the multi-physics optimization of these materials for active-cooling applications.

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.

Up-scaling of multi-variable flood loss models from objects to land use units at the meso-scale

NASA Astrophysics Data System (ADS)

Kreibich, Heidi; Schröter, Kai; Merz, Bruno

2016-05-01

Flood risk management increasingly relies on risk analyses, including loss modelling. Most of the flood loss models usually applied in standard practice have in common that complex damaging processes are described by simple approaches like stage-damage functions. Novel multi-variable models significantly improve loss estimation on the micro-scale and may also be advantageous for large-scale applications. However, more input parameters also reveal additional uncertainty, even more in upscaling procedures for meso-scale applications, where the parameters need to be estimated on a regional area-wide basis. To gain more knowledge about challenges associated with the up-scaling of multi-variable flood loss models the following approach is applied: Single- and multi-variable micro-scale flood loss models are up-scaled and applied on the meso-scale, namely on basis of ATKIS land-use units. Application and validation is undertaken in 19 municipalities, which were affected during the 2002 flood by the River Mulde in Saxony, Germany by comparison to official loss data provided by the Saxon Relief Bank (SAB).In the meso-scale case study based model validation, most multi-variable models show smaller errors than the uni-variable stage-damage functions. The results show the suitability of the up-scaling approach, and, in accordance with micro-scale validation studies, that multi-variable models are an improvement in flood loss modelling also on the meso-scale. However, uncertainties remain high, stressing the importance of uncertainty quantification. Thus, the development of probabilistic loss models, like BT-FLEMO used in this study, which inherently provide uncertainty information are the way forward.

Multi-Body Analysis of the 1/5 Scale Wind Tunnel Model of the V-22 Tiltrotor

NASA Technical Reports Server (NTRS)

Ghiringhelli, G. L.; Masarati, P.; Mantegazza, P.; Nixon, M. W.

1999-01-01

The paper presents a multi-body analysis of the 1/5 scale wind tunnel model of the V-22 tiltrotor, the Wing and Rotor Aeroelastic Testing System (WRATS), currently tested at NASA Langley Research Center. An original multi-body formulation has been developed at the Dipartimento di Ingegneria Aerospaziale of the Politecnico di Milano, Italy. It is based on the direct writing of the equilibrium equations of independent rigid bodies, connected by kinematic constraints that result in the addition of algebraic constraint equations, and by dynamic constraints, that directly contribute to the equilibrium equations. The formulation has been extended to the simultaneous solution of interdisciplinary problems by modeling electric and hydraulic networks, for aeroservoelastic problems. The code has been tailored to the modeling of rotorcrafts while preserving a complete generality. A family of aerodynamic elements has been introduced to model high aspect aerodynamic surfaces, based on the strip theory, with quasi-steady aerodynamic coefficients, compressibility, post-stall interpolation of experimental data, dynamic stall modeling, and radial flow drag. Different models for the induced velocity of the rotor can be used, from uniform velocity to dynamic in flow. A complete dynamic and aeroelastic analysis of the model of the V-22 tiltrotor has been performed, to assess the validity of the formulation and to exploit the unique features of multi-body analysis with respect to conventional comprehensive rotorcraft codes; These are the ability to model the exact kinematics of mechanical systems, and the possibility to simulate unusual maneuvers and unusual flight conditions, that are particular to the tiltrotor, e.g. the conversion maneuver. A complete modal validation of the analytical model has been performed, to assess the ability to reproduce the correct dynamics of the system with a relatively coarse beam model of the semispan wing, pylon and rotor. Particular care has been used

Detecting recurrent gene mutation in interaction network context using multi-scale graph diffusion.

PubMed

Babaei, Sepideh; Hulsman, Marc; Reinders, Marcel; de Ridder, Jeroen

2013-01-23

Delineating the molecular drivers of cancer, i.e. determining cancer genes and the pathways which they deregulate, is an important challenge in cancer research. In this study, we aim to identify pathways of frequently mutated genes by exploiting their network neighborhood encoded in the protein-protein interaction network. To this end, we introduce a multi-scale diffusion kernel and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter, determining the size of the network neighborhood that is taken into account. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity, we find genes that harbor frequent mutations in their interaction network context. We identify densely connected components of known and putatively novel cancer genes and demonstrate that they are strongly enriched for cancer related pathways across the diffusion scales. Moreover, the mutations in the clusters exhibit a significant pattern of mutual exclusion, supporting the conjecture that such genes are functionally linked. Using multi-scale diffusion kernel, various infrequently mutated genes are found to harbor significant numbers of mutations in their interaction network neighborhood. Many of them are well-known cancer genes. The results demonstrate the importance of defining recurrent mutations while taking into account the interaction network context. Importantly, the putative cancer genes and networks detected in this study are found to be significant at different diffusion scales, confirming the necessity of a multi-scale analysis.

Three-dimensional micro-scale strain mapping in living biological soft tissues.

PubMed

Moo, Eng Kuan; Sibole, Scott C; Han, Sang Kuy; Herzog, Walter

2018-04-01

Non-invasive characterization of the mechanical micro-environment surrounding cells in biological tissues at multiple length scales is important for the understanding of the role of mechanics in regulating the biosynthesis and phenotype of cells. However, there is a lack of imaging methods that allow for characterization of the cell micro-environment in three-dimensional (3D) space. The aims of this study were (i) to develop a multi-photon laser microscopy protocol capable of imprinting 3D grid lines onto living tissue at a high spatial resolution, and (ii) to develop image processing software capable of analyzing the resulting microscopic images and performing high resolution 3D strain analyses. Using articular cartilage as the biological tissue of interest, we present a novel two-photon excitation imaging technique for measuring the internal 3D kinematics in intact cartilage at sub-micrometer resolution, spanning length scales from the tissue to the cell level. Using custom image processing software, we provide accurate and robust 3D micro-strain analysis that allows for detailed qualitative and quantitative assessment of the 3D tissue kinematics. This novel technique preserves tissue structural integrity post-scanning, therefore allowing for multiple strain measurements at different time points in the same specimen. The proposed technique is versatile and opens doors for experimental and theoretical investigations on the relationship between tissue deformation and cell biosynthesis. Studies of this nature may enhance our understanding of the mechanisms underlying cell mechano-transduction, and thus, adaptation and degeneration of soft connective tissues. We presented a novel two-photon excitation imaging technique for measuring the internal 3D kinematics in intact cartilage at sub-micrometer resolution, spanning from tissue length scale to cellular length scale. Using a custom image processing software (lsmgridtrack), we provide accurate and robust micro

Multi-Scale Approach for Predicting Fish Species Distributions across Coral Reef Seascapes

PubMed Central

Pittman, Simon J.; Brown, Kerry A.

2011-01-01

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support

Multi-scale approach for predicting fish species distributions across coral reef seascapes.

PubMed

Pittman, Simon J; Brown, Kerry A

2011-01-01

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5-300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided 'outstanding' model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided 'outstanding' model predictions for two of five species, with the remaining three models considered 'excellent' (AUC = 0.8-0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation

Determining Individual Phase Properties in a Multi-phase Q&P Steel using Multi-scale Indentation Tests

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

Cheng, Guang; Choi, Kyoo Sil; Hu, Xiaohua

2016-01-15

A new inverse method was developed to predict the stress-strain behaviors of constituent phases in a multi-phase steel using the load-depth curves measured in nanoindentation tests combined with microhardness measurements. A power law hardening response was assumed for each phase, and an empirical relationship between hardness and yield strength was assumed. Adjustment was made to eliminate the indentation size effect and indenter bluntness effect. With the newly developed inverse method and statistical analysis of the hardness histogram for each phase, the average stress-strain curves of individual phases in a quench and partitioning (Q&P) steel, including austenite, tempered martensite and untemperedmore » martensite, were calculated and the results were compared with the phase properties obtained by in-situ high energy X-ray diffraction (HEXRD) test. It is demonstrated that multi-scale instrumented indentation tests together with the new inverse method are capable of determining the individual phase flow properties in multi-phase alloys.« less

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling

A Multi-Scale Settlement Matching Algorithm Based on ARG

NASA Astrophysics Data System (ADS)

Yue, Han; Zhu, Xinyan; Chen, Di; Liu, Lingjia

2016-06-01

Homonymous entity matching is an important part of multi-source spatial data integration, automatic updating and change detection. Considering the low accuracy of existing matching methods in dealing with matching multi-scale settlement data, an algorithm based on Attributed Relational Graph (ARG) is proposed. The algorithm firstly divides two settlement scenes at different scales into blocks by small-scale road network and constructs local ARGs in each block. Then, ascertains candidate sets by merging procedures and obtains the optimal matching pairs by comparing the similarity of ARGs iteratively. Finally, the corresponding relations between settlements at large and small scales are identified. At the end of this article, a demonstration is presented and the results indicate that the proposed algorithm is capable of handling sophisticated cases.

[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.

Biointerface dynamics--Multi scale modeling considerations.

PubMed

Pajic-Lijakovic, Ivana; Levic, Steva; Nedovic, Viktor; Bugarski, Branko

2015-08-01

Irreversible nature of matrix structural changes around the immobilized cell aggregates caused by cell expansion is considered within the Ca-alginate microbeads. It is related to various effects: (1) cell-bulk surface effects (cell-polymer mechanical interactions) and cell surface-polymer surface effects (cell-polymer electrostatic interactions) at the bio-interface, (2) polymer-bulk volume effects (polymer-polymer mechanical and electrostatic interactions) within the perturbed boundary layers around the cell aggregates, (3) cumulative surface and volume effects within the parts of the microbead, and (4) macroscopic effects within the microbead as a whole based on multi scale modeling approaches. All modeling levels are discussed at two time scales i.e. long time scale (cell growth time) and short time scale (cell rearrangement time). Matrix structural changes results in the resistance stress generation which have the feedback impact on: (1) single and collective cell migrations, (2) cell deformation and orientation, (3) decrease of cell-to-cell separation distances, and (4) cell growth. Herein, an attempt is made to discuss and connect various multi scale modeling approaches on a range of time and space scales which have been proposed in the literature in order to shed further light to this complex course-consequence phenomenon which induces the anomalous nature of energy dissipation during the structural changes of cell aggregates and matrix quantified by the damping coefficients (the orders of the fractional derivatives). Deeper insight into the matrix partial disintegration within the boundary layers is useful for understanding and minimizing the polymer matrix resistance stress generation within the interface and on that base optimizing cell growth. Copyright © 2015 Elsevier B.V. All rights reserved.

A lock-free priority queue design based on multi-dimensional linked lists

DOE PAGES

Dechev, Damian; Zhang, Deli

2015-04-03

The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN)more » for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.« less

A lock-free priority queue design based on multi-dimensional linked lists

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

Dechev, Damian; Zhang, Deli

The throughput of concurrent priority queues is pivotal to multiprocessor applications such as discrete event simulation, best-first search and task scheduling. Existing lock-free priority queues are mostly based on skiplists, which probabilistically create shortcuts in an ordered list for fast insertion of elements. The use of skiplists eliminates the need of global rebalancing in balanced search trees and ensures logarithmic sequential search time on average, but the worst-case performance is linear with respect to the input size. In this paper, we propose a quiescently consistent lock-free priority queue based on a multi-dimensional list that guarantees worst-case search time of O(logN)more » for key universe of size N. The novel multi-dimensional list (MDList) is composed of nodes that contain multiple links to child nodes arranged by their dimensionality. The insertion operation works by first injectively mapping the scalar key to a high-dimensional vector, then uniquely locating the target position by using the vector as coordinates. Nodes in MDList are ordered by their coordinate prefixes and the ordering property of the data structure is readily maintained during insertion without rebalancing nor randomization. Furthermore, in our experimental evaluation using a micro-benchmark, our priority queue achieves an average of 50% speedup over the state of the art approaches under high concurrency.« less

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

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

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…

A Non Local Electron Heat Transport Model for Multi-Dimensional Fluid Codes

NASA Astrophysics Data System (ADS)

Schurtz, Guy

2000-10-01

Apparent inhibition of thermal heat flow is one of the most ancient problems in computational Inertial Fusion and flux-limited Spitzer-Harm conduction has been a mainstay in multi-dimensional hydrodynamic codes for more than 25 years. Theoretical investigation of the problem indicates that heat transport in laser produced plasmas has to be considered as a non local process. Various authors contributed to the non local theory and proposed convolution formulas designed for practical implementation in one-dimensional fluid codes. Though the theory, confirmed by kinetic calculations, actually predicts a reduced heat flux, it fails to explain the very small limiters required in two-dimensional simulations. Fokker-Planck simulations by Epperlein, Rickard and Bell [PRL 61, 2453 (1988)] demonstrated that non local effects could lead to a strong reduction of heat flow in two dimensions, even in situations where a one-dimensional analysis suggests that the heat flow is nearly classical. We developed at CEA/DAM a non local electron heat transport model suitable for implementation in our two-dimensional radiation hydrodynamic code FCI2. This model may be envisionned as the first step of an iterative solution of the Fokker-Planck equations; it takes the mathematical form of multigroup diffusion equations, the solution of which yields both the heat flux and the departure of the electron distribution function to the Maxwellian. Although direct implementation of the model is straightforward, formal solutions of it can be expressed in convolution form, exhibiting a three-dimensional tensor propagator. Reduction to one dimension retrieves the original formula of Luciani, Mora and Virmont [PRL 51, 1664 (1983)]. Intense magnetic fields may be generated by thermal effects in laser targets; these fields, as well as non local effects, will inhibit electron conduction. We present simulations where both effects are taken into account and shortly discuss the coupling strategy between them.

Multi-level structure in the large scale distribution of optically luminous galaxies

NASA Astrophysics Data System (ADS)

Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen

1992-04-01

Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.

A Multi-scale Approach to Urban Thermal Analysis

NASA Technical Reports Server (NTRS)

Gluch, Renne; Quattrochi, Dale A.

2005-01-01

An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.

Multi-scale structures of turbulent magnetic reconnection

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

Nakamura, T. K. M., E-mail: takuma.nakamura@oeaw.ac.at; Nakamura, R.; Narita, Y.

2016-05-15

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in whichmore » modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.« less

Multi-scale structures of turbulent magnetic reconnection

NASA Astrophysics Data System (ADS)

Nakamura, T. K. M.; Nakamura, R.; Narita, Y.; Baumjohann, W.; Daughton, W.

2016-05-01

We have analyzed data from a series of 3D fully kinetic simulations of turbulent magnetic reconnection with a guide field. A new concept of the guide filed reconnection process has recently been proposed, in which the secondary tearing instability and the resulting formation of oblique, small scale flux ropes largely disturb the structure of the primary reconnection layer and lead to 3D turbulent features [W. Daughton et al., Nat. Phys. 7, 539 (2011)]. In this paper, we further investigate the multi-scale physics in this turbulent, guide field reconnection process by introducing a wave number band-pass filter (k-BPF) technique in which modes for the small scale (less than ion scale) fluctuations and the background large scale (more than ion scale) variations are separately reconstructed from the wave number domain to the spatial domain in the inverse Fourier transform process. Combining with the Fourier based analyses in the wave number domain, we successfully identify spatial and temporal development of the multi-scale structures in the turbulent reconnection process. When considering a strong guide field, the small scale tearing mode and the resulting flux ropes develop over a specific range of oblique angles mainly along the edge of the primary ion scale flux ropes and reconnection separatrix. The rapid merging of these small scale modes leads to a smooth energy spectrum connecting ion and electron scales. When the guide field is sufficiently weak, the background current sheet is strongly kinked and oblique angles for the small scale modes are widely scattered at the kinked regions. Similar approaches handling both the wave number and spatial domains will be applicable to the data from multipoint, high-resolution spacecraft observations such as the NASA magnetospheric multiscale (MMS) mission.

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

The DSM‐5 Dimensional Anxiety Scales in a Dutch non‐clinical sample: psychometric properties including the adult separation anxiety disorder scale

PubMed Central

Bögels, Susan M.

2016-01-01

Abstract With DSM‐5, the American Psychiatric Association encourages complementing categorical diagnoses with dimensional severity ratings. We therefore examined the psychometric properties of the DSM‐5 Dimensional Anxiety Scales, a set of brief dimensional scales that are consistent in content and structure and assess DSM‐5‐based core features of anxiety disorders. Participants (285 males, 255 females) completed the DSM‐5 Dimensional Anxiety Scales for social anxiety disorder, generalized anxiety disorder, specific phobia, agoraphobia, and panic disorder that were included in previous studies on the scales, and also for separation anxiety disorder, which is included in the DSM‐5 chapter on anxiety disorders. Moreover, they completed the Screen for Child Anxiety Related Emotional Disorders Adult version (SCARED‐A). The DSM‐5 Dimensional Anxiety Scales demonstrated high internal consistency, and the scales correlated significantly and substantially with corresponding SCARED‐A subscales, supporting convergent validity. Separation anxiety appeared present among adults, supporting the DSM‐5 recognition of separation anxiety as an anxiety disorder across the life span. To conclude, the DSM‐5 Dimensional Anxiety Scales are a valuable tool to screen for specific adult anxiety disorders, including separation anxiety. Research in more diverse and clinical samples with anxiety disorders is needed. © 2016 The Authors International Journal of Methods in Psychiatric Research Published by John Wiley & Sons Ltd. PMID:27378317

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.

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

Scaling relations for a functionally two-dimensional plant: Chamaesyce setiloba (Euphorbiaceae).

PubMed

Koontz, Terri L; Petroff, Alexander; West, Geoffrey B; Brown, James H

2009-05-01

Many characteristics of plants and animals scale with body size as described by allometric equations of the form Y = βM(α), where Y is an attribute of the organism, β is a coefficient that varies with attribute, M is a measure of organism size, and α is another constant, the scaling exponent. In current models, the frequently observed quarter-power scaling exponents are hypothesized to be due to fractal-like structures. However, not all plants or animals conform to the assumptions of these models. Therefore, they might be expected to have different scaling relations. We studied one such plant, Chamaesyce setiloba, a prostrate annual herb that grows to functionally fill a two-dimensional space. Number of leaves scaled slightly less than isometrically with total aboveground plant mass (α ≈ 0.9) and substantially less than isometrically with dry total stem mass (α = 0.82), showing reduced allocation to leaf as opposed to stem tissue with increasing plant size. Additionally, scalings of the lengths and radii of parent and daughter branches differed from those predicted for three-dimensional trees and shrubs. Unlike plants with typical three-dimensional architectures, C. setiloba has distinctive scaling relations associated with its particular prostrate herbaceous growth form.

Multi-scaling allometric analysis for urban and regional development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2017-01-01

The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.

Identifying associations between pig pathologies using a multi-dimensional machine learning methodology.

PubMed

Sanchez-Vazquez, Manuel J; Nielen, Mirjam; Edwards, Sandra A; Gunn, George J; Lewis, Fraser I

2012-08-31

Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously. Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology. The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.

Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.

PubMed

Frasch, Martin G; Lobmaier, Silvia M; Stampalija, Tamara; Desplats, Paula; Pallarés, María Eugenia; Pastor, Verónica; Brocco, Marcela A; Wu, Hau-Tieng; Schulkin, Jay; Herry, Christophe L; Seely, Andrew J E; Metz, Gerlinde A S; Louzoun, Yoram; Antonelli, Marta C

2018-05-30

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Mokken scaling of the Myocardial Infarction Dimensional Assessment Scale (MIDAS).

PubMed

Thompson, David R; Watson, Roger

2011-02-01

The purpose of this study was to examine the hierarchical and cumulative nature of the 35 items of the Myocardial Infarction Dimensional Assessment Scale (MIDAS), a disease-specific health-related quality of life measure. Data from 668 participants who completed the MIDAS were analysed using the Mokken Scaling Procedure, which is a computer program that searches polychotomous data for hierarchical and cumulative scales on the basis of a range of diagnostic criteria. Fourteen MIDAS items were retained in a Mokken scale and these items included physical activity, insecurity, emotional reaction and dependency items but excluded items related to diet, medication or side-effects. Item difficulty, in item response theory terms, ran from physical activity items (low difficulty) to insecurity, suggesting that the most severe quality of life effect of myocardial infarction is loneliness and isolation. Items from the MIDAS form a strong and reliable Mokken scale, which provides new insight into the relationship between items in the MIDAS and the measurement of quality of life after myocardial infarction. © 2010 Blackwell Publishing Ltd.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

Approximate series solution of multi-dimensional, time fractional-order (heat-like) diffusion equations using FRDTM.

PubMed

Singh, Brajesh K; Srivastava, Vineet K

2015-04-01

The main goal of this paper is to present a new approximate series solution of the multi-dimensional (heat-like) diffusion equation with time-fractional derivative in Caputo form using a semi-analytical approach: fractional-order reduced differential transform method (FRDTM). The efficiency of FRDTM is confirmed by considering four test problems of the multi-dimensional time fractional-order diffusion equation. FRDTM is a very efficient, effective and powerful mathematical tool which provides exact or very close approximate solutions for a wide range of real-world problems arising in engineering and natural sciences, modelled in terms of differential equations.

Approximate series solution of multi-dimensional, time fractional-order (heat-like) diffusion equations using FRDTM

PubMed Central

Singh, Brajesh K.; Srivastava, Vineet K.

2015-01-01

The main goal of this paper is to present a new approximate series solution of the multi-dimensional (heat-like) diffusion equation with time-fractional derivative in Caputo form using a semi-analytical approach: fractional-order reduced differential transform method (FRDTM). The efficiency of FRDTM is confirmed by considering four test problems of the multi-dimensional time fractional-order diffusion equation. FRDTM is a very efficient, effective and powerful mathematical tool which provides exact or very close approximate solutions for a wide range of real-world problems arising in engineering and natural sciences, modelled in terms of differential equations. PMID:26064639

A Replication Study on the Multi-Dimensionality of Online Social Presence

ERIC Educational Resources Information Center

Mykota, David B.

2015-01-01

The purpose of the present study is to conduct an external replication into the multi-dimensionality of social presence as measured by the Computer-Mediated Communication Questionnaire (Tu, 2005). Online social presence is one of the more important constructs for determining the level of interaction and effectiveness of learning in an online…

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

NASA Astrophysics Data System (ADS)

Kou, Jisheng; Sun, Shuyu

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng-Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from the microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young-Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young-Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young-Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally, numerical tests

An information model for managing multi-dimensional gridded data in a GIS

NASA Astrophysics Data System (ADS)

Xu, H.; Abdul-Kadar, F.; Gao, P.

2016-04-01

Earth observation agencies like NASA and NOAA produce huge volumes of historical, near real-time, and forecasting data representing terrestrial, atmospheric, and oceanic phenomena. The data drives climatological and meteorological studies, and underpins operations ranging from weather pattern prediction and forest fire monitoring to global vegetation analysis. These gridded data sets are distributed mostly as files in HDF, GRIB, or netCDF format and quantify variables like precipitation, soil moisture, or sea surface temperature, along one or more dimensions like time and depth. Although the data cube is a well-studied model for storing and analyzing multi-dimensional data, the GIS community remains in need of a solution that simplifies interactions with the data, and elegantly fits with existing database schemas and dissemination protocols. This paper presents an information model that enables Geographic Information Systems (GIS) to efficiently catalog very large heterogeneous collections of geospatially-referenced multi-dimensional rasters—towards providing unified access to the resulting multivariate hypercubes. We show how the implementation of the model encapsulates format-specific variations and provides unified access to data along any dimension. We discuss how this framework lends itself to familiar GIS concepts like image mosaics, vector field visualization, layer animation, distributed data access via web services, and scientific computing. Global data sources like MODIS from USGS and HYCOM from NOAA illustrate how one would employ this framework for cataloging, querying, and intuitively visualizing such hypercubes. ArcGIS—an established platform for processing, analyzing, and visualizing geospatial data—serves to demonstrate how this integration brings the full power of GIS to the scientific community.

Multi-Band Light Curves from Two-Dimensional Simulations of Gamma-Ray Burst Afterglows

NASA Astrophysics Data System (ADS)

MacFadyen, Andrew

2010-01-01

The dynamics of gamma-ray burst outflows is inherently multi-dimensional. 1.) We present high resolution two-dimensional relativistic hydrodynamics simulations of GRBs in the afterglow phase using adaptive mesh refinement (AMR). Using standard synchrotron radiation models, we compute multi-band light curves, from the radio to X-ray, directly from the 2D hydrodynamics simulation data. We will present on-axis light curves for both constant density and wind media. We will also present off-axis light curves relevant for searches for orphan afterglows. We find that jet breaks are smoothed due to both off-axis viewing and wind media effects. 2.) Non-thermal radiation mechanisms in GRB afterglows require substantial magnetic field strengths. In turbulence driven by shear instabilities in relativistic magnetized gas, we demonstrate that magnetic field is naturally amplified to half a percent of the total energy (epsilon B = 0.005). We will show high resolution three dimensional relativistic MHD simulations of this process as well as particle in cell (PIC) simulations of mildly relativistic collisionless shocks.

Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

PubMed

Yamaguchi, Satoshi; Inoue, Sayuri; Sakai, Takahiko; Abe, Tomohiro; Kitagawa, Haruaki; Imazato, Satoshi

2017-05-01

The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p < 0.05). The in silico multi-scale model established in this study demonstrates that the Young's moduli, Poisson's ratios, and compressive strengths of CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.

Power-scaling performance of a three-dimensional tritium betavoltaic diode

NASA Astrophysics Data System (ADS)

Liu, Baojun; Chen, Kevin P.; Kherani, Nazir P.; Zukotynski, Stefan

2009-12-01

Three-dimensional diodes fabricated by electrochemical etching are exposed to tritium gas at pressures from 0.05 to 33 atm at room temperature to examine its power scaling performance. It is shown that the three-dimensional microporous structure overcomes the self-absorption limited saturation of beta flux at high tritium pressures. These results are contrasted against the three-dimensional device powered in one instance by tritium absorbed in the near surface region of the three-dimensional microporous network, and in another by a planar scandium tritide foil. These findings suggest that direct tritium occlusion in the near surface of three-dimensional diode can improve the specific power production.

The DSM-5 Dimensional Anxiety Scales in a Dutch non-clinical sample: psychometric properties including the adult separation anxiety disorder scale.

PubMed

Möller, Eline L; Bögels, Susan M

2016-09-01

With DSM-5, the American Psychiatric Association encourages complementing categorical diagnoses with dimensional severity ratings. We therefore examined the psychometric properties of the DSM-5 Dimensional Anxiety Scales, a set of brief dimensional scales that are consistent in content and structure and assess DSM-5-based core features of anxiety disorders. Participants (285 males, 255 females) completed the DSM-5 Dimensional Anxiety Scales for social anxiety disorder, generalized anxiety disorder, specific phobia, agoraphobia, and panic disorder that were included in previous studies on the scales, and also for separation anxiety disorder, which is included in the DSM-5 chapter on anxiety disorders. Moreover, they completed the Screen for Child Anxiety Related Emotional Disorders Adult version (SCARED-A). The DSM-5 Dimensional Anxiety Scales demonstrated high internal consistency, and the scales correlated significantly and substantially with corresponding SCARED-A subscales, supporting convergent validity. Separation anxiety appeared present among adults, supporting the DSM-5 recognition of separation anxiety as an anxiety disorder across the life span. To conclude, the DSM-5 Dimensional Anxiety Scales are a valuable tool to screen for specific adult anxiety disorders, including separation anxiety. Research in more diverse and clinical samples with anxiety disorders is needed. © 2016 The Authors International Journal of Methods in Psychiatric Research Published by John Wiley & Sons Ltd. © 2016 The Authors International Journal of Methods in Psychiatric Research Published by John Wiley & Sons Ltd.

Multi-scale image segmentation method with visual saliency constraints and its application

NASA Astrophysics Data System (ADS)

Chen, Yan; Yu, Jie; Sun, Kaimin

2018-03-01

Object-based image analysis method has many advantages over pixel-based methods, so it is one of the current research hotspots. It is very important to get the image objects by multi-scale image segmentation in order to carry out object-based image analysis. The current popular image segmentation methods mainly share the bottom-up segmentation principle, which is simple to realize and the object boundaries obtained are accurate. However, the macro statistical characteristics of the image areas are difficult to be taken into account, and fragmented segmentation (or over-segmentation) results are difficult to avoid. In addition, when it comes to information extraction, target recognition and other applications, image targets are not equally important, i.e., some specific targets or target groups with particular features worth more attention than the others. To avoid the problem of over-segmentation and highlight the targets of interest, this paper proposes a multi-scale image segmentation method with visually saliency graph constraints. Visual saliency theory and the typical feature extraction method are adopted to obtain the visual saliency information, especially the macroscopic information to be analyzed. The visual saliency information is used as a distribution map of homogeneity weight, where each pixel is given a weight. This weight acts as one of the merging constraints in the multi- scale image segmentation. As a result, pixels that macroscopically belong to the same object but are locally different can be more likely assigned to one same object. In addition, due to the constraint of visual saliency model, the constraint ability over local-macroscopic characteristics can be well controlled during the segmentation process based on different objects. These controls will improve the completeness of visually saliency areas in the segmentation results while diluting the controlling effect for non- saliency background areas. Experiments show that this method works

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

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

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

Layer-by-layer assembly of two-dimensional materials into wafer-scale heterostructures

NASA Astrophysics Data System (ADS)

Kang, Kibum; Lee, Kan-Heng; Han, Yimo; Gao, Hui; Xie, Saien; Muller, David A.; Park, Jiwoong

2017-10-01

High-performance semiconductor films with vertical compositions that are designed to atomic-scale precision provide the foundation for modern integrated circuitry and novel materials discovery. One approach to realizing such films is sequential layer-by-layer assembly, whereby atomically thin two-dimensional building blocks are vertically stacked, and held together by van der Waals interactions. With this approach, graphene and transition-metal dichalcogenides--which represent one- and three-atom-thick two-dimensional building blocks, respectively--have been used to realize previously inaccessible heterostructures with interesting physical properties. However, no large-scale assembly method exists at present that maintains the intrinsic properties of these two-dimensional building blocks while producing pristine interlayer interfaces, thus limiting the layer-by-layer assembly method to small-scale proof-of-concept demonstrations. Here we report the generation of wafer-scale semiconductor films with a very high level of spatial uniformity and pristine interfaces. The vertical composition and properties of these films are designed at the atomic scale using layer-by-layer assembly of two-dimensional building blocks under vacuum. We fabricate several large-scale, high-quality heterostructure films and devices, including superlattice films with vertical compositions designed layer-by-layer, batch-fabricated tunnel device arrays with resistances that can be tuned over four orders of magnitude, band-engineered heterostructure tunnel diodes, and millimetre-scale ultrathin membranes and windows. The stacked films are detachable, suspendable and compatible with water or plastic surfaces, which will enable their integration with advanced optical and mechanical systems.

Layer-by-layer assembly of two-dimensional materials into wafer-scale heterostructures.

PubMed

Kang, Kibum; Lee, Kan-Heng; Han, Yimo; Gao, Hui; Xie, Saien; Muller, David A; Park, Jiwoong

2017-10-12

High-performance semiconductor films with vertical compositions that are designed to atomic-scale precision provide the foundation for modern integrated circuitry and novel materials discovery. One approach to realizing such films is sequential layer-by-layer assembly, whereby atomically thin two-dimensional building blocks are vertically stacked, and held together by van der Waals interactions. With this approach, graphene and transition-metal dichalcogenides-which represent one- and three-atom-thick two-dimensional building blocks, respectively-have been used to realize previously inaccessible heterostructures with interesting physical properties. However, no large-scale assembly method exists at present that maintains the intrinsic properties of these two-dimensional building blocks while producing pristine interlayer interfaces, thus limiting the layer-by-layer assembly method to small-scale proof-of-concept demonstrations. Here we report the generation of wafer-scale semiconductor films with a very high level of spatial uniformity and pristine interfaces. The vertical composition and properties of these films are designed at the atomic scale using layer-by-layer assembly of two-dimensional building blocks under vacuum. We fabricate several large-scale, high-quality heterostructure films and devices, including superlattice films with vertical compositions designed layer-by-layer, batch-fabricated tunnel device arrays with resistances that can be tuned over four orders of magnitude, band-engineered heterostructure tunnel diodes, and millimetre-scale ultrathin membranes and windows. The stacked films are detachable, suspendable and compatible with water or plastic surfaces, which will enable their integration with advanced optical and mechanical systems.

Finite-size scaling of clique percolation on two-dimensional Moore lattices

NASA Astrophysics Data System (ADS)

Dong, Jia-Qi; Shen, Zhou; Zhang, Yongwen; Huang, Zi-Gang; Huang, Liang; Chen, Xiaosong

2018-05-01

Clique percolation has attracted much attention due to its significance in understanding topological overlap among communities and dynamical instability of structured systems. Rich critical behavior has been observed in clique percolation on Erdős-Rényi (ER) random graphs, but few works have discussed clique percolation on finite dimensional systems. In this paper, we have defined a series of characteristic events, i.e., the historically largest size jumps of the clusters, in the percolating process of adding bonds and developed a new finite-size scaling scheme based on the interval of the characteristic events. Through the finite-size scaling analysis, we have found, interestingly, that, in contrast to the clique percolation on an ER graph where the critical exponents are parameter dependent, the two-dimensional (2D) clique percolation simply shares the same critical exponents with traditional site or bond percolation, independent of the clique percolation parameters. This has been corroborated by bridging two special types of clique percolation to site percolation on 2D lattices. Mechanisms for the difference of the critical behaviors between clique percolation on ER graphs and on 2D lattices are also discussed.

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.

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success.

PubMed

Yankeelov, Thomas E; An, Gary; Saut, Oliver; Luebeck, E Georg; Popel, Aleksander S; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A; Ye, Kaiming; Genin, Guy M

2016-09-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology.

Multi-scale Modeling in Clinical Oncology: Opportunities and Barriers to Success

PubMed Central

Yankeelov, Thomas E.; An, Gary; Saut, Oliver; Luebeck, E. Georg; Popel, Aleksander S.; Ribba, Benjamin; Vicini, Paolo; Zhou, Xiaobo; Weis, Jared A.; Ye, Kaiming; Genin, Guy M.

2016-01-01

Hierarchical processes spanning several orders of magnitude of both space and time underlie nearly all cancers. Multi-scale statistical, mathematical, and computational modeling methods are central to designing, implementing and assessing treatment strategies that account for these hierarchies. The basic science underlying these modeling efforts is maturing into a new discipline that is close to influencing and facilitating clinical successes. The purpose of this review is to capture the state-of-the-art as well as the key barriers to success for multi-scale modeling in clinical oncology. We begin with a summary of the long-envisioned promise of multi-scale modeling in clinical oncology, including the synthesis of disparate data types into models that reveal underlying mechanisms and allow for experimental testing of hypotheses. We then evaluate the mathematical techniques employed most widely and present several examples illustrating their application as well as the current gap between pre-clinical and clinical applications. We conclude with a discussion of what we view to be the key challenges and opportunities for multi-scale modeling in clinical oncology. PMID:27384942

Voluntary EMG-to-force estimation with a multi-scale physiological muscle model

PubMed Central

2013-01-01

Background EMG-to-force estimation based on muscle models, for voluntary contraction has many applications in human motion analysis. The so-called Hill model is recognized as a standard model for this practical use. However, it is a phenomenological model whereby muscle activation, force-length and force-velocity properties are considered independently. Perreault reported Hill modeling errors were large for different firing frequencies, level of activation and speed of contraction. It may be due to the lack of coupling between activation and force-velocity properties. In this paper, we discuss EMG-force estimation with a multi-scale physiology based model, which has a link to underlying crossbridge dynamics. Differently from the Hill model, the proposed method provides dual dynamics of recruitment and calcium activation. Methods The ankle torque was measured for the plantar flexion along with EMG measurements of the medial gastrocnemius (GAS) and soleus (SOL). In addition to Hill representation of the passive elements, three models of the contractile parts have been compared. Using common EMG signals during isometric contraction in four able-bodied subjects, torque was estimated by the linear Hill model, the nonlinear Hill model and the multi-scale physiological model that refers to Huxley theory. The comparison was made in normalized scale versus the case in maximum voluntary contraction. Results The estimation results obtained with the multi-scale model showed the best performances both in fast-short and slow-long term contraction in randomized tests for all the four subjects. The RMS errors were improved with the nonlinear Hill model compared to linear Hill, however it showed limitations to account for the different speed of contractions. Average error was 16.9% with the linear Hill model, 9.3% with the modified Hill model. In contrast, the error in the multi-scale model was 6.1% while maintaining a uniform estimation performance in both fast and slow

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

Lithium Depletion in Solar-like Stars: Effect of Overshooting Based on Realistic Multi-dimensional Simulations

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

Baraffe, I.; Pratt, J.; Goffrey, T.

We study lithium depletion in low-mass and solar-like stars as a function of time, using a new diffusion coefficient describing extra-mixing taking place at the bottom of a convective envelope. This new form is motivated by multi-dimensional fully compressible, time-implicit hydrodynamic simulations performed with the MUSIC code. Intermittent convective mixing at the convective boundary in a star can be modeled using extreme value theory, a statistical analysis frequently used for finance, meteorology, and environmental science. In this Letter, we implement this statistical diffusion coefficient in a one-dimensional stellar evolution code, using parameters calibrated from multi-dimensional hydrodynamic simulations of a youngmore » low-mass star. We propose a new scenario that can explain observations of the surface abundance of lithium in the Sun and in clusters covering a wide range of ages, from ∼50 Myr to ∼4 Gyr. Because it relies on our physical model of convective penetration, this scenario has a limited number of assumptions. It can explain the observed trend between rotation and depletion, based on a single additional assumption, namely, that rotation affects the mixing efficiency at the convective boundary. We suggest the existence of a threshold in stellar rotation rate above which rotation strongly prevents the vertical penetration of plumes and below which rotation has small effects. In addition to providing a possible explanation for the long-standing problem of lithium depletion in pre-main-sequence and main-sequence stars, the strength of our scenario is that its basic assumptions can be tested by future hydrodynamic simulations.« less

Lithium Depletion in Solar-like Stars: Effect of Overshooting Based on Realistic Multi-dimensional Simulations

NASA Astrophysics Data System (ADS)

Baraffe, I.; Pratt, J.; Goffrey, T.; Constantino, T.; Folini, D.; Popov, M. V.; Walder, R.; Viallet, M.

2017-08-01

We study lithium depletion in low-mass and solar-like stars as a function of time, using a new diffusion coefficient describing extra-mixing taking place at the bottom of a convective envelope. This new form is motivated by multi-dimensional fully compressible, time-implicit hydrodynamic simulations performed with the MUSIC code. Intermittent convective mixing at the convective boundary in a star can be modeled using extreme value theory, a statistical analysis frequently used for finance, meteorology, and environmental science. In this Letter, we implement this statistical diffusion coefficient in a one-dimensional stellar evolution code, using parameters calibrated from multi-dimensional hydrodynamic simulations of a young low-mass star. We propose a new scenario that can explain observations of the surface abundance of lithium in the Sun and in clusters covering a wide range of ages, from ˜50 Myr to ˜4 Gyr. Because it relies on our physical model of convective penetration, this scenario has a limited number of assumptions. It can explain the observed trend between rotation and depletion, based on a single additional assumption, namely, that rotation affects the mixing efficiency at the convective boundary. We suggest the existence of a threshold in stellar rotation rate above which rotation strongly prevents the vertical penetration of plumes and below which rotation has small effects. In addition to providing a possible explanation for the long-standing problem of lithium depletion in pre-main-sequence and main-sequence stars, the strength of our scenario is that its basic assumptions can be tested by future hydrodynamic simulations.

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

Multi-dimensional mesoscale simulations of detonation initiation in energetic materials with density-based kinetics

NASA Astrophysics Data System (ADS)

Jackson, Thomas Luther; Jost, Antoine M. D.; Zhang, Ju; Sridharan, Prashanth; Amadio, Guilherme

2018-03-01

In this work we present multi-dimensional mesoscale simulations of detonation initiation in energetic materials. We solve the reactive Euler equations, with the energy equation augmented by a power deposition term. The reaction rate at the mesoscale is modelled using density-based kinetics, while the deposition term is based on simulations of void collapse at the microscale, modelled at the mesoscale as hot spots. We carry out two- and three-dimensional mesoscale simulations of random packs of HMX crystals in a binder, and show that transition between no-detonation and detonation depends on the number density of the hot spots, the packing fraction, and the post-shock pressure of an imposed shock. In particular, we show that, for a fixed post-shock pressure, there exists a critical value of the number density of hot spots, such that when the number density is below this value a detonation wave will not develop. We highlight the importance of morphology to initiation by comparing with a homogeneous counterpart, and we compare relevant length scales by examining their corresponding power spectra. We also examine the effect of packing fraction and show that at low post-shock pressures there is significant variation in the initiation times, but that this variation disappears as the post-shock pressure is increased. Finally, we compare three-dimensional simulations with the experimental data, and show that the model is capable of qualitatively reproducing the trends shown in the data.

Cross-Domain Multi-View Object Retrieval via Multi-Scale Topic Models.

PubMed

Hong, Richang; Hu, Zhenzhen; Wang, Ruxin; Wang, Meng; Tao, Dacheng

2016-09-27

The increasing number of 3D objects in various applications has increased the requirement for effective and efficient 3D object retrieval methods, which attracted extensive research efforts in recent years. Existing works mainly focus on how to extract features and conduct object matching. With the increasing applications, 3D objects come from different areas. In such circumstances, how to conduct object retrieval becomes more important. To address this issue, we propose a multi-view object retrieval method using multi-scale topic models in this paper. In our method, multiple views are first extracted from each object, and then the dense visual features are extracted to represent each view. To represent the 3D object, multi-scale topic models are employed to extract the hidden relationship among these features with respected to varied topic numbers in the topic model. In this way, each object can be represented by a set of bag of topics. To compare the objects, we first conduct topic clustering for the basic topics from two datasets, and then generate the common topic dictionary for new representation. Then, the two objects can be aligned to the same common feature space for comparison. To evaluate the performance of the proposed method, experiments are conducted on two datasets. The 3D object retrieval experimental results and comparison with existing methods demonstrate the effectiveness of the proposed method.

Data fusion of multi-scale representations for structural damage detection

NASA Astrophysics Data System (ADS)

Guo, Tian; Xu, Zili

2018-01-01

Despite extensive researches into structural health monitoring (SHM) in the past decades, there are few methods that can detect multiple slight damage in noisy environments. Here, we introduce a new hybrid method that utilizes multi-scale space theory and data fusion approach for multiple damage detection in beams and plates. A cascade filtering approach provides multi-scale space for noisy mode shapes and filters the fluctuations caused by measurement noise. In multi-scale space, a series of amplification and data fusion algorithms are utilized to search the damage features across all possible scales. We verify the effectiveness of the method by numerical simulation using damaged beams and plates with various types of boundary conditions. Monte Carlo simulations are conducted to illustrate the effectiveness and noise immunity of the proposed method. The applicability is further validated via laboratory cases studies focusing on different damage scenarios. Both results demonstrate that the proposed method has a superior noise tolerant ability, as well as damage sensitivity, without knowing material properties or boundary conditions.

A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models.

PubMed

Lu, Pei; Xia, Jun; Li, Zhicheng; Xiong, Jing; Yang, Jian; Zhou, Shoujun; Wang, Lei; Chen, Mingyang; Wang, Cheng

2016-11-08

Accurate segmentation of blood vessels plays an important role in the computer-aided diagnosis and interventional treatment of vascular diseases. The statistical method is an important component of effective vessel segmentation; however, several limitations discourage the segmentation effect, i.e., dependence of the image modality, uneven contrast media, bias field, and overlapping intensity distribution of the object and background. In addition, the mixture models of the statistical methods are constructed relaying on the characteristics of the image histograms. Thus, it is a challenging issue for the traditional methods to be available in vessel segmentation from multi-modality angiographic images. To overcome these limitations, a flexible segmentation method with a fixed mixture model has been proposed for various angiography modalities. Our method mainly consists of three parts. Firstly, multi-scale filtering algorithm was used on the original images to enhance vessels and suppress noises. As a result, the filtered data achieved a new statistical characteristic. Secondly, a mixture model formed by three probabilistic distributions (two Exponential distributions and one Gaussian distribution) was built to fit the histogram curve of the filtered data, where the expectation maximization (EM) algorithm was used for parameters estimation. Finally, three-dimensional (3D) Markov random field (MRF) were employed to improve the accuracy of pixel-wise classification and posterior probability estimation. To quantitatively evaluate the performance of the proposed method, two phantoms simulating blood vessels with different tubular structures and noises have been devised. Meanwhile, four clinical angiographic data sets from different human organs have been used to qualitatively validate the method. To further test the performance, comparison tests between the proposed method and the traditional ones have been conducted on two different brain magnetic resonance angiography

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.

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

PubMed

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

Secure coherent optical multi-carrier system with four-dimensional modulation space and Stokes vector scrambling.

PubMed

Zhang, Lijia; Liu, Bo; Xin, Xiangjun

2015-06-15

A secure enhanced coherent optical multi-carrier system based on Stokes vector scrambling is proposed and experimentally demonstrated. The optical signal with four-dimensional (4D) modulation space has been scrambled intra- and inter-subcarriers, where a multi-layer logistic map is adopted as the chaotic model. An experiment with 61.71-Gb/s encrypted multi-carrier signal is successfully demonstrated with the proposed method. The results indicate a promising solution for the physical secure optical communication.

Simulating Nationwide Pandemics: Applying the Multi-scale Epidemiologic Simulation and Analysis System to Human Infectious Diseases

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

Dombroski, M; Melius, C; Edmunds, T

2008-09-24

This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to humanmore » epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in

Toward a global multi-scale heliophysics observatory

NASA Astrophysics Data System (ADS)

Semeter, J. L.

2017-12-01

We live within the only known stellar-planetary system that supports life. What we learn about this system is not only relevant to human society and its expanding reach beyond Earth's surface, but also to our understanding of the origins and evolution of life in the universe. Heliophysics is focused on solar-terrestrial interactions mediated by the magnetic and plasma environment surrounding the planet. A defining feature of energy flow through this environment is interaction across physical scales. A solar disturbance aimed at Earth can excite geospace variability on scales ranging from thousands of kilometers (e.g., global convection, region 1 and 2 currents, electrojet intensifications) to 10's of meters (e.g., equatorial spread-F, dispersive Alfven waves, plasma instabilities). Most "geospace observatory" concepts are focused on a single modality (e.g., HF/UHF radar, magnetometer, optical) providing a limited parameter set over a particular spatiotemporal resolution. Data assimilation methods have been developed to couple heterogeneous and distributed observations, but resolution has typically been prescribed a-priori and according to physical assumptions. This paper develops a conceptual framework for the next generation multi-scale heliophysics observatory, capable of revealing and quantifying the complete spectrum of cross-scale interactions occurring globally within the geospace system. The envisioned concept leverages existing assets, enlists citizen scientists, and exploits low-cost access to the geospace environment. Examples are presented where distributed multi-scale observations have resulted in substantial new insight into the inner workings of our stellar-planetary system.

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.

Multiscale multifractal detrended-fluctuation analysis of two-dimensional surfaces

NASA Astrophysics Data System (ADS)

Wang, Fang; Fan, Qingju; Stanley, H. Eugene

2016-04-01

Two-dimensional (2D) multifractal detrended fluctuation analysis (MF-DFA) has been used to study monofractality and multifractality on 2D surfaces, but when it is used to calculate the generalized Hurst exponent in a fixed time scale, the presence of crossovers can bias the outcome. To solve this problem, multiscale multifractal analysis (MMA) was recent employed in a one-dimensional case. MMA produces a Hurst surface h (q ,s ) that provides a spectrum of local scaling exponents at different scale ranges such that the positions of the crossovers can be located. We apply this MMA method to a 2D surface and identify factors that influence the results. We generate several synthesized surfaces and find that crossovers are consistently present, which means that their fractal properties differ at different scales. We apply MMA to the surfaces, and the results allow us to observe these differences and accurately estimate the generalized Hurst exponents. We then study eight natural texture images and two real-world images and find (i) that the moving window length (WL) and the slide length (SL) are the key parameters in the MMA method, that the WL more strongly influences the Hurst surface than the SL, and that the combination of WL =4 and SL =4 is optimal for a 2D image; (ii) that the robustness of h (2 ,s ) to four common noises is high at large scales but variable at small scales; and (iii) that the long-term correlations in the images weaken as the intensity of Gaussian noise and salt and pepper noise is increased. Our findings greatly improve the performance of the MMA method on 2D surfaces.

Multi-scale curvature for automated identification of glaciated mountain landscapes

NASA Astrophysics Data System (ADS)

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-03-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.

Multi-scale curvature for automated identification of glaciated mountain landscapes☆

PubMed Central

Prasicek, Günther; Otto, Jan-Christoph; Montgomery, David R.; Schrott, Lothar

2014-01-01

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes. PMID:24748703

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.

Large-scale three-dimensional phase-field simulations for phase coarsening at ultrahigh volume fraction on high-performance architectures

NASA Astrophysics Data System (ADS)

Yan, Hui; Wang, K. G.; Jones, Jim E.

2016-06-01

A parallel algorithm for large-scale three-dimensional phase-field simulations of phase coarsening is developed and implemented on high-performance architectures. From the large-scale simulations, a new kinetics in phase coarsening in the region of ultrahigh volume fraction is found. The parallel implementation is capable of harnessing the greater computer power available from high-performance architectures. The parallelized code enables increase in three-dimensional simulation system size up to a 5123 grid cube. Through the parallelized code, practical runtime can be achieved for three-dimensional large-scale simulations, and the statistical significance of the results from these high resolution parallel simulations are greatly improved over those obtainable from serial simulations. A detailed performance analysis on speed-up and scalability is presented, showing good scalability which improves with increasing problem size. In addition, a model for prediction of runtime is developed, which shows a good agreement with actual run time from numerical tests.

Multi-scale diffuse interface modeling of multi-component two-phase flow with partial miscibility

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

Kou, Jisheng; Sun, Shuyu, E-mail: shuyu.sun@kaust.edu.sa; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049

2016-08-01

In this paper, we introduce a diffuse interface model to simulate multi-component two-phase flow with partial miscibility based on a realistic equation of state (e.g. Peng–Robinson equation of state). Because of partial miscibility, thermodynamic relations are used to model not only interfacial properties but also bulk properties, including density, composition, pressure, and realistic viscosity. As far as we know, this effort is the first time to use diffuse interface modeling based on equation of state for modeling of multi-component two-phase flow with partial miscibility. In numerical simulation, the key issue is to resolve the high contrast of scales from themore » microscopic interface composition to macroscale bulk fluid motion since the interface has a nanoscale thickness only. To efficiently solve this challenging problem, we develop a multi-scale simulation method. At the microscopic scale, we deduce a reduced interfacial equation under reasonable assumptions, and then we propose a formulation of capillary pressure, which is consistent with macroscale flow equations. Moreover, we show that Young–Laplace equation is an approximation of this capillarity formulation, and this formulation is also consistent with the concept of Tolman length, which is a correction of Young–Laplace equation. At the macroscopical scale, the interfaces are treated as discontinuous surfaces separating two phases of fluids. Our approach differs from conventional sharp-interface two-phase flow model in that we use the capillary pressure directly instead of a combination of surface tension and Young–Laplace equation because capillarity can be calculated from our proposed capillarity formulation. A compatible condition is also derived for the pressure in flow equations. Furthermore, based on the proposed capillarity formulation, we design an efficient numerical method for directly computing the capillary pressure between two fluids composed of multiple components. Finally

Multi-temporal Scale Analysis of Environmental Control on Net Ecosystem Exchange of CO2 in Forest Ecosystems

NASA Astrophysics Data System (ADS)

Zhang, Mi; Yu, Guirui; Zhuang, Jie; Gentry, Randy; Koirala, Shesh; Zhang, Leiming; Sun, Xiaomin; Han, Shijie; Yan, Junhua

2013-04-01

Multi-temporal scale analysis of environmental control on forest ecosystem carbon budget is a basis for understanding the responses and adaptation of forest carbon cycle to climate change. In this study, we chose two typical forest ecosystems, Changbaishan temperate mixed forest (CBS) in northeastern China and Dinghushan subtropical evergreen broad-leaved forest (DHS) in southern China to identify the changes in environmental control on net ecosystem exchange of carbon dioxide (NEE) with the temporal scales. The analysis was made based on the flux and routine meteorological data measured during the period from 2005 to 2008. These time series data were analyzed using wavelet and cross wavelet transform. The results showed that NEE had significant daily and annual periodic variation in the two types of forest ecosystem. NEE at CBS and DHS showed semi-annual (176 days) and seasonal (88-104 days) periodic variations, respectively. Photosynthetically active radiation (PAR), vapor pressure deficient (VPD), air temperature (Ta), soil temperature (Ts, at 5-cm depth) controlled daily variation of NEE as indicated by the significant high common power of cross wavelet transform spectrums between NEE and these factors. Similarly, Ta, VPD, and precipitation (P) controlled annual variation of NEE at CBS. However, Ta, PAR, and soil water content (SWC, at 5-cm depth) dominated the annual variation of NEE at DHS. An anti-phase between NEE and PAR at daily scale in the two forest ecosystems demonstrated an agreement of the variation of NEE with PAR, with rising sunlight corresponding with increased net carbon uptake. At annual scale, phase angles between NEE and Ta and between NEE and P were -170° and 176°, respectively at CBS. At DHS, phase angle between NEE and VPD was smallest at annual scale. The results indicated that the peak of net carbon uptake seasonal variation and the peaks of P and Ta seasonal variations occurred at the same month at CBS. But, at DHS, seasonal

Universal scaling laws of diffusion in two-dimensional granular liquids.

PubMed

Wang, Chen-Hung; Yu, Szu-Hsuan; Chen, Peilong

2015-06-01

We find, in a two-dimensional air table granular system, that the reduced diffusion constant D* and excess entropy S(2) follow two distinct scaling laws: D*∼e(S(2)*) for dense liquids and D∼e(3S(2)*) for dilute ones. The scaling for dense liquids is very similar to that for three-dimensional liquids proposed previously [M. Dzugutov, Nature (London) 381, 137 (1996); A. Samanta et al., Phys. Rev. Lett. 92, 145901 (2004)]. In the dilute regime, a power law [Y. Rosenfeld, J. Phys.: Condens. Matter 11, 5415 (1999)] also fits our data reasonably well. In our system, particles experience low air drag dissipation and interact with each others through embedded magnets. These near-conservative many-body interactions are responsible for the measured Gaussian velocity distribution functions and the scaling laws. The dominance of cage relaxations in dense liquids leads to the different scaling laws for dense and dilute regimes.

Multi-scale Modeling of the Impact Response of a Strain Rate Sensitive High-Manganese Austenitic Steel

NASA Astrophysics Data System (ADS)

Önal, Orkun; Ozmenci, Cemre; Canadinc, Demircan

2014-09-01

A multi-scale modeling approach was applied to predict the impact response of a strain rate sensitive high-manganese austenitic steel. The roles of texture, geometry and strain rate sensitivity were successfully taken into account all at once by coupling crystal plasticity and finite element (FE) analysis. Specifically, crystal plasticity was utilized to obtain the multi-axial flow rule at different strain rates based on the experimental deformation response under uniaxial tensile loading. The equivalent stress - equivalent strain response was then incorporated into the FE model for the sake of a more representative hardening rule under impact loading. The current results demonstrate that reliable predictions can be obtained by proper coupling of crystal plasticity and FE analysis even if the experimental flow rule of the material is acquired under uniaxial loading and at moderate strain rates that are significantly slower than those attained during impact loading. Furthermore, the current findings also demonstrate the need for an experiment-based multi-scale modeling approach for the sake of reliable predictions of the impact response.

Leveraging unsupervised training sets for multi-scale compartmentalization in renal pathology

NASA Astrophysics Data System (ADS)

Lutnick, Brendon; Tomaszewski, John E.; Sarder, Pinaki

2017-03-01

Clinical pathology relies on manual compartmentalization and quantification of biological structures, which is time consuming and often error-prone. Application of computer vision segmentation algorithms to histopathological image analysis, in contrast, can offer fast, reproducible, and accurate quantitative analysis to aid pathologists. Algorithms tunable to different biologically relevant structures can allow accurate, precise, and reproducible estimates of disease states. In this direction, we have developed a fast, unsupervised computational method for simultaneously separating all biologically relevant structures from histopathological images in multi-scale. Segmentation is achieved by solving an energy optimization problem. Representing the image as a graph, nodes (pixels) are grouped by minimizing a Potts model Hamiltonian, adopted from theoretical physics, modeling interacting electron spins. Pixel relationships (modeled as edges) are used to update the energy of the partitioned graph. By iteratively improving the clustering, the optimal number of segments is revealed. To reduce computational time, the graph is simplified using a Cantor pairing function to intelligently reduce the number of included nodes. The classified nodes are then used to train a multiclass support vector machine to apply the segmentation over the full image. Accurate segmentations of images with as many as 106 pixels can be completed only in 5 sec, allowing for attainable multi-scale visualization. To establish clinical potential, we employed our method in renal biopsies to quantitatively visualize for the first time scale variant compartments of heterogeneous intra- and extraglomerular structures simultaneously. Implications of the utility of our method extend to fields such as oncology, genomics, and non-biological problems.

Entangled time in flocking: Multi-time-scale interaction reveals emergence of inherent noise

PubMed Central

Murakami, Hisashi

2018-01-01

Collective behaviors that seem highly ordered and result in collective alignment, such as schooling by fish and flocking by birds, arise from seamless shuffling (such as super-diffusion) and bustling inside groups (such as Lévy walks). However, such noisy behavior inside groups appears to preclude the collective behavior: intuitively, we expect that noisy behavior would lead to the group being destabilized and broken into small sub groups, and high alignment seems to preclude shuffling of neighbors. Although statistical modeling approaches with extrinsic noise, such as the maximum entropy approach, have provided some reasonable descriptions, they ignore the cognitive perspective of the individuals. In this paper, we try to explain how the group tendency, that is, high alignment, and highly noisy individual behavior can coexist in a single framework. The key aspect of our approach is multi-time-scale interaction emerging from the existence of an interaction radius that reflects short-term and long-term predictions. This multi-time-scale interaction is a natural extension of the attraction and alignment concept in many flocking models. When we apply this method in a two-dimensional model, various flocking behaviors, such as swarming, milling, and schooling, emerge. The approach also explains the appearance of super-diffusion, the Lévy walk in groups, and local equilibria. At the end of this paper, we discuss future developments, including extending our model to three dimensions. PMID:29689074

Multi-Scale Characterization of Orthotropic Microstructures

DTIC Science & Technology

2008-04-01

D. Valiveti, S. J. Harris, J. Boileau, A domain partitioning based pre-processor for multi-scale modelling of cast aluminium alloys , Modelling and...SUPPLEMENTARY NOTES Journal article submitted to Modeling and Simulation in Materials Science and Engineering. PAO Case Number: WPAFB 08-3362...element for charac- terization or simulation to avoid misleading predictions of macroscopic defor- mation, fracture, or transport behavior. Likewise

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation

NASA Astrophysics Data System (ADS)

Sakamoto, M.; Honda, Y.; Kondo, A.

2016-06-01

From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.

Stability analysis for a multi-camera photogrammetric system.

PubMed

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-08-18

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction.

Stability Analysis for a Multi-Camera Photogrammetric System

PubMed Central

Habib, Ayman; Detchev, Ivan; Kwak, Eunju

2014-01-01

Consumer-grade digital cameras suffer from geometrical instability that may cause problems when used in photogrammetric applications. This paper provides a comprehensive review of this issue of interior orientation parameter variation over time, it explains the common ways used for coping with the issue, and describes the existing methods for performing stability analysis for a single camera. The paper then points out the lack of coverage of stability analysis for multi-camera systems, suggests a modification of the collinearity model to be used for the calibration of an entire photogrammetric system, and proposes three methods for system stability analysis. The proposed methods explore the impact of the changes in interior orientation and relative orientation/mounting parameters on the reconstruction process. Rather than relying on ground truth in real datasets to check the system calibration stability, the proposed methods are simulation-based. Experiment results are shown, where a multi-camera photogrammetric system was calibrated three times, and stability analysis was performed on the system calibration parameters from the three sessions. The proposed simulation-based methods provided results that were compatible with a real-data based approach for evaluating the impact of changes in the system calibration parameters on the three-dimensional reconstruction. PMID:25196012

Accurate complex scaling of three dimensional numerical potentials

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

Cerioni, Alessandro; Genovese, Luigi; Duchemin, Ivan

2013-05-28

The complex scaling method, which consists in continuing spatial coordinates into the complex plane, is a well-established method that allows to compute resonant eigenfunctions of the time-independent Schroedinger operator. Whenever it is desirable to apply the complex scaling to investigate resonances in physical systems defined on numerical discrete grids, the most direct approach relies on the application of a similarity transformation to the original, unscaled Hamiltonian. We show that such an approach can be conveniently implemented in the Daubechies wavelet basis set, featuring a very promising level of generality, high accuracy, and no need for artificial convergence parameters. Complex scalingmore » of three dimensional numerical potentials can be efficiently and accurately performed. By carrying out an illustrative resonant state computation in the case of a one-dimensional model potential, we then show that our wavelet-based approach may disclose new exciting opportunities in the field of computational non-Hermitian quantum mechanics.« less

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale

PubMed Central

Schut, Marc; Hermans, Frans; van Asten, Piet; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs–local-level actors–left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts. PMID:29870559

Effects of multi-stakeholder platforms on multi-stakeholder innovation networks: Implications for research for development interventions targeting innovations at scale.

PubMed

Sartas, Murat; Schut, Marc; Hermans, Frans; Asten, Piet van; Leeuwis, Cees

2018-01-01

Multi-stakeholder platforms (MSPs) have been playing an increasing role in interventions aiming to generate and scale innovations in agricultural systems. However, the contribution of MSPs in achieving innovations and scaling has been varied, and many factors have been reported to be important for their performance. This paper aims to provide evidence on the contribution of MSPs to innovation and scaling by focusing on three developing country cases in Burundi, Democratic Republic of Congo, and Rwanda. Through social network analysis and logistic models, the paper studies the changes in the characteristics of multi-stakeholder innovation networks targeted by MSPs and identifies factors that play significant roles in triggering these changes. The results demonstrate that MSPs do not necessarily expand and decentralize innovation networks but can lead to contraction and centralization in the initial years of implementation. They show that some of the intended next users of interventions with MSPs-local-level actors-left the innovation networks, whereas the lead organization controlling resource allocation in the MSPs substantially increased its centrality. They also indicate that not all the factors of change in innovation networks are country specific. Initial conditions of innovation networks and funding provided by the MSPs are common factors explaining changes in innovation networks across countries and across different network functions. The study argues that investigating multi-stakeholder innovation network characteristics targeted by the MSP using a network approach in early implementation can contribute to better performance in generating and scaling innovations, and that funding can be an effective implementation tool in developing country contexts.

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.

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Manipon, G.; Hua, H.

2012-12-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

Large-Scale, Parallel, Multi-Sensor Data Fusion in the Cloud

NASA Astrophysics Data System (ADS)

Wilson, B.; Manipon, G.; Hua, H.

2012-04-01

NASA's Earth Observing System (EOS) is an ambitious facility for studying global climate change. The mandate now is to combine measurements from the instruments on the "A-Train" platforms (AIRS, AMSR-E, MODIS, MISR, MLS, and CloudSat) and other Earth probes to enable large-scale studies of climate change over periods of years to decades. However, moving from predominantly single-instrument studies to a multi-sensor, measurement-based model for long-duration analysis of important climate variables presents serious challenges for large-scale data mining and data fusion. For example, one might want to compare temperature and water vapor retrievals from one instrument (AIRS) to another instrument (MODIS), and to a model (ECMWF), stratify the comparisons using a classification of the "cloud scenes" from CloudSat, and repeat the entire analysis over years of AIRS data. To perform such an analysis, one must discover & access multiple datasets from remote sites, find the space/time "matchups" between instruments swaths and model grids, understand the quality flags and uncertainties for retrieved physical variables, assemble merged datasets, and compute fused products for further scientific and statistical analysis. To efficiently assemble such decade-scale datasets in a timely manner, we are utilizing Elastic Computing in the Cloud and parallel map/reduce-based algorithms. "SciReduce" is a Hadoop-like parallel analysis system, programmed in parallel python, that is designed from the ground up for Earth science. SciReduce executes inside VMWare images and scales to any number of nodes in the Cloud. Unlike Hadoop, in which simple tuples (keys & values) are passed between the map and reduce functions, SciReduce operates on bundles of named numeric arrays, which can be passed in memory or serialized to disk in netCDF4 or HDF5. Thus, SciReduce uses the native datatypes (geolocated grids, swaths, and points) that geo-scientists are familiar with. We are deploying within Sci

Overview of NASA Multi-dimensional Stirling Convertor Code Development and Validation Effort

NASA Technical Reports Server (NTRS)

Tew, Roy C.; Cairelli, James E.; Ibrahim, Mounir B.; Simon, Terrence W.; Gedeon, David

2002-01-01

A NASA grant has been awarded to Cleveland State University (CSU) to develop a multi-dimensional (multi-D) Stirling computer code with the goals of improving loss predictions and identifying component areas for improvements. The University of Minnesota (UMN) and Gedeon Associates are teamed with CSU. Development of test rigs at UMN and CSU and validation of the code against test data are part of the effort. The one-dimensional (1-D) Stirling codes used for design and performance prediction do not rigorously model regions of the working space where abrupt changes in flow area occur (such as manifolds and other transitions between components). Certain hardware experiences have demonstrated large performance gains by varying manifolds and heat exchanger designs to improve flow distributions in the heat exchangers. 1-D codes were not able to predict these performance gains. An accurate multi-D code should improve understanding of the effects of area changes along the main flow axis, sensitivity of performance to slight changes in internal geometry, and, in general, the understanding of various internal thermodynamic losses. The commercial CFD-ACE code has been chosen for development of the multi-D code. This 2-D/3-D code has highly developed pre- and post-processors, and moving boundary capability. Preliminary attempts at validation of CFD-ACE models of MIT gas spring and "two space" test rigs were encouraging. Also, CSU's simulations of the UMN oscillating-flow fig compare well with flow visualization results from UMN. A complementary Department of Energy (DOE) Regenerator Research effort is aiding in development of regenerator matrix models that will be used in the multi-D Stirling code. This paper reports on the progress and challenges of this

Salient object detection based on multi-scale contrast.

PubMed

Wang, Hai; Dai, Lei; Cai, Yingfeng; Sun, Xiaoqiang; Chen, Long

2018-05-01

Due to the development of deep learning networks, a salient object detection based on deep learning networks, which are used to extract the features, has made a great breakthrough compared to the traditional methods. At present, the salient object detection mainly relies on very deep convolutional network, which is used to extract the features. In deep learning networks, an dramatic increase of network depth may cause more training errors instead. In this paper, we use the residual network to increase network depth and to mitigate the errors caused by depth increase simultaneously. Inspired by image simplification, we use color and texture features to obtain simplified image with multiple scales by means of region assimilation on the basis of super-pixels in order to reduce the complexity of images and to improve the accuracy of salient target detection. We refine the feature on pixel level by the multi-scale feature correction method to avoid the feature error when the image is simplified at the above-mentioned region level. The final full connection layer not only integrates features of multi-scale and multi-level but also works as classifier of salient targets. The experimental results show that proposed model achieves better results than other salient object detection models based on original deep learning networks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Developing a Hypothetical Multi-Dimensional Learning Progression for the Nature of Matter

ERIC Educational Resources Information Center

Stevens, Shawn Y.; Delgado, Cesar; Krajcik, Joseph S.

2010-01-01

We describe efforts toward the development of a hypothetical learning progression (HLP) for the growth of grade 7-14 students' models of the structure, behavior and properties of matter, as it relates to nanoscale science and engineering (NSE). This multi-dimensional HLP, based on empirical research and standards documents, describes how students…

Multi-scale Methods in Quantum Field Theory

NASA Astrophysics Data System (ADS)

Polyzou, W. N.; Michlin, Tracie; Bulut, Fatih

2018-05-01

Daubechies wavelets are used to make an exact multi-scale decomposition of quantum fields. For reactions that involve a finite energy that take place in a finite volume, the number of relevant quantum mechanical degrees of freedom is finite. The wavelet decomposition has natural resolution and volume truncations that can be used to isolate the relevant degrees of freedom. The application of flow equation methods to construct effective theories that decouple coarse and fine scale degrees of freedom is examined.

Multi-scale analysis of the occurrence of Pb, Cr and Mn in the NIST standards: Urban dust (SRM 1649a) and indoor dust (SRM 2584)

NASA Astrophysics Data System (ADS)

Jiang, Mingyu; Nakamatsu, Yuki; Jensen, Keld A.; Utsunomiya, Satoshi

2014-01-01

Adverse health effects of ambient particulate matters are closely related to the speciation of the constituting organic matters and toxic metals. To determine multi-parameters of the metal speciation in urban and indoor dusts, we have performed systematic bulk- to nano-scale (“multi-scale”) analysis on the speciation of Pb, Mn, and Cr in two National Institute of Standards and Technology (NIST) standard reference materials (SRMs): urban dust (SRM 1649a) and indoor dust (SRM 2584), utilizing X-ray absorption near-edge structure, powder X-ray diffraction analysis, electron microprobe analysis, scanning electron microscopy, and transmission electron microscopy. Major crystalline phases are quartz, gypsum, kaolinite, and muscovite in SRM 1649a, while quartz, gypsum, calcite, and possibly muscovite (or chabazite) in SRM 2584. A number of Pb sulfate nanoparticles (50-200 nm) occur in SRM 1649a, whereas micron-sized Pb carbonate is present containing various concentrations of Zn and Ti in the complex texture in SRM 2584. Relatively soluble Mn(II) sulfate is the bulk-averaged Mn speciation in SRM 1649a, although discrete Mn sulfate particles are not characterized by individual particle analysis, implying the diluted Mn distribution within other sulfate. In SRM 2584, Mn speciation includes a mixture of oxides and carbonates, and trace Mn in chromite. Chromite (FeCr2O4) is the major Cr speciation in SRM1694a, while unidentified Cr(III) phases with minor chromite and Pb chromate are present in SRM 2584, among which the Pb chromate is composed of Cr(VI). A significant number of the metal-bearing particles are distributed to the submicron-size fraction in the urban dust, SRM 1649a, suggesting that these metal nanoparticles can potentially penetrate into the deep respiratory system. This study demonstrates that multi-scale analysis combining nano and bulk analytical techniques is a powerful approach to investigate the multi-parameters of metal-bearing nanoparticles in

Lenz's law and dimensional analysis

NASA Astrophysics Data System (ADS)

Pelesko, John A.; Cesky, Michael; Huertas, Sharon

2005-01-01

We show that the time it takes a magnet to fall through a nonmagnetic metallic tube may be found via dimensional analysis. The simple analysis makes this classic demonstration of Lenz's law accessible qualitatively and quantitatively to students with little knowledge of electromagnetism and only elementary knowledge of calculus. The analysis provides a new example of the power and limitations of dimensional analysis.

Orientation of airborne laser scanning point clouds with multi-view, multi-scale image blocks.

PubMed

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters.

Orientation of Airborne Laser Scanning Point Clouds with Multi-View, Multi-Scale Image Blocks

PubMed Central

Rönnholm, Petri; Hyyppä, Hannu; Hyyppä, Juha; Haggrén, Henrik

2009-01-01

Comprehensive 3D modeling of our environment requires integration of terrestrial and airborne data, which is collected, preferably, using laser scanning and photogrammetric methods. However, integration of these multi-source data requires accurate relative orientations. In this article, two methods for solving relative orientation problems are presented. The first method includes registration by minimizing the distances between of an airborne laser point cloud and a 3D model. The 3D model was derived from photogrammetric measurements and terrestrial laser scanning points. The first method was used as a reference and for validation. Having completed registration in the object space, the relative orientation between images and laser point cloud is known. The second method utilizes an interactive orientation method between a multi-scale image block and a laser point cloud. The multi-scale image block includes both aerial and terrestrial images. Experiments with the multi-scale image block revealed that the accuracy of a relative orientation increased when more images were included in the block. The orientations of the first and second methods were compared. The comparison showed that correct rotations were the most difficult to detect accurately by using the interactive method. Because the interactive method forces laser scanning data to fit with the images, inaccurate rotations cause corresponding shifts to image positions. However, in a test case, in which the orientation differences included only shifts, the interactive method could solve the relative orientation of an aerial image and airborne laser scanning data repeatedly within a couple of centimeters. PMID:22454569

visPIG--a web tool for producing multi-region, multi-track, multi-scale plots of genetic data.

PubMed

Scales, Matthew; Jäger, Roland; Migliorini, Gabriele; Houlston, Richard S; Henrion, Marc Y R

2014-01-01

We present VISual Plotting Interface for Genetics (visPIG; http://vispig.icr.ac.uk), a web application to produce multi-track, multi-scale, multi-region plots of genetic data. visPIG has been designed to allow users not well versed with mathematical software packages and/or programming languages such as R, Matlab®, Python, etc., to integrate data from multiple sources for interpretation and to easily create publication-ready figures. While web tools such as the UCSC Genome Browser or the WashU Epigenome Browser allow custom data uploads, such tools are primarily designed for data exploration. This is also true for the desktop-run Integrative Genomics Viewer (IGV). Other locally run data visualisation software such as Circos require significant computer skills of the user. The visPIG web application is a menu-based interface that allows users to upload custom data tracks and set track-specific parameters. Figures can be downloaded as PDF or PNG files. For sensitive data, the underlying R code can also be downloaded and run locally. visPIG is multi-track: it can display many different data types (e.g association, functional annotation, intensity, interaction, heat map data,…). It also allows annotation of genes and other custom features in the plotted region(s). Data tracks can be plotted individually or on a single figure. visPIG is multi-region: it supports plotting multiple regions, be they kilo- or megabases apart or even on different chromosomes. Finally, visPIG is multi-scale: a sub-region of particular interest can be 'zoomed' in. We describe the various features of visPIG and illustrate its utility with examples. visPIG is freely available through http://vispig.icr.ac.uk under a GNU General Public License (GPLv3).

Space-coiling fractal metamaterial with multi-bandgaps on subwavelength scale

NASA Astrophysics Data System (ADS)

Man, Xianfeng; Liu, Tingting; Xia, Baizhan; Luo, Zhen; Xie, Longxiang; Liu, Jian

2018-06-01

Acoustic metamaterials are remarkably different from conventional materials, as they can flexibly manipulate and control the propagation of sound waves. Unlike the locally resonant metamaterials introduced in earlier studies, we designed an ultraslow artificial structure with a sound speed much lower than that in air. In this paper, the space-coiling approach is proposed for achieving artificial metamaterial for extremely low-frequency airborne sound. In addition, the self-similar fractal technique is utilized for designing space-coiling Mie-resonance-based metamaterials (MRMMs) to obtain a band-dispersive spectrum. The band structures of two-dimensional (2D) acoustic metamaterials with different fractal levels are illustrated using the finite element method. The low-frequency bandgap can easily be formed, and multi-bandgap properties are observed in high-level fractals. Furthermore, the designed MRMMs with higher order fractal space coiling shows a good robustness against irregular arrangement. Besides, the proposed artificial structure was found to modify and control the radiation field arbitrarily. Thus, this work provides useful guidelines for the design of acoustic filtering devices and acoustic wavefront shaping applications on the subwavelength scale.

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.

Computational Analysis of Multi-Rotor Flows

NASA Technical Reports Server (NTRS)

Yoon, Seokkwan; Lee, Henry C.; Pulliam, Thomas H.

2016-01-01

Interactional aerodynamics of multi-rotor flows has been studied for a quadcopter representing a generic quad tilt-rotor aircraft in hover. The objective of the present study is to investigate the effects of the separation distances between rotors, and also fuselage and wings on the performance and efficiency of multirotor systems. Three-dimensional unsteady Navier-Stokes equations are solved using a spatially 5th order accurate scheme, dual-time stepping, and the Detached Eddy Simulation turbulence model. The results show that the separation distances as well as the wings have significant effects on the vertical forces of quadroror systems in hover. Understanding interactions in multi-rotor flows would help improve the design of next generation multi-rotor drones.

Multi-scale Material Parameter Identification Using LS-DYNA® and LS-OPT®

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

Stander, Nielen; Basudhar, Anirban; Basu, Ushnish

2015-09-14

Ever-tightening regulations on fuel economy, and the likely future regulation of carbon emissions, demand persistent innovation in vehicle design to reduce vehicle mass. Classical methods for computational mass reduction include sizing, shape and topology optimization. One of the few remaining options for weight reduction can be found in materials engineering and material design optimization. Apart from considering different types of materials, by adding material diversity and composite materials, an appealing option in automotive design is to engineer steel alloys for the purpose of reducing plate thickness while retaining sufficient strength and ductility required for durability and safety. A project tomore » develop computational material models for advanced high strength steel is currently being executed under the auspices of the United States Automotive Materials Partnership (USAMP) funded by the US Department of Energy. Under this program, new Third Generation Advanced High Strength Steel (i.e., 3GAHSS) are being designed, tested and integrated with the remaining design variables of a benchmark vehicle Finite Element model. The objectives of the project are to integrate atomistic, microstructural, forming and performance models to create an integrated computational materials engineering (ICME) toolkit for 3GAHSS. The mechanical properties of Advanced High Strength Steels (AHSS) are controlled by many factors, including phase composition and distribution in the overall microstructure, volume fraction, size and morphology of phase constituents as well as stability of the metastable retained austenite phase. The complex phase transformation and deformation mechanisms in these steels make the well-established traditional techniques obsolete, and a multi-scale microstructure-based modeling approach following the ICME [0]strategy was therefore chosen in this project. Multi-scale modeling as a major area of research and development is an outgrowth of the

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

A One-Dimensional Global-Scaling Erosive Burning Model Informed by Blowing Wall Turbulence

NASA Technical Reports Server (NTRS)

Kibbey, Timothy P.

2014-01-01

A derivation of turbulent flow parameters, combined with data from erosive burning test motors and blowing wall tests results in erosive burning model candidates useful in one-dimensional internal ballistics analysis capable of scaling across wide ranges of motor size. The real-time burn rate data comes from three test campaigns of subscale segmented solid rocket motors tested at two facilities. The flow theory admits the important effect of the blowing wall on the turbulent friction coefficient by using blowing wall data to determine the blowing wall friction coefficient. The erosive burning behavior of full-scale motors is now predicted more closely than with other recent models.

Developing a Multi-Dimensional Evaluation Framework for Faculty Teaching and Service Performance

ERIC Educational Resources Information Center

Baker, Diane F.; Neely, Walter P.; Prenshaw, Penelope J.; Taylor, Patrick A.

2015-01-01

A task force was created in a small, AACSB-accredited business school to develop a more comprehensive set of standards for faculty performance. The task force relied heavily on faculty input to identify and describe key dimensions that capture effective teaching and service performance. The result is a multi-dimensional framework that will be used…

Unsupervised DInSAR processing chain for multi-scale displacement analysis

NASA Astrophysics Data System (ADS)

Casu, Francesco; Manunta, Michele

2016-04-01

Earth Observation techniques can be very helpful for the estimation of several sources of ground deformation due to their characteristics of large spatial coverage, high resolution and cost effectiveness. In this scenario, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most effective methodologies for its capability to generate spatially dense deformation maps at both global and local spatial scale, with centimeter to millimeter accuracy. DInSAR exploits the phase difference (interferogram) between SAR image pairs relevant to acquisitions gathered at different times, but with the same illumination geometry and from sufficiently close flight tracks, whose separation is typically referred to as baseline. Among several, the SBAS algorithm is one of the most used DInSAR approaches and it is aimed at generating displacement time series at a multi-scale level by exploiting a set of small baseline interferograms. SBAS, and generally DInSAR, has taken benefit from the large availability of spaceborne SAR data collected along years by several satellite systems, with particular regard to the European ERS and ENVISAT sensors, which have acquired SAR images worldwide during approximately 20 years. Moreover, since 2014 the new generation of Copernicus Sentinel satellites has started to acquire data with a short revisit time (12 days) and a global coverage policy, thus flooding the scientific EO community with an unprecedent amount of data. To efficiently manage such amount of data, proper processing facilities (as those coming from the emerging Cloud Computing technologies) have to be used, as well as novel algorithms aimed at their efficient exploitation have to be developed. In this work we present a set of results achieved by exploiting a recently proposed implementation of the SBAS algorithm, namely Parallel-SBAS (P-SBAS), which allows us to effectively process, in an unsupervised way and in a limited time frame, a huge number of SAR images

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.

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart

PubMed Central

Amr, Ali; Neumann, Dominik; Georgescu, Bogdan; Seegerer, Philipp; Kamen, Ali; Haas, Jan; Frese, Karen S.; Irawati, Maria; Wirsz, Emil; King, Vanessa; Buss, Sebastian; Mereles, Derliz; Zitron, Edgar; Keller, Andreas; Katus, Hugo A.; Comaniciu, Dorin; Meder, Benjamin

2015-01-01

Background Despite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders. Methods and Results State-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters. Conclusion This paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation. PMID:26230546

A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

2016-06-01

In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

Urban Flow and Pollutant Dispersion Simulation with Multi-scale coupling of Meteorological Model with Computational Fluid Dynamic Analysis

NASA Astrophysics Data System (ADS)

Liu, Yushi; Poh, Hee Joo

2014-11-01

The Computational Fluid Dynamics analysis has become increasingly important in modern urban planning in order to create highly livable city. This paper presents a multi-scale modeling methodology which couples Weather Research and Forecasting (WRF) Model with open source CFD simulation tool, OpenFOAM. This coupling enables the simulation of the wind flow and pollutant dispersion in urban built-up area with high resolution mesh. In this methodology meso-scale model WRF provides the boundary condition for the micro-scale CFD model OpenFOAM. The advantage is that the realistic weather condition is taken into account in the CFD simulation and complexity of building layout can be handled with ease by meshing utility of OpenFOAM. The result is validated against the Joint Urban 2003 Tracer Field Tests in Oklahoma City and there is reasonably good agreement between the CFD simulation and field observation. The coupling of WRF- OpenFOAM provide urban planners with reliable environmental modeling tool in actual urban built-up area; and it can be further extended with consideration of future weather conditions for the scenario studies on climate change impact.

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.

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

Python Winding Itself Around Datacubes: How to Access Massive Multi-Dimensional Arrays in a Pythonic Way

NASA Astrophysics Data System (ADS)

Merticariu, Vlad; Misev, Dimitar; Baumann, Peter

2017-04-01

While python has developed into the lingua franca in Data Science there is often a paradigm break when accessing specialized tools. In particular for one of the core data categories in science and engineering, massive multi-dimensional arrays, out-of-memory solutions typically employ their own, different models. We discuss this situation on the example of the scalable open-source array engine, rasdaman ("raster data manager") which offers access to and processing of Petascale multi-dimensional arrays through an SQL-style array query language, rasql. Such queries are executed in the server on a storage engine utilizing adaptive array partitioning and based on a processing engine implementing a "tile streaming" paradigm to allow processing of arrays massively larger than server RAM. The rasdaman QL has acted as blueprint for forthcoming ISO Array SQL and the Open Geospatial Consortium (OGC) geo analytics language, Web Coverage Processing Service, adopted in 2008. Not surprisingly, rasdaman is OGC and INSPIRE Reference Implementation for their "Big Earth Data" standards suite. Recently, rasdaman has been augmented with a python interface which allows to transparently interact with the database (credits go to Siddharth Shukla's Master Thesis at Jacobs University). Programmers do not need to know the rasdaman query language, as the operators are silently transformed, through lazy evaluation, into queries. Arrays delivered are likewise automatically transformed into their python representation. In the talk, the rasdaman concept will be illustrated with the help of large-scale real-life examples of operational satellite image and weather data services, and sample python code.

Numerical simulation on hydromechanical coupling in porous media adopting three-dimensional pore-scale model.

PubMed

Liu, Jianjun; Song, Rui; Cui, Mengmeng

2014-01-01

A novel approach of simulating hydromechanical coupling in pore-scale models of porous media is presented in this paper. Parameters of the sandstone samples, such as the stress-strain curve, Poisson's ratio, and permeability under different pore pressure and confining pressure, are tested in laboratory scale. The micro-CT scanner is employed to scan the samples for three-dimensional images, as input to construct the model. Accordingly, four physical models possessing the same pore and rock matrix characteristics as the natural sandstones are developed. Based on the micro-CT images, the three-dimensional finite element models of both rock matrix and pore space are established by MIMICS and ICEM software platform. Navier-Stokes equation and elastic constitutive equation are used as the mathematical model for simulation. A hydromechanical coupling analysis in pore-scale finite element model of porous media is simulated by ANSYS and CFX software. Hereby, permeability of sandstone samples under different pore pressure and confining pressure has been predicted. The simulation results agree well with the benchmark data. Through reproducing its stress state underground, the prediction accuracy of the porous rock permeability in pore-scale simulation is promoted. Consequently, the effects of pore pressure and confining pressure on permeability are revealed from the microscopic view.

Numerical Simulation on Hydromechanical Coupling in Porous Media Adopting Three-Dimensional Pore-Scale Model

PubMed Central

Liu, Jianjun; Song, Rui; Cui, Mengmeng

2014-01-01

A novel approach of simulating hydromechanical coupling in pore-scale models of porous media is presented in this paper. Parameters of the sandstone samples, such as the stress-strain curve, Poisson's ratio, and permeability under different pore pressure and confining pressure, are tested in laboratory scale. The micro-CT scanner is employed to scan the samples for three-dimensional images, as input to construct the model. Accordingly, four physical models possessing the same pore and rock matrix characteristics as the natural sandstones are developed. Based on the micro-CT images, the three-dimensional finite element models of both rock matrix and pore space are established by MIMICS and ICEM software platform. Navier-Stokes equation and elastic constitutive equation are used as the mathematical model for simulation. A hydromechanical coupling analysis in pore-scale finite element model of porous media is simulated by ANSYS and CFX software. Hereby, permeability of sandstone samples under different pore pressure and confining pressure has been predicted. The simulation results agree well with the benchmark data. Through reproducing its stress state underground, the prediction accuracy of the porous rock permeability in pore-scale simulation is promoted. Consequently, the effects of pore pressure and confining pressure on permeability are revealed from the microscopic view. PMID:24955384

Collaborative Visualization and Analysis of Multi-dimensional, Time-dependent and Distributed Data in the Geosciences Using the Unidata Integrated Data Viewer

NASA Astrophysics Data System (ADS)

Meertens, C. M.; Murray, D.; McWhirter, J.

2004-12-01

Over the last five years, UNIDATA has developed an extensible and flexible software framework for analyzing and visualizing geoscience data and models. The Integrated Data Viewer (IDV), initially developed for visualization and analysis of atmospheric data, has broad interdisciplinary application across the geosciences including atmospheric, ocean, and most recently, earth sciences. As part of the NSF-funded GEON Information Technology Research project, UNAVCO has enhanced the IDV to display earthquakes, GPS velocity vectors, and plate boundary strain rates. These and other geophysical parameters can be viewed simultaneously with three-dimensional seismic tomography and mantle geodynamic model results. Disparate data sets of different formats, variables, geographical projections and scales can automatically be displayed in a common projection. The IDV is efficient and fully interactive allowing the user to create and vary 2D and 3D displays with contour plots, vertical and horizontal cross-sections, plan views, 3D isosurfaces, vector plots and streamlines, as well as point data symbols or numeric values. Data probes (values and graphs) can be used to explore the details of the data and models. The IDV is a freely available Java application using Java3D and VisAD and runs on most computers. UNIDATA provides easy-to-follow instructions for download, installation and operation of the IDV. The IDV primarily uses netCDF, a self-describing binary file format, to store multi-dimensional data, related metadata, and source information. The IDV is designed to work with OPeNDAP-equipped data servers that provide real-time observations and numerical models from distributed locations. Users can capture and share screens and animations, or exchange XML "bundles" that contain the state of the visualization and embedded links to remote data files. A real-time collaborative feature allows groups of users to remotely link IDV sessions via the Internet and simultaneously view and

Quantifying two-dimensional nonstationary signal with power-law correlations by detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Fan, Qingju; Wu, Yonghong

2015-08-01

In this paper, we develop a new method for the multifractal characterization of two-dimensional nonstationary signal, which is based on the detrended fluctuation analysis (DFA). By applying to two artificially generated signals of two-component ARFIMA process and binomial multifractal model, we show that the new method can reliably determine the multifractal scaling behavior of two-dimensional signal. We also illustrate the applications of this method in finance and physiology. The analyzing results exhibit that the two-dimensional signals under investigation are power-law correlations, and the electricity market consists of electricity price and trading volume is multifractal, while the two-dimensional EEG signal in sleep recorded for a single patient is weak multifractal. The new method based on the detrended fluctuation analysis may add diagnostic power to existing statistical methods.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the

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

An integrated multi-scale risk analysis procedure for pluvial flooding

NASA Astrophysics Data System (ADS)

Tader, Andreas; Mergili, Martin; Jäger, Stefan; Glade, Thomas; Neuhold, Clemens; Stiefelmeyer, Heinz

2016-04-01

Mitigation of or adaptation to the negative impacts of natural processes on society requires a better understanding of the spatio-temporal distribution not only of the processes themselves, but also of the elements at risk. Information on their values, exposures and vulnerabilities towards the expected impact magnitudes/intensities of the relevant processes is needed. GIS-supported methods are particularly useful for integrated spatio-temporal analyses of natural processes and their potential consequences. Hereby, pluvial floods are of particular concern for many parts of Austria. The overall aim of the present study is to calculate the hazards emanating from pluvial floods, to determine the exposure of given elements at risk, to determine their vulnerabilities towards given pluvial flood hazards and to analyze potential consequences in terms of monetary losses. The whole approach builds on data available on a national scale. We introduce an integrated, multi-scale risk analysis procedure with regard to pluvial flooding. Focusing on the risk to buildings, we firstly exemplify this procedure with a well-documented event in the city of Graz (Austria), in order to highlight the associated potentials and limitations. Secondly, we attempt to predict the possible consequences of pluvial flooding triggered by rainfall events with recurrence intervals of 30, 100 and 300 years. (i) We compute spatially distributed inundation depths using the software FloodArea. Infiltration capacity and surface roughness are estimated from the land cover units given by the official cadastre. Various assumptions are tested with regard to the inflow to the urban sewer system. (ii) Based on the inundation depths and the official building register, we employ a set of rules and functions to deduce the exposure, vulnerability and risk for each building. A risk indicator for each building, expressed as the expected damage associated to a given event, is derived by combining the building value and

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.

Adherence is a multi-dimensional construct in the POUNDS LOST trial

PubMed Central

Williamson, Donald A.; Anton, Stephen D.; Han, Hongmei; Champagne, Catherine M.; Allen, Ray; LeBlanc, Eric; Ryan, Donna H.; McManus, Katherine; Laranjo, Nancy; Carey, Vincent J.; Loria, Catherine M.; Bray, George A.; Sacks, Frank M.

2011-01-01

Research on the conceptualization of adherence to treatment has not addressed a key question: Is adherence best defined as being a uni-dimensional or multi-dimensional behavioral construct? The primary aim of this study was to test which of these conceptual models best described adherence to a weight management program. This ancillary study was conducted as a part of the POUNDS LOST trial that tested the efficacy of four dietary macro-nutrient compositions for promoting weight loss. A sample of 811 overweight/obese adults was recruited across two clinical sites, and each participant was randomly assigned to one of four macronutrient prescriptions: (1) Low fat (20% of energy), average protein (15% of energy); (2) High fat (40%), average protein (15%); (3) Low fat (20%), high protein (25%); (4) High fat (40%), high protein (25%). Throughout the first 6 months of the study, a computer tracking system collected data on eight indicators of adherence. Computer tracking data from the initial 6 months of the intervention were analyzed using exploratory and confirmatory analyses. Two factors (accounting for 66% of the variance) were identified and confirmed: (1) behavioral adherence and (2) dietary adherence. Behavioral adherence did not differ across the four interventions, but prescription of a high fat diet (vs. a low fat diet) was found to be associated with higher levels of dietary adherence. The findings of this study indicated that adherence to a weight management program was best conceptualized as being multi-dimensional, with two dimensions: behavioral and dietary adherence. PMID:19856202